Rogue Waves: Freaks of Nature Studied with Math and Lasers – Inside Science News Service

The elusive waves, once thought to be myths, are explained by the same math that's found in a wide range of settings.

(Inside Science) -- During Columbus third voyage to the Americas, as his six-ship fleet sailed around the southern tip of Trinidad, an island just off the coast of Venezuela, they encountered a freak wave taller than the ships mast. The wave hoisted the ships up to its peak before dropping them down into a huge trough. Columbus would later name the passageway Boca del Serpiente -- Mouth of the Serpent -- for the ferocity of its waters.

Once regarded as myths or pieces of folklore, rogue waves can spike out of nowhere and dissipate just moments later, terrifying sailors and sinking ships. Half a millennium would pass after Columbus encounter before the first rogue wave was measured by a scientific instrument. On New Years Day of 1995, the Draupner oil platform perched in the North Sea off the coast of Norway spotted a wave 84 feet tall -- more than twice the height of its neighboring waves.

Like stock market crashes and devastating earthquakes, the study of rogue waves has been plagued by the scarcity of data.

The Draupner wave was the first time that a rogue wave was actually observed by a scientific instrument; before that it was all just people telling about it. But if we want to learn more about these waves, well need to obtain better statistics and more data, said Tobias Grafke, a physicist from the University of Warwick in the U.K. He is an author of a paper published in the journal Physical Review X that explored the probabilities of rogue waves from a statistical perspective.

It's a very localized phenomenon that comes out of nowhere. I mean, you can just put certain measurement points somewhere and hope that a rogue wave would come by, but it's very, very rare, said Hadas Frostig, a physicist from Boston University not involved in Grafkes paper.

Moreover, rogue waves are so strong that they often destroy the instruments trying to measure them, said Grafke.

Due to the difficulty of collecting real-world data -- even a team of satellites would probably struggle to spot the fleeting, unpredictable waves -- researchers have mostly studied rogue waves in wave pools, dialing in specific conditions that might generate a rogue wave.

An in-lab rogue wave experiment by researchers from the University of Oxford and the University of Edinburgh. [Credit: Ton van den Bremer and Mark McAllister at the University of Oxford.]

Scientists think rogue waves can be generated via two main mechanisms. In the first, waves of different wavelengths, peaking at the same spot, combine to build a massive wave. Because each of their amplitudes simply adds up to form the final height of the rogue wave, it is referred to as a linear process. In contrast, the second mechanism is nonlinear and has to do with how waves with different wavelengths interact and exchange energy with each other. (Check out this infographic by Quanta Magazine that explains the difference between the two concepts.)

A rogue wave can be built linearly or nonlinearly, or a combination of both.

Depending on how a wave model is set up, the relative importance of the two mechanisms is different. What we want is a theory that can predict the probability of these waves and the way they evolve given the state of the ocean, said Grafke. In other words, a model that can predict rogue waves based on the ocean condition without having to predetermine the significance for each mechanism.

Grafke and his colleagues developed a model based on mathematical concepts called solitons and instantons. Solitons are solitary excitations in a field, such as single, short pulses of light; instantons are mathematical devices for interpreting rare events in systems where random processes are present.

According to Amin Chabchoub, who studies environmental fluid mechanics at the University of Sydney in Australia and was not involved in the paper, the model is unique in its approach to predicting the occurrence of rogue waves independent of the formation mechanism.

The study of waves is rarely limited to a single medium. (For example, we have previously covered how a phenomenon called excitable waves plays a role in vastly different systems such as wildfires and heart arrhythmia.)

Since 2007, researchers have begun studying rogue waves in systems where the abundance of data is not a problem because the waves can be easily generated in huge numbers with existing technologies. Theses waves also happen to be much, much faster: light.

Once people started studying rogue waves, it spurred this whole field where people are asking what kind of physics gives rise to these very rare, very extreme events, said Frostig, who recently published a paper in the journal Optica that used laser systems to study rogue waves.

Using optical systems, scientists can generate the immense amount of data required to gauge the probabilities of rogue waves arising under different mechanisms. They have observed that optical rogue waves occur more frequently than would be expected if the waves formation were governed by Gaussian statistics, commonly known as a bell curve.

According to Frostig, rogue wave experiments in optical systems have primarily been focusing on how light waves of different wavelengths interact with each other to generate an extreme event. She and her colleagues discovered these mechanisms alone cannot account for the frequency of rogue waves present in their system. In this relatively young field, new results often create more questions than they answer.

Optical rogue waves do not play a significant role in fiber optics systems like those that bring internet to homes and offices, because the fibers are designed to prevent signals of different frequencies interfering with each other. Nor will ocean rogue wave models likely become a practical solution for safeguarding sailors anytime soon.

But the study of rogue waves and the statistics that govern them is not limited to the ocean or fiber optics. For example, speckle patterns -- the graininess of a laser when it is projected on a surface -- is related to optical rogue waves and has applications in imaging techniques.

Rogue waves also share a mathematical framework with other systems -- some of which arent even waves. Protein folding, disease transmission and even some animal population estimation techniques all display similar statistical characteristics as rogue waves.

The underlying math itself is very general, and it tells you how a system evolves around the probability of an extremely rare event, things like extreme shocks in acoustics systems, extreme voltage vortices and models for turbulence, said Grafke. It doesn't need to be a rogue wave.

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Rogue Waves: Freaks of Nature Studied with Math and Lasers - Inside Science News Service

Power To The Tenth Power – IT Jungle

August 17, 2020Timothy Prickett Morgan

This is one of my favorite times of the year, with the Hot Chips symposium usually underway this week at Stanford University and all the vendors big and small trotting out their, well, hottest chippery. In this case, hot means extremely interesting but it often means burning shedloads of watts as well. But this is the time that the chip architects show off what they have been working on for four or five years and what has already been in production in recent months or will be in the coming months.

IBM tends to jump the gun a bit with its Power processors, and is doing so a little more than usual with the Power10 processor, which we frankly had hoped would be available later this year rather than later next year. But none of that matters. What does matter is that Power9 is giving customers plenty of headroom in compute at the moment and that Power10 will, thanks to the innovative engineering that Big Blue has come up with, be well worth the wait.

This is the kind of processor complex and system architecture that we have been waiting to see arrive for a long, long time. And we will be getting into the details of that architecture in the coming weeks after IBMs presentation is done at Hot Chips this week. In the meantime, IBM talked with us about how Power10 extends the lead that the Power architecture has over X86 and Arm alternatives for enterprise systems and we are going to focus on that ahead of the Power10 preview and talk to the top brass at Big Blue about how they had better start thinking about systems differently and get people to start thinking about them differently and then invest in IBMs own technology and build the best damned public cloud in the world based on it. We are talking about a moonshot-class investment the likes of which we have not seen out of IBM since it invested $100 million to create the BlueGene protein folding supercomputer back in 1999 to break through the petaflops performance barrier.

So without further ado, here is the wafer of Power10 chips that have come back as early silicon from the fabs at Samsun Electronics, IBMs manufacturing partner:

The research alliance that IBM set up with Samsung, Applied Materials, AMD, GlobalFoundries, and others many years ago has contributed tweaks to the 7 nanometer process that Samsung is using to make the Power10 chips, according to IBM, which is not just using Samsungs plain vanilla 7 nanometer etching, which is called V1 and which uses extreme ultraviolet (EUV) lithography techniques. (Similar to the ones that GlobalFoundries, the former AMD fab cut loose several years ago, was working on for Power10 when it decided in August 2018 to spike the whole 7 nanometer effort, and importantly both flavors of 7 nanometer using regular lithography and using EUV were killed off. Thus driving IBM into Samsungs waiting arms as a foundry partner for the Power10 chips. (Intel and Taiwan Semiconductor Manufacturing Corp were not going to get the deals, that is for sure.)

Samsung started building its V1 fab back in February 2018 and invested $6 billion in the effort in the first two years and has probably spend a few billion dollars more this year. Back in April 2019, Samsung said it was going to invest $115 billion between then and 2030 to build up its foundry both for its own use and for others like IBM. And it is about the safest bet that IBM has outside of GlobalFoundries when it comes to picking a fab partner, given its long history of collaboration with Samsung and the latter companys desire to boost its merchant foundry credentials. Everybody including Intel had better hope Samsung gets good at this, because there are not enough deep pockets otherwise to allay all of the risk as we move from 7 nanometers down to 5 nanometers down to 3 nanometers looking ahead in the current decade.

We are not at liberty to say much about Power10 as we go to press for the Monday issue of The Four Hundred, but we will do a series of follow-up stories to drill down into different aspects of the machines, which we have been prebriefed about under embargo for later today. Here is one thing that IBM did allow us to share with you:

I have only seen the core count of the Power10 chip detailed in a few internal roadmaps, and all of them said that Power10 would have 48 cores. This made logical sense, given that Power8 maxxed out at 12 cores and Power9 maxxed out at 24 skinny cores (or 12 fat ones) across the same 96 threads per die, mostly enabled from the shrink from 22 nanometers with Power8 to 14 nanometers with Power9. It was logical to assume that with the shrink to 7 nanometers that the core count could double up again.

What we now know from the roadmap above is that with the shrink to 7 nanometers, IBM gutted the core design and started with a clean slate to maximize the new 7 nanometer process something that we suspect it was not planning to do with the GlobalFoundries 7 nanometer process and crammed 16 fat cores or 32 skinny cores on a die. Only 15 fat cores or 30 skinny cores are activated to help improve the yield on the chips, assuming that at least 1 in 16 of the cores will be a dud on the new 7 nanometer process, as IBM and Samsung are assuming. At some point, when the yields on the V1 process improve, IBM could activate that latent 16th core and there is an instant performance upgrade for those using a newer stepping of the Power10 chip. The gutting of the microarchitecture is what has allowed IBM to boost the core count from 12 to 16 per chip moving from Power9 to Power10, which is considerably more than expected.

With Power10, IBM is cutting down on the number of chips it is making, which will also help lower costs but it also calls into question whether there will be a single-core or even dual-core variant aimed specifically at smaller IBM i shops. (We will fight that battle later.)

Rather than having three different chip implementations a half skinny chip and a full skinny chip for machines with one or two sockets and a full fat chip for big NUMA iron as it did with Power8 and Power9, IBM moving to a single chip with fat cores and putting one or two of them into a socket to get 30 cores or 60 cores into a socket. This is a much more aggressive strategy, and interestingly, either the single-chip module (SCM) or dual-chip module (DCM) variants of the Power10 chip can be run in SMT4 (four threads per core) or SMT8 (eight threads per core) mode. This mode is not switchable by users, but by IBM at the time it packages up the processor. In the past, to get 24 cores meant running in SMT4 mode, or four threads per core, and not all systems had this capability. This was just a funny way of isolating threads and caches to lower the core count and therefore enterprise software licenses for SMT8 customers, but it also meant raising the per-socket price on software running on the 24-core Power9 variant for software that was priced based on cores and not sockets. It would be useful if IBM could make this SMT level settable at system boot, but it is hard-coded into the processor microcode that customers cannot change because of the software pricing issue mentioned above.

We strongly suspect that IBM never intended to do a monolithic Power10 die with 48 cores on it, but rather a 7 nanometer shrink of the 24-core Nimbus part with some tweaks and then put two of them into a single socket to create a throughput monster. With the Power10 chip as it will be delivered, IBM can, in theory once yields improve, provide customers with 33 percent more cores and, if history is any guide, somewhere around 3X the raw throughput at the 4 GHz design point that IBM has used for Power chips since the Power7 way back in 2010. (The Power6 had a 5 GHz design point, which was quite impressive but not sustainable because Dennard scaling and Moores Law scaling were running out of steam.)

We cant say a lot about it right now, but this memory clustering technology, and indeed the whole memory subsystem of the Power10 chip, is the killer technology with Power10. IBM will be able to do things that other architectures simply cannot, with multi-petabyte memory clustering and sharing across large numbers of Power10 systems.

And that is why IBM has to be the one to invest in building and using these systems, to demonstrate their capabilities, and to make sure Power10 systems are available on the IBM Cloud on Day One of their launch and in huge numbers, not in prototype and proofs of concept onesies and twosies here and there around a dozen or so cloud regions. This is not about drinking the Kool-Aid, which is easy enough, but eating your own dog food first, as we say in this IT business. IBM has to move its own apps to its own cloud running on Power10 iron and be the case study that others can learn from and benefit from.

Theres plenty of time between now and the end of 2021 to make that happen, and IBM i customers as well as those running AIX and Linux should all be invited to come along for the ride.

Power Systems Slump Is Not As Bad As It Looks

The Path Truly Opens To Alternate Power CPUs, But Is It Enough?

Powers Of Ten

What Open Sourcing Powers ISA Means For IBM i Shops

IBMs Plan For Etching Power10 And Later Chips

The Road Ahead For Power Is Paved With Bandwidth

IBM Puts Future Power Chip Stakes In The Ground

What Will IBM i Do With A Power10 Processor?

Samsung Joins The OpenPower Consortium Party

Read more here:
Power To The Tenth Power - IT Jungle

PHILANTROPY IN EDUCATION TOWARDS THE GREATER GOOD – The Star Online

BEING Master of a Cambridge College has its highlights, one of the most pleasurable of which is meeting our benefactors.

My college, Gonville and Caius, has thousands of benefactors, but only the most eminent are commemorated in stone on the Benefactors Wall inside the Great Gate that looks onto the busiest part of Cambridge.

The first name on the wall is the co-founder Edmund Gonville (1348) and the 30th is Jeffrey Cheah, honorary fellow of the college.

The Benefactors Wall at Cambridge College.

One of the greatest Jewish rabbis was Maimonides (1138-1204). As well as codifying religious law, he was also a philosopher, and his day job was being a medical doctor.

Indeed, he was physician to the great Sultan Saladin, and much admired by Islamic scientists and scholars.

He formulated Eight Levels of Giving applied to charitable donations. The highest level is: Giving an interest-free loan to a person in need; forming a partnership with a person in need; giving a grant to a person in need; finding a job for a person in need; so long as that loan, grant, partnership or job results in the person no longer living by relying upon others.

This highest level of philanthropy encompasses precisely what Tan Sri Dr Jeffrey Cheah through his Foundation does.

Grants are awarded to scientists and educators to enable them to carry out their groundbreaking research and scholarship, and it works in partnership with them; this also financially supports young people massively so they will be able to undertake higher education, have jobs and contribute to Malaysian society.

To cap it all, medicine is a central part of those activities. Maimonides really would have approved.

It is for those reasons I have enjoyed so much my relationship with Tan Sri Dr Jeffrey Cheah and the Jeffrey Cheah Foundation we are working together in a partnership that improves medicine, science and education in my college and university, and in our partners institutions in Malaysia for the benefit of the world.

I take pride in being an Honorary Jeffrey Cheah Distinguished Professor so I can continue being a small part in this great partnership.

Crises bring out the worst and the best in society. Some politicians who have spent their careers disregarding the truth have discovered to their cost and the even greater cost of their populations that viruses take no notice of lies.

Crazy groups protest against vaccinations and even claim that Bill Gates, who is a fine philanthropist, is putting microchips in vaccines, and 5G networks spread the virus.

But so many people in every walk of life are doing their bit, from delivery drivers dropping off goods to those isolating at home to people sewing masks and protective gear. Much kindness is shining through.

Low paid healthcare workers are risking their lives caring for the sick and elderly.

Doctors, scientists and engineers in global collaboration have risen as one to the task of tackling the pandemic.

Developments in biotechnology and diagnostics that have sprung from fundamental work on DNA, proteins and molecular and cellular biology are being employed in force.

Scientists are challenging ideas and concepts as new facts are discovered in order to make progress.

I take pride in being a scientist and being part of the scientific movement that has led to the breakthroughs that are allowing the rapid response to the crisis.

Experimental scientists, however, need considerable support and infrastructure in order to carry out this critical research. Much of it is provided by governments, but it is never enough and sometimes too driven by politics or not flexible enough for unpredictable innovation.

Philanthropic individuals and organisations have for long catalysed scientific progress by funding individuals and laboratories and hospitals.

Long live philanthropy and those, like Tan Sri Dr Jeffrey Cheah, who selflessly practise it in the interests of mankind.

About Prof Sir Alan Fersht FRS FMedSci

Honorary Jeffrey Cheah Distinguished Professor

Master of Gonville and Caius College, Cambridge 2008-2018

Herschel Smith Professor of Organic Chemistry, University of Cambridge

A world leading protein scientist, Prof Sir Alan Fersht FRS is widely regarded as one of the main pioneers of protein engineering, a process he developed to analyse the structure, activity and folding of proteins.

He studied at Gonville and Caius College, and earned his PhD degree in 1968. He was Master of Gonville and Caius College, Cambridge from 2012-2018.

In August 2020, Fersht was awarded the Copley Medal of the Royal Society, the most prestigious science prize in the UK and the worlds oldest, dating back to 1731. The medal is awarded for outstanding achievements in research in any branch of science. Previous winners encompass the most famous scientists of the last few centuries including Joseph Priestly, Benjamin Franklin, Charles Darwin, Dmitri Mendeleev, Albert Einstein Niels Bohr as well as Francis Crick and Stephen Hawking, both Fellows of Gonville and Caius.

With interests spanning chemistry and biology, he has been appointed to three of the most prestigious societies in the US Foreign Associate of the National Academy of Sciences (USA); Honorary Foreign Member of the American Academy of Arts and Sciences; and Foreign Honorary Member of the American Philosophical Society.

He is a member of prestigious UK and European academies Fellow of the Royal Society of London; Member of European Molecular Biology Organisation (EMBO); and Member of Academia Europaea. On top of co-founding three biotech companies, Fersht is also the recipient of many global recognitions including the Gabor Medal of the Royal Society for Molecular Biology, its Davy Medal for Chemistry, and Royal Medal for his work on protein folding.

Both Fersht and Nobel Prize winner Sir Gregory Winter FRS, his collaborator, were knighted for their work on protein engineering.

This article is brought to you by Jeffrey Cheah Foundation in conjunction with its 10th anniversary.

Related stories:

https://www.thestar.com.my/news/nation/2020/07/19/leaving-a-legacy-to-inspire

https://www.thestar.com.my/news/nation/2020/07/19/setting-the-bar-in-education#cxrecs_s

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PHILANTROPY IN EDUCATION TOWARDS THE GREATER GOOD - The Star Online

Folding@home infectious disease research with Spot Instances – idk.dev

This post was contributed by Jarman Hauser, Jessie Xie, and Kinnar Kumar Sen.

Folding@home(FAH) is a distributed computing project that uses computational modeling to simulate protein structure, stability, and shape (how it folds). These simulationshelp to advancedrug discoveries and cures for diseases linked to protein dynamics within human cells. The FAH software crowdsources its distributed compute platform allowing anyone to contribute by donating unused computational resources from personal computers, laptops, and cloud servers.

In this post, I walk through deploying EC2 Spot Instances, optimized for the latest Folding@home client software. I describe how to be flexible across a combination ofGPU-optimized Amazon EC2 Spot Instances configured in anEC2 Auto Scaling group. The Auto Scaling group handles launching and maintaining a desiredcapacity, and automatically request resources to replace any that are interrupted or manually shut down.

Spot Instances are spare EC2 capacity available at up to a 90% discount compared to On-Demand Instance prices. The only difference between On-Demand Instance and Spot Instances is that Spot Instances can be interrupted by EC2 with two minutes of notification when EC2 needs the capacity back. This makes Spot Instances a great fit for stateless, fault-tolerant workloads like big data, containers, batch processing, AI/ML training, CI/CD and test/dev. For more information, see Amazon EC2 Spot Instances.

In addition to being flexible across instance types, another best practice for using Spot Instances effectively is to select the appropriate allocation strategy. Allocation strategies in EC2 Auto Scaling help you automatically provision capacity according to your workload requirements. We recommend that using the capacity optimized strategy to automatically provision instances from the most-available Spot Instance pools by looking at real-time capacity data. Because your Spot Instance capacity is sourced from pools with optimal capacity, this decreases the possibility that your Spot Instances are reclaimed. For more information about allocation strategies, see Spot Instances in the EC2 Auto Scaling user guide and configuring Spot capacity optimization in this user guide.

AmazonCloudWatchinstance metrics and logs for real-time monitoring of the protein folding progress.

To complete the setup, you must have an AWS account with permissions to the listed resources above. When you sign up for AWS, your AWS account is automatically signed up for all services in AWS, including Amazon EC2. If you dont have an AWS account, find more info about creating an accounthere.

The AWS CloudFormation (CFn) template includes customizable configuration parameters. Some of these settings, such as instance type, affect the cost of deployment. For cost estimates, see the pricing pages for each AWS service you are using. Prices are subject to change. You are responsible for the cost of the AWS services used. There is no additional cost for using the CFn template.

Note: There is no additional charge to use Deep Learning AMIs you pay only for the AWS resources while theyre running. Folding@home client software is a free, open-source software that is distributed under theFolding@home EULA.

Tip: After you deploy the AWS CloudFormationtemplate, we recommend that you enable AWS Cost Explorer. Cost Explorer is aneasy-to-use interface that lets you visualize, understand, and manage your AWS costs and usage e.g. you can break down costs to show hourly costs for your protein folding project.

First thing you must do is download, then make a few edits to the template.

Once downloaded, open the template file in your favorite text editor to make a few edits to the configuration before deploying.

In theUser Information section, you have the option to create a unique user name, join or create a new team, or contribute anonymously. For this example, I leave the values set to default and contribute as an anonymous user, the default team. More details about teams and leaderboards can be foundhereand details about PASSKEYshere.

Once edited and saved to a location you can easily find later, in the next section youll learn how to upload the template in the AWS CloudFormation console.

Next, log into the AWS Management Console, choose the Region you want to run the solution in, then navigate to AWSCloudFormation to launch the template.

In the AWS CloudFormation console, click on Create stack. Upload the template we just configured and click on Next to specify stack details.

Enter a stack name and adjust the capacity parameters as needed. In this example I set the desiredCapacity and minSize at 2 to handle protein folding jobs assigned to the client, and then the maxSize set at 12. Setting your maxSize to 12 ensures you have capacity for larger jobs that get assigned. These parameters can be adjusted based on your desired capacity.

If breaking out usage and cost data is required,, you can optionally add additional configurations like tags, permissions, stack policies, rollback options, and more advanced options in the next stack configuration step. Click Next to Review and then create the stack.

Under the Events tab, you can see the status of the AWS resources being created. When the status is CREATE_COMPLETE (approx. 35 minutes), the environment with Folding@home is installed and ready.Once the stack is created, the GPU instances will begin protein simulation.

The AWS CloudFormation template creates a log group fahlog that each of the instances send log data to. This allows you to visualize the protein folding progress in near real time via the Amazon CloudWatch console. To see the log data, navigate over to the Resources tab and click on the cloudWatchLogGroup link for fahlog. Alternatively, you can navigate to the Amazon CloudWatch console and choose fahlog under log groups.Note: Sometimes it takes a bit of time for Folding@Home Work Units (WU) to be downloaded in the instances and allocate all the available GPUs.

In the CloudWatch console, check out the Insights feature in the left navigation menu to see analytics for your protein folding logs. Select fahlog in the search box and run the default query that is provided for you in the query editor window to see your protein folding results.

Another thing you can do is create a dashboard in the CloudWatch console to automatically refresh based on the time intervals you set. Under Dashboardsin the left navigation bar, I was able to quickly create a few widgets to visualize CPU utilization, network in/out, and protein folding completed steps. This is a nifty tool that, with a little more time, you could configure more detailed metrics like cost per fold, and GPU monitoring.

You can let this run as long as you want to contribute to this project. When youre ready to stop, AWS CloudFormation gives us the option to delete the stack and resources created.On the AWS CloudFormation console, select the stack, and select delete.When you delete a stack, you delete the stack and all of its resources.

In this post, I shared how to launch a cluster of EC2 GPU-optimized Spot Instances to aid in Folding@homes protein dynamics research that could lead to therapeutics for infectious diseases. I leveraged Spot best practices by being flexible with instance selections across multiple families, sizes, and Availability Zones, and by choosing the capacity-optimized allocation strategy to ensure our cluster scales optimally and securely. Now you are ready to donate compute capacity with Spot Instances to aid disease research efforts on Folding@home.

Folding@home is currently based at the Washington University School of Medicine in St. Louis, under the directorship of Dr. Greg Bowman. The project was started by the Pande Laboratory atStanford University, under the direction of Dr.Vijay Pande, who led the project until 2019.[4]Since 2019, Folding@home has been led by Dr. Greg Bowman ofWashington University in St. Louis, a former student of Dr. Pande, in close collaboration with Dr. John Chodera of MSKCC and Vince Voelz of Temple University.[5]

With heightened interest in the project, Folding@home has grown to a community of2M+ users, bringing together the compute power of over 600K GPUs and 1.6M CPUs.

This outpouring of support has made Folding@home one of the worlds fastest computing systems achievingspeeds of approximately 1.2exaFLOPS, or 2.3 x86 exaFLOPS, by April 9, 2020 making it the worlds firstexaFLOP computing system.Folding@homes COVID-19 effortspecifically focuses on better understanding how the viral proteins moving parts enable to infect a human host, evade an immune response, and create new copies of the virus.The project is leveraging this insight to help design new therapeutic antibodies and small molecules that might prevent infection. They are engaged with a number of experimental collaborators to quickly iterate between computational design and experimental testing.

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Folding@home infectious disease research with Spot Instances - idk.dev

Nine Cambridge researchers among this years Royal Society medal and award winners – India Education Diary

He is one of the 25 Royal Society medals and awards winners announced today, nine of whom are researchers at the University of Cambridge. The annual prizes celebrate exceptional researchers and outstanding contributions to science across a wide array of fields.

President of the Royal Society, Venki Ramakrishnan, said:

The Royal Societys medals and awards celebrate those researchers whose ground-breaking work has helped answer fundamental questions and advance our understanding of the world around us. They also champion those who have reinforced sciences place in society, whether through inspiring public engagement, improving our education system, or by making STEM careers more inclusive and rewarding.

This year has highlighted how integral science is in our daily lives, and tackling the challenges we face, and it gives me great pleasure to congratulate all our winners and thank them for their work.

Sir Alan Fersht FMedSci FRS, Emeritus Professor in the Department of Chemistry and former Master of Gonville and Caius College, is awarded the Copley Medal for the development and application of methods to describe protein folding pathways at atomic resolution, revolutionising our understanding of these processes.

Most of us who become scientists do so because science is one of the most rewarding and satisfying of careers and we actually get paid for doing what we enjoy and for our benefitting humankind. Recognition of ones work, especially at home, is icing on the cake, said Sir Alan. Like many Copley medallists, I hail from a humble immigrant background and the first of my family to go to university. If people like me are seen to be honoured for science, then I hope it will encourage young people in similar situations to take up science.

As the latest recipient of the Royal Societys premier award, Sir Alan joins an elite group of scientists, that includes Charles Darwin, Albert Einstein and Dorothy Hodgkin, and more recently Professor John Goodenough (2020) for his research on the rechargeable lithium battery, Peter Higgs (2015), the physicist who hypothesised the existence of the Higgs Boson, and DNA fingerprinting pioneer Alec Jeffreys (2014).

Professor Barry Everitt FMedSci FRS, from the Department of Psychology and former Master of Downing College, receives the Croonian Medal and Lecture for research which has elucidated brain mechanisms of motivation and applied them to important societal issues such as drug addiction.

Professor Everitt said: In addition to my personal pride about having received this prestigious award, I hope that it helps draw attention to experimental addiction research, its importance and potential.

Professor Herbert Huppert FRS of the Department of Applied Mathematics and Theoretical Physics, and a Fellow of Kings College, receives a Royal Medal for outstanding achievements in the physical sciences. He has been at the forefront of research in fluid mechanics. As an applied mathematician he has consistently developed highly original analysis of key natural and industrial processes. Further to his research, he has chaired policy work on how science can help defend against terrorism, and carbon capture and storage in Europe.

In addition to the work for which they are recognised with an award, several of this years recipients have also been working on issues relating to the COVID-19 pandemic.

Professor Julia Gog of the Department of Applied Mathematics and Theoretical Physics and a Fellow of Queens College, receives the Rosalind Franklin Award and Lecture for her achievements in the field of mathematics. Her expertise in infectious diseases and virus modelling has seen her contribute to the pandemic response, including as a participant at SAGE meetings. The STEM project component of her award will produce resources for Key Stage 3 (ages 11-14) maths pupils and teachers exploring the curriculum in the context of modelling epidemics and infectious diseases and showing how maths can change the world for the better.

The Societys Michael Faraday Prize is awarded to Sir David Spiegelhalter OBE FRS, of the Winton Centre for Centre for Risk and Evidence Communication and a Fellow of Churchill College, for bringing key insights from the disciplines of statistics and probability vividly home to the public at large, and to key decision-makers, in entertaining and accessible ways, most recently through the COVID-19 pandemic.

The full list of Cambridges 2020 winners and their award citations:

Copley MedalAlan Fersht FMedSci FRS, Department of Chemistry, and Gonvilleand Caius CollegeHe has developed and applied the methods of protein engineering to provide descriptions of protein folding pathways at atomic resolution, revolutionising our understanding of these processes.

Croonian Medal and LectureProfessor Barry Everitt FMedSci FRS, Department of Psychology and Downing CollegeHe has elucidated brain mechanisms of motivation and applied them to important societal issues such as drug addiction.

Royal Medal AProfessor Herbert Huppert FRS, Department of Applied Mathematics and Theoretical Physics,and Kings CollegeHe has been at the forefront of research in fluid mechanics. As an applied mathematician he has consistently developed highly original analysis of key natural and industrial processes.

Hughes MedalProfessor Clare Grey FRS, Department of Chemistry and Pembroke CollegeFor her pioneering work on the development and application of new characterization methodology to develop fundamental insight into how batteries, supercapacitors and fuel cells operate.

Ferrier Medal and LectureProfessor Daniel Wolpert FMedSci FRS, Department of Engineering and Trinity CollegeFor ground-breaking contributions to our understanding of how the brain controls movement. Using theoretical and experimental approaches he has elucidated the computational principles underlying skilled motor behaviour.

Michael Faraday Prize and LectureSir David Spiegelhalter OBE FRS, Winton Centre for Risk and Evidence Communication and Churchill CollegeFor bringing key insights from the disciplines of statistics and probability vividly home to the public at large, and to key decision-makers, in entertaining and accessible ways, most recently through the COVID-19 pandemic.

Milner Award and LectureProfessor Zoubin Ghahramani FRS, Department of Engineering and St Johns CollegeFor his fundamental contributions to probabilistic machine learning.

Rosalind Franklin Award and LectureProfessor Julia Gog, Department of Applied Mathematics and Theoretical Physics, and Queens CollegeFor her achievements in the field of mathematics and her impactful project proposal with its potential for a long-term legacy.

Royal Society Mullard AwardProfessor Stephen Jackson FMedSci FRS, Gurdon Institute, Department of BiochemistryFor pioneering research on DNA repair mechanisms and synthetic lethality that led to the discovery of olaparib, which has reached blockbuster status for the treatment of ovarian and breast cancers.

The full list of medals and awards, including their description and past winners can be found on the Royal Society website:https://royalsociety.org/grants-schemes-awards/awards/

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Nine Cambridge researchers among this years Royal Society medal and award winners - India Education Diary

AI Researchers Design Program To Generate Sound Effects For Movies and Other Media – Unite.AI

A team of researchers from the Pritzker School of Molecular Engineering (PME) at the University of Chicago has recently succeeded in the creation of an AI system that can create entirely new, artificial proteins by analyzing stores of big data.

Proteins are macromolecules essential for the construction of tissues in living things, and critical to the life of cells in general. Proteins are used by cells as chemical catalysts to make various chemical reactions occur and to carry out complex tasks. If scientists can figure out how to reliably engineer artificial proteins, it could open the door to new ways of carbon capturing, new methods of harvesting energy, and new disease treatments. Artificial proteins have the power to dramatically alter the world we live in. As reported by EurekaAlert, a recent breakthrough by researchers at PME University of Chicago has put scientists closer to those goals. The PME researchers made use of machine learning algorithms to develop a system capable of generating novel forms of protein.

The research team created machine learning models trained on data pulled from various genomic databases. As the models learned, they began to distinguish common underlying patterns, simple rules of design, that enable the creation of artificial proteins. Upon taking the patterns and synthesizing the respective proteins in the lab, the researchers found that the artificial proteins created chemical reactions that were approximately as effective as those driven by naturally occurring proteins.

According to Joseph Regenstein Professor at PME UC, Rama Ranganathan, the research team found that genome data contains a massive amount of information regarding the basic functions and structures of proteins. By utilizing machine learning to recognize these common structures, the researchers were able to bottle natures rules to create proteins ourselves.

The researchers focused on metabolic enzymes for this study, specifically a family of proteins called chorismate mutase. This protein family is necessary for life in a wide variety of plants, fungi, and bacteria.

Ranganathan and collaborators realized that genome databases contained insights just waiting to be discovered by scientists, but that traditional methods of determining the rules regarding protein structure and function have only had limited success. The team set out to design machine learning models capable of revealing these design rules. The models findings imply that new artificial sequences can be created by conserving amino acid positions and correlations in the evolution of amino acid pairs.

The team of researchers created synthetic genes that encoded amino acid sequences producing these proteins. They cloned bacteria with these synthetic genes and found that the bacteria used the synthetic proteins in their cellular machinery, functioning almost exactly the same as regular proteins.

According to Ranganathan, the simple rules that their AI distinguished can be used to create artificial proteins of incredible complexity and variety. As Ranganathan explained to EurekaAlert:

The constraints are much smaller than we ever imagined they would be. There is a simplicity in natures design rules, and we believe similar approaches could help us search for models for design in other complex systems in biology, like ecosystems or the brain.

Ranganathan and collaborators want to take their models and generalize them, creating a platform scientists can use to better understand how proteins are constructed and what effects they have. They hope to use their AI systems to enable other scientists to discover proteins that can tackle important issues like climate change. Ranganathan and Associate Professor Andrew Ferguson have created a company dubbed Evozyne, which aims to commercialize the technology and promote its use in fields like agriculture, energy, and environment.

Understanding the commonalities between proteins, and the relationships between structure and function could also assist in the creation of new drugs and forms of therapy. Though protein folding has long been considered an incredibly difficult problem for computers to crack, the insights from models like the once produced by Ranganathans team could help increase the speed these calculations are produced at, facilitating the creation of new drugs based on these proteins. Drugs could be developed that block the creation of proteins within viruses, potentially aiding in the treatment of even novel viruses like the Covid-19 coronavirus.

Ranganathan and the rest of the research team still need to understand how and why their models work and how they produce reliable protein blueprints. The research teams next goal is to better understand what attributes the models are taking into account to arrive at their conclusions.

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AI Researchers Design Program To Generate Sound Effects For Movies and Other Media - Unite.AI

"Floppy" Proteins Used To Create Artificial Organelles Within Human Cells – Technology Networks

Biomedical engineers at Duke University have demonstrated a method for controlling the phase separation of an emerging class of proteins to create artificial membrane-less organelles within human cells. The advance, similar to controlling how vinegar forms droplets within oil, creates opportunities for engineering synthetic structures to modulate existing cell functions or create entirely new behaviors within cells.The results appear online in the journal Nature Chemistry.

Proteins function by folding into specific 3-D shapes that interact with different biomolecular structures. Researchers previously believed that proteins needed these fixed shapes to function. But in the last two decades, a large new class of intrinsically disordered proteins (IDPs) have been discovered that have large regions that are floppy that is, they do not fold into a defined 3-D shape. It is now understood these regions play an important, previously unrecognized role in controlling various cellular functions.

IDPs are also useful for biomedical applications because they can undergo phase transitions changing from a liquid to a gel, for example, or from a soluble to an insoluble state, and back again in response to environmental triggers, like changes in temperature. These features also dictate their phase behavior in cellular environments and are controlled by adjusting characteristics of the IDPs such as their molecular weight or the sequence in which the amino acids are linked together.

Although there are many natural IDPs that show phase behavior in cells, they come in many different flavors, and it has been difficult to discern the rules that govern this behavior, said Ashutosh Chilkoti, the Alan L. Kaganov Distinguished Professor of Biomedical Engineering at Duke. This paper provides very simple engineering principles to program this behavior within a cell.

Others in the field have taken a top-down approach where theyll make a change to a natural IDP and see how its behavior changes within a cell, said Michael Dzuricky, a research scientist working in the Chilkoti laboratory and first author of the study. Were taking the opposite approach and building our own artificial IDPs from simple thermodynamic principles. This enables us and others to precisely tune a single propertythe shape of the IDPs phase diagramto better understand how this parameter affects biological behavior.

In the new paper, the researchers begin by looking to nature for examples of IDPs that come together to form biomolecular condensates within cells. These weakly-held-together structures allow cells to create compartments without also building a membrane to encapsulate it. Using one such IDP from the common fruit fly as a basis, the researchers draw from their extensive history of working with IDPs to engineer a molecularly simpler artificial version that retains the same behavior.

This simpler version allowed the researchers to make precise changes to the molecular weight of the IDP and amino acids of the IDPs. The researchers show that, depending on how these two variables are tweaked, the IDPs come together to form these compartments at different temperatures in a test tube. And by consistently trying various tweaks and temperatures, the researchers gained a solid understanding of which design parameters are most important to control the IDPs behavior.

A test tube, however, is not the same as a living cell, so the researchers then went one step further to demonstrate how their engineered IDPs behave within E. coli. As predicted, their artificial IDPs grouped together to form a tiny droplet within the cells cytoplasm. And because the IDPs behavior was now so well understood, the researchers showed they could predictably control how they coalesced using their test tube principles as a guide.

We were able to change temperatures in cells to develop a complete description of their phase behavior, which mirrored our test tube predictions, said Dzuricky. At this point, we were able to design different artificial IDP systems where the droplets that are formed have different material properties.

Put another way, because the researchers understood how to manipulate the size and composition of the IDPs to respond to temperature, they could program the IDPs to form droplets or compartments of varying densities within cells. To show how this ability might be useful to biomedical engineers, the researchers then used their newfound knowledge, as nature often does, to create an organelle that performs a specific function within a cell.

The researchers showed that they could use the IDPs to encapsulate an enzyme to control its activity level. By varying the molecular weight of the IDPs, the IDPs hold on the enzyme either increased or decreased, which in turn affected how much it could interact with the rest of the cell.

To demonstrate this ability, the researchers chose an enzyme used by E. coli to convert lactose into usable sugars. However, in this case, the researchers tracked this enzymes activity with a fluorescent reporter in real-time to determine how the engineered IDP organelle was affecting enzyme activity.

In the future, the researchers believe they could use their new IDP organelles to control the activity levels of biomolecules important to disease states. Or to learn how natural IDPs fill similar cellular roles and understand how and why they sometimes malfunction.

This is the first time anybody has been able to precisely define how the protein sequence controls phase separation behavior inside cells, said Dzuricky. We used an artificial system, but we think that the same rules apply to natural IDPs and are excited to begin testing this theory.

We can also now start to program this type of phase behavior with any protein in a cell by fusing them to these artificial IDPs, said Chilkoti. We hope that these artificial IDPs will provide new tool for synthetic biology to control cell behavior.

This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source.

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"Floppy" Proteins Used To Create Artificial Organelles Within Human Cells - Technology Networks

Nine Cambridge researchers among this year’s Royal Society medal and award winners – Cambridge Network

President of the Royal Society, Venki Ramakrishnan, said: "The Royal Societys medals and awards celebrate those researchers whose ground-breaking work has helped answer fundamental questions and advance our understanding of the world around us. They also champion those who have reinforced sciences place in society, whether through inspiring public engagement, improving our education system, or by making STEM careers more inclusive and rewarding.

"This year has highlighted how integral science is in our daily lives, and tackling the challenges we face, and it gives me great pleasure to congratulate all our winners and thank them for their work."

Sir Alan Fersht FMedSci FRS, Emeritus Professor in the Department of Chemistry and former Master of Gonville and Caius College, is awarded the Copley Medal for the development and application of methods to describe protein folding pathways at atomic resolution, revolutionising our understanding of these processes.

"Most of us who become scientists do so because science is one of the most rewarding and satisfying of careers and we actually get paid for doing what we enjoy and for our benefitting humankind. Recognition of ones work, especially at home, is icing on the cake," said Sir Alan. "Like many Copley medallists, I hail from a humble immigrant background and the first of my family to go to university. If people like me are seen to be honoured for science, then I hope it will encourage young people in similar situations to take up science."

As the latest recipient of the Royal Societys premier award, Sir Alan joins an elite group of scientists, that includes Charles Darwin, Albert Einstein and Dorothy Hodgkin, and more recently Professor John Goodenough (2020) for his research on the rechargeable lithium battery, Peter Higgs (2015), the physicist who hypothesised the existence of the Higgs Boson, and DNA fingerprinting pioneer Alec Jeffreys (2014).

Read the full story, with the complete list of Cambridges 2020 winners and their award citations

Reproduced courtesy of the University of Cambridge

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Nine Cambridge researchers among this year's Royal Society medal and award winners - Cambridge Network

What’s New in Computing vs. COVID-19: Bars, Visualizations, New Therapeutics & More – HPCwire

Supercomputing, big data and artificial intelligence are crucial tools in the fight against the coronavirus pandemic. Around the world, researchers, corporations and governments are urgently devoting their computing resources to this global crisis. This column collects the biggest news about how advanced technologies are helping us fight back against COVID-19.

Nvidia uses [emailprotected] data to visualize moving spike proteins

[emailprotected]s crowdsourced network of volunteer computers, which has boomed during the pandemic, have enabled the production of massive datasets describing the folding of SARS-CoV-2s viral proteins particularly the spike protein. A scientific visualization team at Nvidia used that dataset to produce a haunting, ultra-high-resolution fly-through visualization of those proteins. To read more, click here.

Calculations on Comet boost understanding of immune responses to foreign pathogens

Researchers at the San Diego Supercomputer Center used Comet to assist a study on T cell receptors that the team says will inform understanding on the adaptive immune systems response to pathogens like SARS-CoV-2. Our most recent study puts us one step closer to truly understanding the extreme and beneficial diversity in the immune system, and identifying features of immunity that are shared by most people, said James E. Crowe, Jr., director of the Vanderbilt Vaccine Center of Vanderbilt University Medical Center. To read more, click here.

Supercomputer research leads to clinical study of potential COVID-19 therapeutic

Research conducted under the auspices of European public-private consortium Exscalate4CoV has led to the approval of a human clinical trial studying the use of the existing osteoporosis drug raloxifene for the treatment of mild cases of COVID-19. Raloxifene was one of several drugs to emerge from a massive supercomputer-powered screening of hundreds of thousands of candidate molecules. The researchers are hopeful that the drug may halt the progression of infection in certain cases. To read more, click here.

Researchers use supercomputing to study the minute movements of the coronavirus proteins

SARS-CoV-2s notorious spike protein, which allows it to infect human cells, relies on movement to pry open and enter host cells. While the basic stages of its movement were imaged early in the year, the intermediary states between those stages had not been fully captured until now. Researchers from UC Berkeley and Istanbul Technical University used TACC supercomputers to simulate these minute movements, identifying potential middle states that could serve as useful drug targets. To read more, click here.

RIKEN teams with businesses to study and reduce the risk of COVID-19 infection in restaurants and bars

Japanese research institute RIKEN, host of the Top500-leading supercomputer Fugaku, has teamed up with Suntory Liquors Ltd. and Toppan Printing Co., Ltd. to develop face shields specifically for eating and drinking in order to reduce the risk of COVID-19 infection in restaurants and bars. The study is making use of Fugaku, which has been involved in a variety of viral droplet simulations. To read more, click here.

Corona supercomputer receives major upgrade for coronavirus research

The (coincidentally named) Corona supercomputer at Lawrence Livermore National Laboratory (LLNL) has received a major upgrade to assist with its research on the coronavirus. The system now boasts almost 1,000 new AMD Radeon Instinct MI50 GPUs, more than doubling its speed (for a total of 11 peak petaflops). The expansion of Corona allows us to routinely run the computationally intensive molecular dynamics simulations to obtain the free energy between antibodies-antigens, said LLNL COVID-19 researcher Felice Lightstone. To read more, click here.

Brookhaven National Laboratory issues update on its work to fight the coronavirus

Since early this year, Brookhaven National Laboratory has been supporting a range of projects aimed at combating COVID-19. The lab recently issued an update on its research, highlighting a variety of supercomputer-supported research, including a scalable high-performance computing and AI infrastructure that allows for high-throughput ensemble docking studies and AI-driven molecular dynamics simulations. To read more, click here.

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What's New in Computing vs. COVID-19: Bars, Visualizations, New Therapeutics & More - HPCwire

Arizona universities join forces to contribute to COVID-19 modeling and simulation efforts – ASU Now

July 14, 2020

While the COVID-19 pandemic continues to impact the world, the research computing centers at Arizona State University, Northern Arizona Universityand University of Arizonahave united as a team to contribute to the Folding@homeproject. The project utilizes idle computing power to significantly contribute to vital scientific research and therapeutic drug discovery.

The Arizona Research Computing consortium is contributing to this collective effort by using advanced computing resources to perform complex protein modeling computations during brief idle periods on local supercomputers. By running these computations only during downtime, contributions to COVID-19 modeling and simulation efforts can be made through the Folding@home project without impacting everyday research. Artist rendition of the SARS-Cov-2 virus. The envelope protein is shown in cyan. (Figure from Klick health https://covid19.klick.com/) Download Full Image

The Folding@home project provides people around the world the opportunity to make active contributions to a variety of scientific research efforts including COVID-19. Volunteers, or citizen scientists, can download the Folding@home software to their personal computers, allowing simulations of complex scientific processes to run in the background while their personal computers are not in use. The Folding@home project is crowdsourcing at its best, using shared computing power at a massive scale to help solve grand challenges in biomedical research.

In addition to mobilizing citizen scientists across the globe, many institutions and corporations are contributing their own computational resources such as high performance workstations and servers. This distributed computational power is estimated to be 10 times faster than the worlds fastest individual supercomputer.

The onslaught of COVID-19 has raised the visibility of the Folding@home project, highlighting a unique opportunity to fight the virus. The project seeks to understand how proteins, which are large, complex molecules that play an important role in how our bodies function, fold to perform their biological functions. This helps researchers understand diseases that result from protein misfolding and identify novel ways to develop new drug therapies.

How proteins fold or misfold can help us understand what causes diseases like cancer, Alzheimer's disease and diabetes. It might also lend insight into viruses such as SARS-CoV-2,the cause of the recent COVID-19pandemic.

Imagine if I told 100 people to fold a pipe cleaner. They are going to fold it in 100 different ways because theres an infinite number of combinations of how to take something that is straight and fold it," said Blake Joyce, assistant director of research computing at the University of Arizona."Thats what viruses and living things do with proteins. They make copies of themselves and fold them up in their own particular way.

Using computational modeling, researchers can explore the mechanics of proteins of the virus and predict every possible way it might fold, or physically change shape.

In biology, shape is function. If you can disrupt that shape, the virus is inactive or cant do its thing. If you disrupt any of the mechanisms that can damage us, you have a cure, or at least something you can treat. And that is what were after. It just takes a lot of computing to come up with every possible way to bend a pipe cleaner, Joyce said.

By running computer simulations, researchers can take the virus and see how it interacts with various compounds or drugs and narrow down which ones might work to interrupt one of the critical mechanisms the virus needs to survive.

Folding@home assigns pieces of a protein simulation to each computer and the results are returned to create an overall simulation. Folding@home computations for COVID-19 research seem to be most productive on the kind of computers found in facilities like Arizonas research computing centers, making their contributions even more valuable.

Volunteers can track their contributions on the Folding@home website and combine their efforts as a team, receiving points for completing work assigned to them and even earning bonus points for work that is more computationally demanding or that might have a greater scientific priority.

The Arizona Research Computing team has risen quickly in the ranks, highlighting the powerful computing capabilities at Arizonas state universities and the effectiveness of regional collaborations. As of mid-June, the Arizona Research Computing team was ranked in the top 100 out of nearly a quarter of a million teams, surpassing Hewlett Packard, Cisco Systems, Apple Computer, Inc., Google, Ireland and Poland, as well as many other university, industry and national or international contributors.

The Folding@home project investigates many research questions that require an enormous amount of computing, but this specific use for COVID-19 provides a unique opportunity, spurring many computing centers to participate in Folding@home for the first time, said Gil Speyer, lead scientific software engineer for Arizona State Universitys research computing center.

Todays biomedical research requires vast amounts of time and computing power. While the Arizona Research Computing team may directly impact COVID-19 research in a small way, the overall impact of the Folding@home project is much broader and will continue to have applications beyond the COVID-19 pandemic.

ASU:

Sean Dudley, assistant vice president and chief research information officer, Research Technology Office

Douglas Jennewein, senior director, research computing, Research Technology Office

Gil Speyer, lead scientific software engineer, Research Technology Office

Marisa Brazil, associate director, research computing, Research Technology Office

Jason Yalim, postdoc,research computing, Research Technology Office

Lee Reynolds, systems analyst principal, research computing, Research Technology Office

Eric Tannenhill, senior software engineer,research computing, Research Technology Office

NAU:

Chris Coffey

UArizona:

Blake Joyce, assistant director, research computing

Todd Merritt, information technology manager, principal

Ric Anderson, systems administrator, principal

Chris Reidy, systems administrator, principal

Adam Michel, systems administrator, principal

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Arizona universities join forces to contribute to COVID-19 modeling and simulation efforts - ASU Now

HPC revolutionising speed of life science research – Business Weekly

Until recently High Performance Computing (HPC) was largely the preserve of the automotive, aerospace and financial services industries but, increasingly, the need for HPC within the life sciences sector has predominated.

Never has this been more evident than in the last six months of the pandemic, which has seen global HPC resources pooled in an unprecedented effort to halt the progress of COVID-19.

HPC refers to the practice of aggregating super-computing power in a way that delivers much higher performance than the typical desktop computer or workstation.

It enables researchers to analyse vast datasets, run extraordinarily large numbers of calculations in epidemiology, bioinformatics and molecular modelling and solve highly complex scientific problems.

Most significantly, it enables scientists and researchers to do in hours and days what would have, otherwise, taken months and years via slower, traditional computing platforms.

According to HPC expert Adrian Wander over the next few years, we will start seeing an ever-increasing democratisation of HPC which will be central to super-computing becoming a routine part of life sciences and pharmaceutical research.

A former research student with a PhD in theoretical solid-state physics, Adrian was a chemistry lecturer at Cambridge University, working under Professor Sir David King (later chief scientific advisor to Tony Blairs government) before devoting the next 30 years to working in HPC.

During this time, Adrian was an integral part of the team setting up the Hartree Centre home to some of the most advanced computing, data and AI technologies in the UK ran the scientific computing department at the Science & Technology Facilities Council before moving to the European Centre for Medium-Range Weather Forecasts (ECMWF), delivering highly critical, time-sensitive computations that relied heavily on HPC modelling for speed and accuracy.

He says: Historically, HPC was seen as a complex, specialist activity requiring special machines and expert techniques. But, especially in recent months, we have seen a dramatic change in who wants and needs access to HPC.

Traditionally, the biggest users were the automotive and aerospace sectors. But in the current COVID-19 climate, aeroplanes arent being purchased and consumers arent buying cars, whereas we are seeing a dramatic rise in the use of HPC within the life sciences industry not least because the need has never been greater.

HPC expert Adrian Wander

The life sciences sector was initially slow to catch onto HPC compared with the physical science community. In 2007, the Biotechnology & Biological Sciences Research Council (BBSRC) paid for 10 per cent of Britains academic national supercomputer service, HECToR (High End Computing Terascale Resource) but it ended up dropping the partnership because it wasnt being used by its community.

More recently there has been a huge upsurge in life sciences to explore workloads more actively and efficiently e.g. via simulation and modelling of protein folding and the structures of proteins, and similar areas. And, of course, Artificial Intelligence is being relied on heavily in the search for new drugs by automatically sampling huge numbers of drug candidates on the target treatment.

Adrian adds: Over the next few years, HPC will become both simpler to use and more easily available and it will inevitably become a more mainstream part of research portfolios just as incubators and wet benches are now.

Even with genome sequencing, the Oxford nanopore system takes you down into quite small organisations doing this kind of work because the new sequencing machines make sequencing quite easy to do.

The tricky part is putting all the bits together to assemble the full genome and this requires increasing amounts of compute power, irrespective of the size of the organisation doing the assembly.

The technological advance in this field has been incredible: Sequencing the first human genome was an international effort that cost around $1 billion and took 13 years to complete. Today, genomic studies and meta-genomics are routinely run for between $3000-$5000 and take little more than a couple of days to complete.

To quantify the remarkable difference HPC is making to scientific discovery, one only has to note the following: After HIV-1 (the main cause of AIDS in humans) was first identified in 1981, it took almost three more decades to genetically decode it.

Four years later, in 2013, the SARS outbreak (due to another coronavirus) was decoded within three months. This year the genome behind COVID-19 was decoded and published globally within days. Things are indeed changing in the life sciences sector. And rapidly so.

At the end of May, this country led by UK Research and Innovation became the first European super-computing partner to join the COVID-19 High Performance Computing Consortium, contributing more than 20 Petaflops of HPC capability to the global effort addressing the coronavirus crisis.

The consortium currently has 56 active projects and more than 430 Petaflops of compute which, collectively, is equal to the computing power of almost 500,000 laptops.

For perspective, a supercomputer with just eight petaflops can do a million calculations per person in the world per second. But, by pooling supercomputing capacity the consortium offers 50 times that and hopes to reduce the time it takes to discover new molecules which could lead to coronavirus treatments and a vaccine.

Last week, it was revealed that Summit, the worlds second-fastest supercomputer, had been employed to produce a genetic study of COVID-19 patients, analysing 2.5 billion genetic combinations in just two weeks.

The insights which Summit has produced through HPC and AI are significant in understanding how coronavirus causes the COVID-19 disease and additionally indicate potential new therapies to treat the worst symptoms.

Of course, return on investment is also important in driving the move towards HPC. Hyperion Research recently reported that every dollar spent on HPC in life sciences earns $160 of which $41 is profit or cost-saving.

Adrian explains: On the face of it, when you look at the cost of hosted services, it might seem expensive. But you need to weigh that against the fact that you no longer need an in-house team of high voltage engineers and all that comes with them.

And for the big drug companies and pharmas using increasing amounts of HPC cycles for drug discovery, personalised healthcare has the potential to become a huge profit-making market.

With astronomical levels of computational life sciences data being produced daily, the need for secure storage to house this and advanced computing infrastructure to rapidly analyse the vast datasets is becoming paramount. Thats the reason why more and more research institutions are outsourcing or co-locating to specialist data centres such as the bleeding edge Kao Data campus in Harlow.

Adam Nethersole

Kao Datas director, Adam Nethersole explains: Staying static isnt an option within a highly competitive sector where being first to market is everything especially when were talking about life-saving treatments, medicines and vaccines.

So across the life sciences sector, most universities, laboratories or research institutes are looking to expand their access to high performance computing.

But, of course, many of these organisations are pretty landlocked and with old architecture and there isnt available space that can be turned into a hyper-efficient data centre unless youre in new, state of the art facilities.

And even if you are able to scale internally and have the technical expertise in-house to do this you still need to consider how youre going to power and cool the additional servers especially in locations like Cambridge where there simply isnt a vast surplus of available electricity ready and available to be utilised.

One solution is using hyperscale cloud services but, while these are great for streaming videos, music and playing video games, they arent optimal for specialist computing which requires servers located closely together (and not virtualised in the cloud) and in many cases, bespoke, tailored IT architecture. Cloud platforms also tend to be expensive when moving large amounts of data.

This is why were seeing an increasing number of enquiries about moving computing infrastructure off-premise and into an advanced industrial scale data centre like the one we operate at Kao Data.

With multi-megawatts of power and space available immediately and excellent connectivity back-up to Cambridge citys research parks, were ideally placed to support.

One of Cambridges most forward-thinking research institutions, EMBL-EBI, has already done this and we are in conversation with others about helping them plan their computing footprint for the next 10, 15 and 20 years.

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HPC revolutionising speed of life science research - Business Weekly

Hopkins chemist awarded New Innovator Award from National Institutes of Health – The Hub at Johns Hopkins

ByRachel Wallach

Proteins must fold themselves up into specific three-dimensional shapes to perform tasks required by the cell for function and survival. But when proteins fold into the wrong shape, they aggregate or clump togetherthink of the way eggs transform from liquid to solid during the cooking process.

Misfolded proteins can disrupt the normal functioning of the cell, and are associated with a wide range of diseases. When the proteins inside neurons aggregate, the toxic structures they create cause neurodegenerative diseases like Alzheimer's and Parkinson's. "Over billions of years of evolution, cells were challenged with the task to get their proteins to fold up correctly and stay that way," says Stephen Fried, assistant professor in the Department of Chemistry in the Krieger School of Arts and Sciences. "But we humans live for a pretty long time, and as the proteins in our brains get older, there seems to be a slow process where they forget what shape they're supposed to be in. They form structures that stick to each other, ultimately leading to the death of neurons, dementia, and other maladies associated with age."

Fried has received an NIH Director's New Innovator Award from the National Institutes of Health's High-Risk, High-Reward Research program to continue his studies into both the normal process of protein folding and what happens on a molecular level when the process goes awry. The award, in the amount of $1.5 million over five years, supports unusually innovative research from early career investigators.

Francis S. Collins

Director, National Institutes of Health

"The breadth of innovative science put forth by the 2020 cohort of early career and seasoned investigators is impressive and inspiring," said NIH Director Francis S. Collins. "I am confident that their work will propel biomedical and behavioral research and lead to improvements in human health."

Scientists have been trying to understand the folding process for some time by studying purified proteins in test tubes. What sets Fried's research apart is that he and his team are studying the normal and abnormal folding of proteins in their native contextin this case, within rodent brains.

"We think that the tools we're developing on the front part of our project will give us a new view into why cells are so good at getting their proteins to assemble into such complicated and intricate architectures," Fried says. "We will then apply the tools to take a look at what's going on inside rats' brains at the molecular level when they age. Specifically, we want to know what's different in cognitively healthy versus cognitively impaired rats."

Fried has been collaborating with Michela Gallagher, Krieger-Eisenhower Professor of Psychology and Neuroscience, whose long-term research on Alzheimer's-related changes within the brain has produced experimental drugs now in clinical trials. While Gallagher's team focuses on the brain's structures, Fried's team complements the research by working at the molecular level. "Our collaboration will zoom in on the proteins forming incorrect shapes inside the brain; what they are interacting with, and what shapes they are forming," Fried says.

It is the opportunity for such interdisciplinary work that made the NIH award possible, Fried says, pointing to the preliminary data he and Gallagher were able to produce that he believes convinced the reviewers to take a chance on this uncharted territory.

Jotham Suez, a postdoctoral fellow at the Weizmann Institute of Science and is expected to join the Johns Hopkins Bloomberg School of Public Health as an assistant professor in the Department of Molecular Microbiology and Immunology in January, was also awarded an Early Independence Award from the High-Risk, High-Reward Research program. A microbiologist, Suez focuses on how non-nutritive sweeteners affect microbiomes. His early research indicated that non-caloric sweeteners can negatively affect health through the disruption of gut bacteria, and his research at JHU will focus on deciphering the underlying mechanisms.

The High-Risk, High-Reward Research program catalyzes scientific discovery by supporting research proposals that, due to their inherent risk, may struggle in the traditional peer-review process despite their transformative potential. Program applicants are encouraged to think "outside the box" and to pursue trailblazing ideas in any area of research relevant to the NIH's mission to advance knowledge and enhance health.

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Hopkins chemist awarded New Innovator Award from National Institutes of Health - The Hub at Johns Hopkins

A New Map Catalogs the Effects of Coronavirus Mutations – Howard Hughes Medical Institute

Scientists have analyzed every possible mutation to one key part of the coronavirus. The data could help guide vaccine and drug development and hint at how the virus might spread.

HHMI scientists are joining many of their colleagues worldwide in working to combat the new coronavirus. Theyre developing diagnostic testing, understanding the viruss basic biology, modeling the epidemiology, and developing potential therapies or vaccines. Over the next several weeks, we will be sharing stories of some of this work.

As the novel coronavirus spreads, its picking up new mutations for better and for worse.

Now, Howard Hughes Medical Institute Investigator Jesse Bloom and his colleagues have cataloged how nearly 4,000 different mutations alter SARS-CoV-2s ability to bind to human cells.

Their data, publicly available online as an interactive map, is a new resource for researchers developing antiviral drugs and vaccines to fight COVID-19, the infectious disease caused by SARS-CoV-2. The work also reveals how individual mutations may affect the viruss behavior, the team reports August 11, 2020in the journal Cell.

We dont know how the virus will evolve, but now we have a way to look at the mutations that can occur and see their effects, says Bloom, a virologist at the Fred Hutchinson Cancer Research Center.

Each time a virus replicates, it can pick up new genetic mutations. Many of these mutations have no effect on a viruss behavior. Others could make the virus better or worse at infecting people. To what extent mutations might be making SARS-CoV-2 more dangerous has been an open and controversial question. Doctors and scientists have analyzed genetic differences in virus samples collected from COVID-19 patients around the world, hunting for clues to the diseases spread. But until now, no one had comprehensively linked potential mutations to their functional effect on SARS-CoV-2.

We dont know how the virus will evolve, but now we have a way to look at the mutations that can occur and see their effects.

Jesse Bloom, HHMI Investigator at the Fred Hutchinson Cancer Research Center

The new study focused on mutations to a key part of SARS-CoV-2 its spike protein. This protein binds to a protein on human cells called ACE2, a necessary step for infection. Mutations in the spike protein could change how well SARS-CoV-2 sticks to and thus infects human cells.

Blooms team bred yeast cells to display a fragment of the spike protein on their surface. This fragment, called the receptor binding domain, makes direct contact with ACE2. The researchers systematically created thousands of versions of the fragment each with different mutations. Then they measured how well these mutated fragments stuck to ACE2. That let them assess how various mutations might affect the function of the binding domain.

The data show that many possible mutations could make the virus bind to human cells more strongly. But those mutations dont seem to be gaining a foothold in circulating versions of the virus.

This would suggest that theres some sort of sweet spot, where if the virus can bind ACE2 pretty well, then its able to infect humans, Bloom says. Maybe theres no evolutionary need for it to get better.

Other mutations made it harder for the spike protein to bind to cells or prevented the protein from properly folding into its final shape, the team found. Versions of the virus with these mutations might be less likely to gain a foothold because they cant infect cells as effectively. The teams targeted lab tests arent a perfect proxy for how mutations will affect the virus in the wild, where many other factors influence how effectively it can spread but theyre a useful starting place.

The data will also be valuable for researchers designing drugs and vaccines to fight COVID-19, says Tyler Starr, a postdoc in Blooms lab who led the project alongside graduate student Allie Greaney. Understanding the consequences of different mutations can guide the development of drugs that will continue to work as the virus changes over time. Plus, Starr says, its becoming clear that antibodies that stick to this part of the virus are really good, protective antibodies that we would want to elicit with a vaccine.

Study coauthor Neil King and his lab at the University of Washington is already working on such vaccines. His team is designing artificial proteins that mimic components of the virus. As part of a vaccine, such proteins could potentially train peoples immune systems to produce antibodies that target the coronavirus. The researchers modify the artificial proteins to make them more stable and easier to produce in large quantities than the natural versions of the proteins.

The data from Blooms team offers a roadmap to making those modifications. Normally, when were trying to figure out how to make a protein better, were shooting in the dark, says Daniel Ellis, a graduate student in Kings lab. The information theyve given us is kind of like a cheat sheet. It makes our lives amazingly easier.

###

Citation

Tyler N. Starr et al. Deep mutationalscanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding. Cell. Published online on August 11, 2020. doi:10.1016/j.cell.2020.08.012

Original post:
A New Map Catalogs the Effects of Coronavirus Mutations - Howard Hughes Medical Institute

All processors on deck in the race to research COVID-19 – Silicon Prairie News

Sometimes a problem is so urgent and complex, you need the whole world working on it.

Thats COVID-19.

Sometimes you also need the help of a global supercomputer.

Thats Folding@home.

A distributed computing project powering research into SARS-CoV-2, Folding@home seeks to develop effective, patent-free drugs to treat the deadly coronavirus, which has caused over 732,000 deaths worldwide, including more than 163,000 deaths nationally.

But a successful response to this large-scale, generation-defining problem cant be realized without the combined computing resources of millions of ordinary citizens around the world. Thats why Folding@home is inviting everyday computer users to share their excess computing power with researchers. Volunteers can download the necessary software here.

Weve had several million volunteers, citizen scientists that have downloaded the software and helped us out in this, said Anton Thynell, head of collaboration and communication for Folding@home in a recent interview with Dubuque, Iowa radio station KDTH-AM. Were actually the strongest supercomputer in the world.

A self-described moonshot collaboration, Folding@home studies both the virus and the human proteins it interacts with. So far, the project has discovered novel protein structures previously inaccessible to researchers.

With that victory in tow, the team has shifted toward the discovery of new therapies to treat the illnessone that scientists and the medical community are still struggling to figure out.

What Folding@home does is basically trying to map out the entire virus and how it folds and unfolds, Thynell said. But this requires an immense amount of computing.

To that end, Omaha-based cloud provider First National Technology Solutions (FNTS) has joined several other organizations worldwide in the effort, providing access to a phenomenal amount of excess processing power that is then tied together with other processors around the world to create the supercomputer, said FNTS president Kim Whittaker in that same interview. (Whittaker sits on the board of the nonprofit AIM Institute, which operates Silicon Prairie News.)

We wanted to look for ways that we could give back and help other organizations with different supercomputing initiatives that they have underway, Whittaker said.With the technology in place to make these complicated simulations possible through our partnership with Folding@home, this allows scientists to concentrate on research, analysis and finding cures.

FNTS is active in the community, actively supporting organizations such as the AIM Institute.The company is celebrating its 25-year anniversaryin August as a nationally recognized advisor in managed IT services.

Folding@home began at Stanford University in 2000 as a distributed computing project for disease research that simulates protein folding, computational drug design and molecular dynamics. When the pandemic hit, the project shifted to address the mechanics of the novel coronavirus, with unprecedented support from people around the world, Thynell said.

It is really fascinating what theyve been able to accomplish with individuals and companies that have donated time and resources, all for a good cause, to help solve some of these healthcare challenges, Whittaker said.

Thynell gave a direct plea for users to please consider downloading the software from the Folding@home website and running it on both their personal and work computers, if possible.

Youre helping us with a small part of a very large simulation, where were trying to understand better how SARS-CoV-2 works and moves, Thynell said.

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All processors on deck in the race to research COVID-19 - Silicon Prairie News

Nine Cambridge researchers among this year’s Royal Society medal and award winners – Mirage News

He is one of the 25 Royal Society medals and awards winners announced today, nine of whom are researchers at the University of Cambridge. The annual prizes celebrate exceptional researchers and outstanding contributions to science across a wide array of fields.

President of the Royal Society, Venki Ramakrishnan, said:

The Royal Societys medals and awards celebrate those researchers whose ground-breaking work has helped answer fundamental questions and advance our understanding of the world around us. They also champion those who have reinforced sciences place in society, whether through inspiring public engagement, improving our education system, or by making STEM careers more inclusive and rewarding.

This year has highlighted how integral science is in our daily lives, and tackling the challenges we face, and it gives me great pleasure to congratulate all our winners and thank them for their work.

Sir Alan Fersht FMedSci FRS, Emeritus Professor in the Department of Chemistry and former Master of Gonville and Caius College, is awarded the Copley Medal for the development and application of methods to describe protein folding pathways at atomic resolution, revolutionising our understanding of these processes.

Most of us who become scientists do so because science is one of the most rewarding and satisfying of careers and we actually get paid for doing what we enjoy and for our benefitting humankind. Recognition of ones work, especially at home, is icing on the cake, said Sir Alan. Like many Copley medallists, I hail from a humble immigrant background and the first of my family to go to university. If people like me are seen to be honoured for science, then I hope it will encourage young people in similar situations to take up science.

As the latest recipient of the Royal Societys premier award, Sir Alan joins an elite group of scientists, that includes Charles Darwin, Albert Einstein and Dorothy Hodgkin, and more recently Professor John Goodenough (2020) for his research on the rechargeable lithium battery, Peter Higgs (2015), the physicist who hypothesised the existence of the Higgs Boson, and DNA fingerprinting pioneer Alec Jeffreys (2014).

Professor Barry Everitt FMedSci FRS, from the Department of Psychology and former Master of Downing College, receives the Croonian Medal and Lecture for research which has elucidated brain mechanisms of motivation and applied them to important societal issues such as drug addiction.

Professor Everitt said: In addition to my personal pride about having received this prestigious award, I hope that it helps draw attention to experimental addiction research, its importance and potential.

Professor Herbert Huppert FRS of the Department of Applied Mathematics and Theoretical Physics, and a Fellow of Kings College, receives a Royal Medal for outstanding achievements in the physical sciences. He has been at the forefront of research in fluid mechanics. As an applied mathematician he has consistently developed highly original analysis of key natural and industrial processes. Further to his research, he has chaired policy work on how science can help defend against terrorism, and carbon capture and storage in Europe.

In addition to the work for which they are recognised with an award, several of this years recipients have also been working on issues relating to the COVID-19 pandemic.

Professor Julia Gog of the Department of Applied Mathematics and Theoretical Physics and a Fellow of Queens College, receives the Rosalind Franklin Award and Lecture for her achievements in the field of mathematics. Her expertise in infectious diseases and virus modelling has seen her contribute to the pandemic response, including as a participant at SAGE meetings. The STEM project component of her award will produce resources for Key Stage 3 (ages 11-14) maths pupils and teachers exploring the curriculum in the context of modelling epidemics and infectious diseases and showing how maths can change the world for the better.

The Societys Michael Faraday Prize is awarded to Sir David Spiegelhalter OBE FRS, of the Winton Centre for Centre for Risk and Evidence Communication and a Fellow of Churchill College, for bringing key insights from the disciplines of statistics and probability vividly home to the public at large, and to key decision-makers, in entertaining and accessible ways, most recently through the COVID-19 pandemic.

The full list of Cambridges 2020 winners and their award citations:

Copley Medal

Alan Fersht FMedSci FRS, Department of Chemistry, and Gonville and Caius College

He has developed and applied the methods of protein engineering to provide descriptions of protein folding pathways at atomic resolution, revolutionising our understanding of these processes.

Croonian Medal and Lecture

Professor Barry Everitt FMedSci FRS, Department of Psychology and Downing College

He has elucidated brain mechanisms of motivation and applied them to important societal issues such as drug addiction.

Royal Medal A

Professor Herbert Huppert FRS, Department of Applied Mathematics and Theoretical Physics, and Kings College

He has been at the forefront of research in fluid mechanics. As an applied mathematician he has consistently developed highly original analysis of key natural and industrial processes.

Hughes Medal

Professor Clare Grey FRS, Department of Chemistry and Pembroke College

For her pioneering work on the development and application of new characterization methodology to develop fundamental insight into how batteries, supercapacitors and fuel cells operate.

Ferrier Medal and Lecture

Professor Daniel Wolpert FMedSci FRS, Department of Engineering and Trinity College

For ground-breaking contributions to our understanding of how the brain controls movement. Using theoretical and experimental approaches he has elucidated the computational principles underlying skilled motor behaviour.

Michael Faraday Prize and Lecture

Sir David Spiegelhalter OBE FRS, Winton Centre for Risk and Evidence Communication and Churchill College

For bringing key insights from the disciplines of statistics and probability vividly home to the public at large, and to key decision-makers, in entertaining and accessible ways, most recently through the COVID-19 pandemic.

Milner Award and Lecture

Professor Zoubin Ghahramani FRS, Department of Engineering and St Johns College

For his fundamental contributions to probabilistic machine learning.

Rosalind Franklin Award and Lecture

Professor Julia Gog, Department of Applied Mathematics and Theoretical Physics, and Queens College

For her achievements in the field of mathematics and her impactful project proposal with its potential for a long-term legacy.

Royal Society Mullard Award

Professor Stephen Jackson FMedSci FRS, Gurdon Institute, Department of Biochemistry

For pioneering research on DNA repair mechanisms and synthetic lethality that led to the discovery of olaparib, which has reached blockbuster status for the treatment of ovarian and breast cancers.

The full list of medals and awards, including their description and past winners can be found on the Royal Society website: https://royalsociety.org/grants-schemes-awards/awards/

Adapted from a Royal Society press release.

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Nine Cambridge researchers among this year's Royal Society medal and award winners - Mirage News

Life after R&D death: Halozyme CEO Helen Torley on the company’s pivot and path to profitability – FierceBiotech

Halozyme CEO Helen Torley has always been frank about what would happen if the companys foray into drug development failed: The two-pillar company would ditch its internal pipeline and focus solely on providing its drug delivery technology to pharma partners.

Now, nine months after its pancreatic cancer program foundered in phase 3, that transparency, along with lots of planning and quick decision-making, have turned out to be key in keeping the company aliveand profitable.

With the second quarter of 2020, Halozyme delivered its first profitable quarter of what it expects to be many, with earnings per share of $0.19. The company reeled in $25.8 million in income, compared witha loss of $14.6 million during the same quarter last year.

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Part of that gain comes from canning its R&D work. In November 2019, the company announced that its lead program, a PEGylated version of its hyaluronidase enzyme, in tandem with Celgenes Abraxane and the chemo drug gemcitabine, did not extend the lives of patients with pancreatic cancer compared withAbraxane and chemo alone.

Halozyme, which had two plans in its pocketone for an FDA approval and one for a trial failurepulled the trigger on a pivot. It started a reorganization that would lay off more than half of its staffersabout 160and worked to expand its drug delivery business with the 120 employees that remained.

RELATED: Halozyme kills pipeline, cuts 55% of jobs as lead cancer med flops in phase 3

The hardest part was the town hall, where we had to talk about the results being negative. To see almost 300 faces looking at you trying to understand what happened, Torley said. Because we had such conviction; opinion leaders had such a conviction we had a good shot at it.

All told, winding down its development pipeline dropped its R&D spend to $9 million from $33.9 million the same quarter last year.

But saving on R&D costs isnt the whole story. Halozymes revenue jumped to $55.2 million from $39.1 million year over year, largely thanks to payments from partners Janssen and Bristol Myers Squibb totaling $32.3 million.

The companys partnerships are based on Enhanze, its drug delivery technology that uses the enzyme hyaluronidase to break down hyaluronan, a natural sugar chain that forms a gel in the innermost layer of the skin. This allows drugs, like Janssens multiple myeloma med, Darzalex, to be injected just under the skin, saving patients from hours-long intravenous infusions.

In the second quarter alone, Halozyme has seen three new approvals for its partnered drugs: nods from the FDA and European Medicines Agency for the subcutaneous version of Darzalex, and an FDA green light for Roches Phesgo, a combination of breast-cancer drugs Perjeta and Herceptin using the Enhanze technology.

Halozyme now has five partnered drugs on the market, including subcutaneous versions of Roches Herceptin and Rituxan, as well as of Baxaltas HYQVIA, a treatment for primary immunodeficiency. And more are in the works. Janssen is also testing subcutaneous Darzalex in in a protein-folding disorder called light-chain amyloidosis, while Bristol Myers is testing a subcutaneous form of Yervoy in combination with its PD-1 blocker Opdivo in multiple cancers.

This year is mostly about milestones It was important we didnt take the eye off the ball with Enhanze and continued to support our partners with trial initiations and the regulatory back-and-forth as we get ready for approvals, Torley said. If everything like that could go well, we knew we would be profitable in the second quarter.

Between 2020 and 2022, the company expects to pick up $350 million to $450 million in milestone payments as its partnered programs move through the clinic.

We expect three phase 3 starts this year, all of which are associated with milestones, Torley said. The company expects to see nine new studies this year, including one new phase 2 study and five new phase 1 studies.

In 2021, Halozyme expects to add some royalty income, too: Once all the reimbursement is in place for Darzalex in the U.S. and Europe, and for Phesgo in the U.S., we see the opportunity for robust uptake, Torley said. 2020 is a bit of a setup yearwe will see revenues this year, but they will be substantial in 2021.

Although the COVID-19 pandemic threw a wrench in the plan, Halozymes partners have stayed on track. Despite seeing delays of one to two quarters in some partnered programs, its partners have managed to start trials on time. Based on its partners' latest updates, Halozyme anticipates $230 million to $245 million in sales this year.

And to keep growing, Halozyme plans to add new partners to the mix.

Things slowed down certainly in Q2, but were definitely seeing an uptake in the pace of discussions, Torley said. Weve never had as broad an array of conversations as we have at the moment, with both biotech and pharma.

Torley believes the Janssen and Roche approvals have driven this interest.

We had two recent approvals with products early in their life cycle with a lot of growth ahead of them What Enhanze has allowed to happen has grabbed peoples attention: turning a four- to six-hour IV into a three- to -five-minute [subcutaneous injection]. People marvel at that, she said.

Beyond supporting its partners and signing new ones, any growth will come from M&A. It's not an immediate priority, "but if at the right time, we find the right platform," the company would acquire a technology that complements Enhanze and that is "partly or substantially derisked."

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Life after R&D death: Halozyme CEO Helen Torley on the company's pivot and path to profitability - FierceBiotech

Demand Scenario of Zinc Deficiency Treatment Market to Remain Positive Through 2025 – Research Newspaper

Zinc is a micronutrient and essential trace element required for metabolism reactions that catalyze number of enzyme reactions, protein folding, gene expression etc. Deficiency of zinc may cause range of infectious diseases and other complications affecting almost every aspect of health such as delayed or retarded growth in children, hair loss, lack of cognitive function, reduced sense of taste and smell, loss of appetite, immunosuppression, anemia, night blindness, etc. Zinc deficiency may also cause deficiency of vitamin A as zinc is required for vitamin A absorption. Zinc deficiency is the fifth leading factor causing disease across the globe, and according to World Health Organization (WHO) 31% of the global population is experiencing zinc deficiency.

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Underdeveloped countries are facing major problem of death due to childhood diarrhea and pneumonia caused due to zinc deficiency. As per International Zinc Nutrition Consultative Group (IZiNCG) zinc deficiency is expected to cause 176,000 diarrhea deaths, 406,000 pneumonia deaths and 207,000 malaria deaths across the world Regions such as Africa, Middle East and South-East Asia are bearing high burden of zinc deficiency due to poor nutrition, lack of breastfeeding etc. Treatment of zinc deficiency mainly involves intake of zinc rich food and zinc supplements. Mild zinc deficiency requires treatment with zinc supplements at 2-3 times the recommended dietary allowance (RDA) and moderate to severe zinc deficiency requires zinc supplements with 4-5 times the RDA and treatment is continued for at least 6 months.

Oral repletion of zinc in the form of zinc acetate, zinc sulfate, zinc aspartate, zinc orotate and zinc gluconate, multivitamin supplements etc. and zinc supplements are available in the form of oral tablets capsules, syrups or intravenous solutions. National Institute of Health (NIH) recommends daily intake of 20-40 mg zinc for adults orally to avoid complications caused by zinc deficiency. High dose of zinc i.e. more than 50 mg per day is recommended to patients with severe zinc deficiency or patients with irreversible malabsorptive disorders. Intravenous administration of zinc is rarely recommended unless the patient is suffering from intestinal failure or on long-tern treatment with total parenteral nutrition.

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Market for zinc deficiency treatment is primarily driven by increasing occurrence of malnutrition in underdeveloped and developing countries. Increasing incidence of anemia, hypovitaminosis A, etc. are other factors driving demand for zinc supplements across the globe. Zinc supplements are also used as an adjunctive therapy in many disorders such as alopecia, ulcers, electrolyte replenishment therapy for diarrhea, etc.; high incidence of which can propel the demand for zinc supplements over the forecast period. However, unavailability of treatment opportunities in the underdeveloped countries can be the factor which can hamper growth of global zinc deficiency treatment market.

The global market for zinc deficiency treatment is segmented on basis of product types, treatment, dosage form, distribution channel and geography:

Among treatment type, dietary supplements is expected to dominate the global market as dietary zinc supplements are recommended along with drug therapy in every patient suffering from zinc deficiency. Among all four distribution channels of zinc supplements, e-commerce is expected to experience highest growth over the forecast period.

On the basis of geography, global zinc deficiency treatment testing market is segmented into five key regions viz. North America, Latin America, Europe, Asia Pacific, and Middle East & Africa. Asia Pacific is expected to dominate the global market for zinc deficiency treatment due to high level of malnutrition in developing countries such as India, Bangladesh, Sri Lanka, etc. The region is expected to witness robust growth due to growing awareness towards malnutrition and its consequences. North America and Western Europe shows lower occurrence of zinc deficiency as adequate intake of animal food by population in the region. Despite high incidence of zinc deficiency in Middle East and Africa market growth is limited by access to zinc supplements due to low purchasing power and poor health consciousness among general population.

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Some of the key players present in global zinc deficiency treatment market are

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Demand Scenario of Zinc Deficiency Treatment Market to Remain Positive Through 2025 - Research Newspaper

Cryo-EM structures of the air-oxidized and dithionite-reduced photosynthetic alternative complex III from Roseiflexus castenholzii – Science Advances

INTRODUCTION

Photosynthesis transforms solar energy to chemical energy and supports nearly all life on Earth. Sunlight is absorbed by pigments in the light-harvesting (LH) antenna system, and excitation energy is transferred to the reaction center (RC), where photochemistry occurs, initiating an electron transfer process. The electron transport chain (ETC) couples the redox reactions associated with electron donors and acceptors to proton translocation to build up a proton motive force across the membrane, which, in turn, drives the formation of adenosine triphosphate (ATP) and other energy-consuming processes. In photosynthetic and respiratory ETCs, complex III (mitochondrial and bacterial cytochrome bc1, chloroplast and cyanobacterial cytochrome b6f) functions primarily to couple thermodynamically favorable electron transfer to proton translocation across the membrane (13). As quinol:electron acceptor oxidoreductases, these complexes create a transmembrane (TM) proton gradient through the Q-cycle mechanism: Four protons are translocated for every two electrons transferred to cytochrome c (cyt c) or plastocyanin upon quinol oxidation (35).

Notably, a functional counterpart for the cyt bc1 complex, alternative complex III (ACIII), has been identified in a wide range of bacterial taxa, and its presence usually coincides with the absence of the cyt bc1 complex (610). This complex is structurally and compositionally unrelated to the bacterial cyt bc1 complex, but it plays the same central role as a quinol:electron acceptor oxidoreductase in both the respiratory and photosynthetic ETCs (6, 813). In the respiratory chain, ACIII is usually associated with different cyt c oxidases and functions in aerobic electron transfer (14, 15). In the photosynthetic ETC of Chloroflexus aurantiacus, in which ACIII was originally discovered (16), the photosynthetic ACIII catalyzes the oxidation of menaquinol and mediates transfer of the released electrons to a periplasmic blue copper protein auracyanin, which, in turn, completes a cyclic electron transfer back to the RC (9, 12, 13).

Recent studies of the respiratory ACIII from Rhodothermus marinus (17) and Flavobacterium johnsoniae (18) have elucidated the structural features of this complex that are related to quinol coordination, cyt c oxidase association, and putative proton translocation. Regarding the association with different cyt c oxidases and the linear electron transfer mode of respiratory ACIII, the photosynthetic ACIII has a distinct composition and functions in a simple and efficient cyclic ETC using the electron donor menaquinol (8, 12, 13, 19, 20). However, the structure of the photosynthetic ACIII remains unknown. In particular, the fundamental coupling mechanisms underlying the menaquinol oxidation and proton translocation of the respiratory and photosynthetic ACIII complexes have received little research attention. Therefore, a structural investigation of the photosynthetic ACIII is necessary for a deeper understanding of the common coupling mechanism used by the ACIII from diverse bacterial taxa.

Roseiflexus castenholzii is a chlorosome-less filamentous anoxygenic phototroph. It contains a mosaic LH antenna, the type II pheophytin-quinone RC, and a cyclic electron transport system. The LH antenna of R. castenholzii is structurally similar to the LH1, but spectroscopically it resembles the LH2 of purple bacteria (19, 21, 22). Our previous structure of the R. castenholzii core complex (rcRC-LH) revealed a previously unknown architecture and a new type of menaquinone shuttling channel in the bacterial RC-LHs and illustrated the molecular basis underlying the LH and energy transfer mechanisms of early prokaryotes (23). We then extracted and purified R. castenholzii ACIII and its periplasmic electron acceptor auracyanin and revealed that ACIII oxidizes menaquinol-4 or menaquinol-7 and transfers the electrons to the copper ion coordinated in auracyanin (24). Here, we report the structures of the six-subunit R. castenholzii ACIII in air-oxidized and dithionite-reduced states, determined by single-particle cryoelectron microscopy (cryo-EM) at 3.3- and 3.5- resolution, respectively. We elucidated its structural features and here propose a previously unrecognized redox-coupled electron transfer and proton translocation mechanism that apparently links the respiratory and photosynthetic functions of the ACIII.

We purified the ACIII from phototrophically grown R. castenholzii using a modification of previous methods (7, 8, 16). We next used SDSpolyacrylamide gel electrophoresis (PAGE) and blue native PAGE to evaluate the purified ACIII (fig. S1A). Consistent with the molecular size expected from the corresponding gene sequences, we observed that the overall 300-kDa complex was composed of six subunits (ActA, ActB, ActC, ActD, ActE, and ActF), with molecular masses ranging from ~10 to 110 kDa (fig. S1A). Each subunit was confirmed by peptide mass fingerprinting (PMF) (tables S1 and S2). Further, gel filtration analysis (fig. S1B) indicated that the purified ACIII was a monomer containing one copy of each subunit. Spectral analysis indicated that the purified ACIII was air-oxidized: It was reduced via addition of sodium dithionite (fig. S1C). The reduced-minus-oxidized difference spectrum showed two absorbance peaks at 524 and 554 nm, indicating the increase of the c-type heme absorbance after reduction (fig. S1D).

To elucidate the proposed conformational changes that were involved in the redox-driven proton translocation of respiratory ACIII (17), the vitrified air-oxidized and dithionite-reduced ACIII were individually subjected to cryo-EM single-particle analysis. A dataset of 257,815 particles of the air-oxidized ACIII was used to reconstruct an electron potential map with an average resolution of 3.3 and a local resolution extending to 2.5 (fig. S2 and movie S1). The final reconstructed cryo-EM map was resolved and enabled us to build an accurate model of the TM helices with side chains in the air-oxidized ACIII (fig. S3) and all the cofactors and lipid molecules (Table 1 and fig. S4). The cryo-EM map of the dithionite-reduced ACIII was reconstructed from 488,581 particles to 3.5- resolution, the composition and overall structure of which resembles that of the air-oxidized ACIII (Table 1, fig. S5, and movie S2).

Different from the respiratory ACIII from R. marinus that contains seven subunits (ActABCDEFH) and one additional unidentified subunit (17), the photosynthetic ACIII only contains six core subunits (ActA, ActB, ActC, ActD, ActE, and ActF) as in F. johnsoniae (18). Superimposition of R. castenholzii ACIII structure with that of R. marinus and F. johnsoniae gives a main-chain root mean square deviation (RMSD) of 1.5 and 3.2 , respectively. Like the two respiratory ACIII structures, R. castenholzii ACIII is assembled into an L-shaped architecture with dimensions of 141 by 98 by 80 ; a TM arm (42 ) containing 23 TM helices from subunits ActA, ActC, ActD, and ActF; and a peripheral arm comprising the periplasmic subunits ActA, ActB, and ActE. On the periplasmic side, subunit ActB forms extensive contacts with ActE, the penta-heme binding domain of ActA, and the periplasmic region of ActC, ActD, and ActF. The loop between the two TMs of ActD inserts into the interface of ActA, ActB, ActC, and ActF. The globular domain of ActD is located in the cytoplasm (Fig. 1, A and B).

(A) The cryo-EM map of the air-oxidized ACIII is shown from the front (left) and back (right) view and represented with the dimensions of the TM and periplasmic region. Each of the six subunits is labeled with the length of its encoded amino acid. (B) Cartoon representation of the air-oxidized ACIII. The c-type hemes and lipids are shown as sticks, and the iron-sulfur clusters are shown as spheres. (C) Representation of the arrangement of cofactors in the air-oxidized ACIII. (D) Edge-to-edge distance between the iron-sulfur clusters and the hemes in the air-oxidized ACIII. The distances are labeled and shown in dashed lines. Color codes for all panels: lime green, ActA; slate, ActB; wheat, ActC; violet, ActD; yellow orange, ActE; aquamarine, ActF; red, c-type heme; orange brown, iron-sulfur clusters; yellow, lipids.

Similar to R. marinus ACIII, given its known electron transport function, one [3Fe-4S] and three [4Fe-4S] clusters in ActB, and six c-type hemes (five in ActA and one in ActE) were modeled in the density map of R. castenholzii ACIII (Fig. 1C and fig. S4), apparently forming wires of the six hemes and the iron-sulfur clusters (Fig. 1D). The six c-type hemes exemplify identical positions and orientations as that in R. marinus and F. johnsoniae ACIII, but there are only one [3Fe-4S] cluster and one [4Fe-4S] cluster identified at deviated positions in F. johnsoniae ACIII (fig. S6A). The six hemes and four iron-sulfur clusters are all located within reasonable edge-to-edge distances (less than 14 ) to permit direct electron transfer along the wire.

Structural superimposition of the air-oxidized and dithionite-reduced ACIII showed a main-chain RMSD of 0.4 (Fig. 2A), indicating that dithionite reduction does not induce obvious conformational changes at the current resolution. However, the difference map of ACIII (the air-oxidized map minus dithionite-reduced map) showed major electron potential differences at the periplasmic subunits (ActA, ActE, and ActB) and the cytoplasmic side of the TM region of ActA, ActC, and ActD (Fig. 2A). The increased electron potentials were observed at the six heme groups as well as the four iron-sulfur clusters (Fig. 2A and movie S3), indicating that these electron carriers are essentially reduced after dithionite treatment, which is consistent with the increased heme spectral differences upon dithionite reduction (fig. S1D).

(A) The air-oxidized minus dithionite-reduced electron potential difference map (orange) of the ACIII is shown from the front (left) and back (right) view. The structures of the air-oxidized and dithionite-reduced ACIII (white) are superimposed, with the iron-sulfur clusters and heme groups shown in sphere and stick models. The color code for each subunit and cofactors of the air-oxidized ACIII is the same as that in Fig. 1. (B) Ribbon representation of the ActA and ActE subunits bound with pentaheme and monoheme groups (red sticks). The N and C termini of the protein are highlighted with a black dot and labeled. (C) Spatial organization and immobilization of the pentaheme and monoheme groups in ActA and ActE subunits. The residues that axially coordinate the heme iron ions are shown as sticks and labeled; the center-to-center distances of the hemes are shown and labeled. (D) Overall structure of ActB subunit. The B1 and B2 domains are colored in blue and magenta, respectively. The iron-sulfur clusters are shown as spheres. (E) Coordination of the iron-sulfur clusters in the ActB subunit. The conserved cysteine residues that coordinate the iron-sulfur clusters are shown as sticks and labeled, and the B2 domain is shown as a ribbon with 80% transparency.

ActA (Gln9-Arg226) and ActE (Cys33-Asn193) were found to be penta-heme and mono-heme subunits, respectively, which form the main electron transfer wire of the photosynthetic ACIII. ActA is membrane-anchored, with an N-terminal TM helix (1, Gln9-Trp43). Five c-type hemes were bound in the loop regions between its six helices on the periplasmic side (Fig. 2B). The C-terminal mono-heme binding domain of ActE is composed of three helices and two turns (Fig. 2B), and our model showed a lipid anchor that is present at the N terminus of ActE (fig. S4D). This observation suggested the possibility that the consensus lipobox sequence L/V-A/T-G/A-C (M30TAC33) (fig. S6B) in the actE gene sequence may be excised from the transcript or degraded following translation in cells or at some point before the final complex assembly. This phenomenon was also observed in the respiratory ACIII (17).

The six heme groups bound by ActA and ActE are each covalently attached via thioester linkages to cysteine residues of highly conserved heme binding motifs (C-X-X-C-H), and their iron ions are axially coordinated through bi-His or His-Met residue couplets (Fig. 2C and fig. S6B). The five hemes of the ActA subunit are arranged in alternating parallel (heme_2,5 and heme_3,4) and perpendicular pairs (heme_2,3 and heme_4,5) (Fig. 2C). In particular, the heme_3,4 pair adopts typical stacked motif in van der Waals contact (edge-to-edge distance, 4.8 ), whereas heme_2,3 (5.1 ) and heme_4,5 (4.5 ) exemplify the T-shaped heme pairs (Figs. 1D and 2C). The spatial organization of heme_2 to heme_5 resembles that of the tetraheme in Shewanella oneidensis STC, in which the electron transfer between stacked heme pairs is approximately an order of magnitude greater than for the T-shaped heme pairs (25). But the electronic coupling of T-shaped heme pairs would be strongly enhanced by cysteine linkages inserted in the space between these pairs (26). The heme_1 is closest in terms of edge-to-edge distance to [3Fe-4S] (8.3 ), and it is buried in a hydrophobic pocket formed by residues from ActB, ActC, ActD, and ActE (fig. S6C). The porphyrin ring of the mono-heme in ActE is inclined about 60 compared to that of heme_5 in ActA, with an edge-to-edge distance of 9.0 and a center-to-center distance of 16.7 (Figs. 1D and 2C).

No midpoint redox potential data are available for the six hemes and iron sulfur clusters in R. castenholzii ACIII. The heme redox potentials of R. marinus ACIII was shown to range from 45 mV to +230 mV at neutral pH (11). Potentiometric titration of the c hemes in F. johnsoniae ACIII gives redox potentials at +331 mV and +439 mV (18). For C. aurantiacus ACIII, which shares 59% sequence identities with R. castenholzii ACIII, the heme midpoint redox potentials were determined to be 228 mV, 110 mV, +94 mV, and +391 mV (8). With the highest redox potential at +391 mV (8), the monoheme of ActE is believed to be the final electron prosthetic group to accept the electrons transferred from the five hemes in ActA. Regarding the high sequence homology and functional similarity (9) of ActA and ActE with that of C. aurantiacus and respiratory ACIIIs from R. marinus and F. johnsoniae (fig. S6, A to C), as well as the spatial distribution of the six hemes (Fig. 2, A to C), electrons can be sequentially transferred along a wire that begins with the heme_1 in ActA and ends with the monoheme in the ActE subunit, and then eventually to the acceptor auracyanin (13, 24).

The largest subunit, ActB (Gly77-Glu1006), was found to be composed of 26 helices and 17 strands that can be divided into two subdomains: the B1 domain (Gly77-Phe714) and B2 iron-sulfur binding domain (Leu715-Glu1006) (Fig. 2D). The N terminus of ActB was resolved from Gly77, just behind the signal peptidase cleavage site A71LA73. The twin-arginine translocase signal peptide assists with the translocation of ActB to periplasm (27). Superimposition analysis of ActB with PsrA and PsrB subunits of polysulfide reductase (PsrABC), an integral membrane-bound enzyme that performs quinone-coupled reduction of polysulfide substrates (28), revealed that the B2 iron-sulfur binding domain is similar to PsrB and that both the folding and positions of the four iron-sulfur clusters match well between the two subunits (fig. S7A). The analysis also revealed that the B1 domain of ActB forms a fold similar to the known substrate binding pocket of PsrA (fig. S9B), yet the absence of any cofactors in our model suggests that the function of ActB does not mirror the reduction activity of PsrA.

The four iron-sulfur clusters are covalently coordinated by conserved Cys residues (Fig. 2E and fig. S6D), with the largest edge-to-edge distance of 9.7 (Fig. 1D). The [3Fe-4S] is located at the interface with ActC and in the most proximity to the periplasmic side of the four-helix bundle that hosts the menaquinol binding pocket (Fig. 3A). This iron-sulfur cluster is the most probable primary electron acceptor from the menaquinol bound in the ActC subunit. The midpoint redox potential of [3Fe-4S] in R. marinus ACIII was determined to be +140 mV (11, 17), which is sufficient for an uphill electron transfer from menaquinol (70 mV at pH 7) (29). The role of the three [4Fe-4S] clusters in both respiratory and photosynthetic ACIIIs are still unknown. The air-oxidized minus dithionite-reduced electron potential differences at the [3Fe-4S] and three [4Fe-4S] clusters indicate that these iron-sulfur clusters can be reduced upon dithionite treatment (Fig. 2A and movie S3). An edge-to-edge distance of 8.3 was observed between the [3Fe-4S] and heme_1 in the ActC subunit (Fig. 1D), which suggests that the electrons accepted by the [3Fe-4S] cluster are most probably transferred along the heme wire to reduce a periplasmic electron carrier.

(A) Ribbon representation of the side (left) and bottom-up (right) views of the ActC (wheat) and ActF (aquamarine) subunits. The TM helices of ActC and ActF are labeled with numbers, and the iron-sulfur clusters in ActB and heme groups in ActA subunit are shown in spheres and red sticks, respectively. The N and C termini of each subunit are highlighted with a black dot and labeled. (B) Open cavity (bright yellow) between the TM helices of ActA, ActC, and ActD subunits of ACIII, which is equivalent to the menaquinol binding pocket. The cavity inside the TM region of ACIII was calculated using the program HOLLOW (44), and it is shown as a surface model. (C) Zoomed-in view of the putative menaquinol binding pocket, with essential amino acids shown as stick models. (D) Interactions between the modeled menaquinol head (blue stick model) and the menaquinol binding pocket. Residues are shown as stick models, and the hydrogen bonding interactions are shown as dashed lines with distances labeled.

The ActC (Lys8-Ala464) and ActF (Gln4-Ser399) subunits each contain 10 TM helices. The middle eight helices are arranged into two four-helix bundles (TM2-5 and TM6-9 of ActC, and TM2-5 and TM6-9 of ActF), which were sandwiched by the intersection of TM1 (TM1) and TM10 (TM10) (Fig. 3A). The helix bundles of ActC and ActF resemble the structure of PsrC dimer (fig. S7C). Superimposition of the structures of ActC and PsrC gives a main-chain RMSD of 1.1 . The quinone binding pocket of PsrC, which is formed by the N-terminal four-helix bundle and located at the periplasmic side, was identified according to the structures complexed with MK-7, pentachlorophenol, and ubiquinone-1 (28). Although no menaquinol was found in the current structures, we observed an open cavity between the TM helices of ActA, ActD, and TM3/4 of ActC subunits, which is equivalent to the quinol binding pocket of PsrC (Fig. 3B and movie S4).

On the basis of structural analysis and comparison as well as sequence alignment (fig. S8), we identified a menaquinol binding pocket of ACIII at the periplasmic side of the first four-helix bundle in ActC, about 12 away from the [3Fe-4S] cluster (Fig. 3C). Adjacent to [3Fe-4S], a strictly conserved His141 residue replaces the Glu67 of PsrC quinol binding pocket (Fig. 3C and figs. S7D and S8), which is involved in proton transfer from the menaquinol (30). The side chains of Trp84, Ile88, Phe91, Pro138, and Leu168 further form a hydrophobic pocket that is capable of immobilizing the menaquinol head group (Fig. 3D). The two carbonyl oxygen atoms of the modeled menaquinol head are capable of forming hydrogen bonds with the imidazole group of His141 (2.8 ) and the hydroxyl group of Asp171 (2.8 ), which further forms hydrogen bonds with Asp252 (2.9 ) (Fig. 3D). At the bottom of the pocket, Ile249 takes the position of Tyr130 in PsrC, which forms a hydrogen bond (2.6 ) with the O1 carbonyl group of MK-7 (fig. S7D) (28). The menaquinol binding pocket of R. castenholzii ACIII shares high sequence homology and conformational similarity with that of R. marinus and F. johnsoniae ACIII (fig. S7, E and F), indicating that ACIIIs play essentially similar enzymatic function in the photosynthesis and respiration.

On the basis of the structural comparison with the respiratory ACIII, we further identified a putative proton translocation passage in the ActC subunit. The passage begins at the cytoplasmic residues Arg198 and Asp199 and proceeds to the TM region located primarily at the first four-helix bundle of the periplasmic region (Fig. 4, A and C). This passage is composed of 22 proton-carrying residues that provide side chains for hydrogen bonding with protons (Fig. 4A). The air-oxidized minus dithionite-reduced electron potential differences were mainly distributed at the cytoplasmic side of TM1, TM3, TM4, TM5, and TM10 of ActC (Figs. 2A and 4C), where the menaquinol binding pocket and proton translocation passage are absent. Furthermore, we did not observe obvious structural differences at the proton translocation passage between the air-oxidized and dithionite-reduced structures (Fig. 2A).

(A) Organization of the menaquinol binding pocket (highlighted with a green box), [3Fe-4S] cluster, heme_1, and the putative proton translocation passage in ActC (wheat). The distance between [3Fe-4S] and the side chain of Asp171 in the menaquinol binding pocket is 12.2 , and the edge-to-edge distance between the [3Fe-4S] cluster and heme_1 is 8.3 . The residues that constitute the proton translocation passage and menaquinol binding pocket are shown as stick models, and the TM helices of ActC are shown as ribbon with 80% transparency. (B) Zoomed-in view of the hydrogen bonding networks between the menaquinol binding pocket and middle passage residues of the proton translocation passage in the ActC subunit, as well as the residues from the ActD and ActF subunits. Residues are shown as stick models, and the hydrogen bonding interactions are shown as dashed lines with distances labeled. (C) Topology diagram of the ActC subunit. The amino acids that constitute the menaquinol binding pocket and proton translocation pathway are shown in blue and green triangles, respectively.

In the middle of the passage, three strictly conserved residuesArg394, His246, and His99form a hydrogen bonding network that links the menaquinol binding pocket and proton translocation passage (Fig. 4B). The imidazole group of His246 forms hydrogen bonds with the guanidine group of Arg394 (3.1 ) and imidazole nitrogen of His99 (3.3 ), which forms a weak hydrogen bond with the main chain of Ile95 (3.3 ). The main-chain nitrogen of Ile95 is further hydrogen-bonded with the main-chain oxygen of Phe91 (3.1 ), one of the key residues involved in menaquinol coordination. In close proximity to His246, Ile248 forms a hydrogen bond with Asp171 (3.0 ), which is hydrogen-bonded with Asp252 (2.9 ) at the top of the menaquinol binding pocket (Fig. 4B).

Arg394, His246, and His99 are strictly conserved in both the respiratory and photosynthetic ACIII (fig. S8). Superimposition analyses showed that the triplet residues adopt the same side-chain orientations and hydrogen bonding network as that from R. marinus and F. johnsoniae (Fig. 5, A and B), suggesting that these residues share a similar function in the respiratory and photosynthetic ACIII. Asp394 is also conserved in other polysulfide, tetrathionate, nitrate, and dimethyl sulfoxide reductases (30). Mutation of Arg394 in Wolinella succinogenes PsrC resulted in an inactive enzyme, which was suggested that it stabilizes the deprotonated quinol (30). Regarding the sequence conservation, location, and extensive hydrogen bonding interactions with the menaquinol binding pocket, the triplet residues are likely essential for coupling the menaquinol oxidation and proton translocation.

(A) Comparison of the proton translocation passage in R. castenholzii ActC (wheat) with that of the respiratory ActC from R. marinus (PDB 6f0k, white) and F. johnsoniae (PDB 6btm, pink). The [3Fe-4S] cluster, heme_1, and the amino acids are shown as sticks. (B) Middle passage residues that are capable of forming hydrogen bonding networks. (C) Putative proton translocation passage in R. castenholzii ActF subunit (aquamarine) and its superimposition with that of R. marinus (PDB 6f0k, white) and F. johnsoniae (PDB 6btm, pink). (D) The middle passage residues that are capable of forming hydrogen bonds in ActF subunits are shown in stick models.

We observed a similar proton translocation passage in the ActF subunit formed by 20 less conserved amino acids (about 20% identities) from the cytoplasmic to periplasmic side (Fig. 5C and fig. S9). In the middle of the ActF passage, side chains of Glu335, Ser217, and Tyr339 are capable of forming hydrogen bonding interactions, but no menaquinol-binding pocket and similar hydrogen bonding networks as that in ActC were found (Fig. 5C). In addition, Ser217 and Tyr339 are less conserved in both the photosynthetic and respiratory ActF, and Glu335 is replaced by Arg in C. aurantiacus and His residue in the respiratory ActF (Fig. 5D and fig. S9). Minor electron potential differences were only observed at His287, Ala189, and Met65 of the ActF subunit, suggesting that this subunit is not sensitive to the air-oxidized and dithionite-reduced state of ACIII. To be noted, a conserved residue Tyr264F forms a hydrogen bond with the main-chain oxygen of Pro267C (2.8 ), which is close to the periplasmic portion of the proton translocation passage in ActC (Fig. 4B). The distinct conservation of these proton translocation passages indicates that the ActC subunit plays consensus important role in both the respiratory and photosynthetic ACIII.

The function of the ActD subunit in the ACIII remains obscure. We observed hydrogen bonding interactions between Asn100 of ActD and Tyr755 of ActB, as well as between Leu106 of ActD and Tyr753 of ActB (fig. S10A). We also observed extensive hydrophobic interactions between residues located in the ActD loop and subunits ActB, ActF, and ActC. These interactions can stabilize the conformation of TM5, which contributes to the menaquinol binding pocket (fig. S10A). Near the menaquinol binding pocket, a hydrogen bond is formed between the hydroxyl groups of Glu118 of ActD and Ser244 of ActC (2.1 ), which was close to the His246 of ActC that would be essential for coupling the menaquinol oxidation and proton translocation (Fig. 4B). Thus, ActD might play a primary role in stabilizing the TM region of ACIII, which thereby contributes to a stable menaquinol binding pocket and proton translocation passage.

As a functional counterpart of the bc1 complex, ACIII plays a central role in both the photosynthetic and respiratory ETC of a wide range of bacterial taxa (610). It couples quinol oxidation with TM proton translocation to build up a TM proton gradient, which drives the formation of ATP required for bacterial growth. However, the nature of the coupling mechanism(s) for the respiratory and photosynthetic functions of ACIII has not been well discussed.

The photosynthetic bacterium R. castenholzii has evolved a simple but efficient cyclic ETC to transform solar energy into chemical energy that is different from the linear respiratory chain (3133). Our study has revealed the structure of the first photosynthetic ACIII comprising six conserved subunits, in both the air-oxidized and dithionite-reduced states, as well as the nature and position of the cofactors, including six hemes and four iron-sulfur clusters. We also detected a menaquinol binding pocket positioned at the periplasmic side of the TM subunit ActC. This pocket is capable of immobilizing the menaquinol head group via strictly conserved residues (Fig. 3D), which is linked by extensive hydrogen bonding interactions with three proton-carrying residues in the middle of an apparent proton translocation passage. In addition, the ActD subunit is shown to coordinate extensive interactions with subunits ActA, ActB, ActC, and ActF.

Previous enzymatic analyses confirmed the activity of photosynthetic ACIII as a menaquinol:auracyanin or cyt c oxidoreductase (9). Recently, we revealed that R. castenholzii ACIII oxidizes menaquinol-4 or menaquinol-7 and transfers electrons to its periplasmic electron acceptor auracyanin (24). It has been revealed that there is a single quinol binding site in R. marinus ACIII by isothermal titration calorimetry experiments (17). The high sequence and structural similarity among photosynthetic and respiratory ACIIIs would also suggest a single menaquinol binding pocket of R. castenholzii ACIII. Within this pocket, menaquinol binds and is oxidized by the terminal electron acceptor auracyanin, releasing two protons into periplasm. Considering that menaquinone is reduced at the binding site of RC-LH complex (23), accepting two protons from cytoplasm, an apparent efficient quinone shuttling cycle is formed among RC-LH, the membrane quinone pool, and ACIII in the R. castenholzii simple cyclic photosynthetic ETC. As a result, with the reduction of one molecule menaquinone at RC-LH and the oxidation of one shuttled menaquinol at ACIII, two transferred electrons are accompanied with two protons transferred from cytoplasm to periplasm, yielding a H+/e ratio of 2:2.

To date, no experimental data on the H+/e stoichiometry for any ACIII were reported. Previous studies proposed that ACIII could also actively pump additional protons from cytoplasm into periplasm (10, 12, 14, 15), which would yield a different H+/e stoichiometry deduced from above quinone shuttling cycle. However, the detailed mechanism of its active proton translocation has not been elucidated. The lack of any redox-active cofactors in the TM and cytoplasmic regions of ACIII argues against a Q-cycle type H+ pumping mechanism, such as is used in the cyt bc1 and cyt b6f complexes.

Structural comparison and analyses revealed two putative proton translocation passages in ActC and ActF, respectively, for both photosynthetic and respiratory ACIII (Fig. 5, A and C). The side chains of the middle-passage triplet residues Arg394, His264, and His99 of ActC adopt exactly the same conformation for all three ACIIIs (Fig. 5B). However, the proton-carrying residues in the passage of ActF are less conserved than that of ActC (Fig. 5, C and D). Notably, the respiratory ACIIIs from R. marinus (17) and F. johnsoniae (18) contain two conserved His and Asp residues in the middle passage of ActF, but these two residues are replaced by Glu and Tyr in the R. castenholzii ACIII (Fig. 5D and fig. S9). In addition, neither menaquinol binding pocket nor hydrogen bonding network was found in ActF. Less differences of electron potential around ActF between the air-oxidized and dithionite-reduced states (Fig. 2A) suggest that ActF is insensitive to the changes of redox potential. Therefore, most probably, ActF passage lacks a driving force for efficient TM proton translocation. If there exists a redox-coupled active proton translocation in ACIII, it would be mostly located in the ActC subunit and driven by the coupling between menaquinol oxidation and putative proton passage, without the necessary conformational change.

On the basis of the above structural analysis and discussion, we propose a redox-coupled proton translocation mechanism for the photosynthetic ACIII, which occurs within the subunit of ActC (Fig. 6). In the menaquinol binding pocket, at the close-to-neutral pH environment (pH ~6.5) of periplasmic space, both Asp171 and His141 are deprotonated and coordinate the bound menaquinol (MQH2) by hydrogen bonds. The hydroxyl hydrogens of menaquinol can be bound by the hydroxyl oxygen of Asp171 and imidazole nitrogen of His141, respectively. Upon oxidation, the hydroxyl group of menaquinol that faces the side chain of Asp171 is first oxidized to form an intermediate semi-menaquinol. The released hydrogen protonates Asp171. Lacking the coordination by Asp171, the semi-menaquinol would be relocated in the binding pocket and thus enable extraction of one proton from the proximal proton passage of ActC, resulting in one proton translocated from the cytoplasm. The binding of the extracted proton will induce a reorganized electronic structure of semi-menaquinol, releasing another hydroxyl hydrogen to protonate His141. The reorganized semi-menaquinol can be further coordinated by the hydroxyl group of Asp171. Then, the semi-menaquinol is further oxidized to form menaquinone (MQ) and release the exacted proton. After the release of menaquinone and the extracted proton from the menaquinol binding pocket, the two protons from oxidation of menaquinol are released to periplasmic space with the deprotonation of Asp171 and His141. During this proposed process, one instance of menaquinol oxidation is coupled to one proton pumped from the cytoplasm. As a result, three protons are released into the periplasm per two electrons transferred (Fig. 6).

The menaquinol head group and the side chains of the essential amino acids are shown to indicate the coupling mechanism of the photosynthetic ACIII from R. castenholzii. Upon menaquinol oxidation, two electrons are sequentially transferred to the [3Fe-4S] cluster with a time interval, two protons from oxidation of menaquinol are released to periplasmic space, and one proton is pumped from the cytoplasm (colored in red) through hydrogen bonding networking with the essential amino acids in the proton translocation passage. As a result, three protons are released into the periplasm per two electrons transferred during oxidation of one instance of menaquinol.

In both the respiratory and photosynthetic ACIII structures, a [3Fe-4S] cluster in the ActB subunit functions as the primary electron acceptor from menaquinol (17, 18), donating the electrons along the six-heme wire and finally onto the periplasmic electron acceptor. Both the photosynthetic ACIII from R. castenholzii and the respiratory ACIII from R. marinus contain additional three [4Fe-4S] clusters, while only one [4Fe-4S] cluster was identified in the F. johnsoniae ACIII (18). The function of [4Fe-4S] clusters remains largely unknown.

Our observation of the electron potential differences of these [4Fe-4S] clusters between air-oxidized and dithionite-reduced states indicates that these clusters are either accessible to dithionite or connected to the electron transfer wire. In Psr with the absence of heme groups, two electrons released from MK-7 are transferred via five [4Fe-4S] clusters to the bis-MGD (bis-molybdopterin guanine dinucleotide) cofactor and then reduce polysulfide (28). Unfortunately, no cofactors were observed in the B1 domain of ActB subunit (fig. S7B), indicating an electron transfer dead end in these [4Fe-4S] clusters. How they contribute to the electron transfer of ACIII needs to be further considered.

Both heme and iron-sulfur cluster are single electron carriers that are unable to transfer two electrons simultaneously. Thus, a sequential transfer of electrons upon menaquinol oxidation is necessary. In addition, the latency time between the formation of semi-menaquinol and its further oxidation needs long enough to allow extraction of proton from the translocation passage, but it should not be too long to avoid the formation of reactive oxygen species. On the other side, the final periplasmic electron acceptor auracyanin can only accept one electron each time. Therefore, the speed of electron transfer in ACIII should be well controlled. The alternating T-shaped spatial organization of the six hemes in ACIII would limit in one order the electron transfer efficiency of the heme wire, which would increase the steady time of semi-menaquinol. This limitation could be further compensated by the [4Fe-4S] clusters playing as an electron sink. Overall, the possible electron transfer during menaquinol oxidation would look like that, the first electron would quickly sink into the [4Fe-4S] clusters via [3Fe-4S] with the formation of semi-menaquinol, and the second electron could then be transferred to the final periplasmic acceptor auracyanin via the heme wire; with a second auracyanin binding, the sinking electron in the [4Fe-4S] clusters could be further transferred to the final acceptor via the heme wire. As a result, the existence of the [4Fe-4S] clusters would be very important in assisting sequential and efficient transfer of two electrons with an intrinsic time interval.

In summary, our work provides a structural basis and conceptual insight into the coupling mechanism underlying menaquinol oxidation, electron transfer, and proton translocation for the photosynthetic ACIII, which seems likely to play the same role as a menaquinol:electron acceptor oxidoreductase in respiratory ACIIIs. Direct experimental will be required for definitive characterization the proton pumping mechanism of these ACIIIs.

R. castenholzii DSM 13941 was grown in a batch culture anaerobically in modified PE medium at 50C under high-light conditions for 10 days (19). Cells were harvested by centrifugation at 10,000g for 20 min, and the pellet was washed twice with 20 mM tris buffer (pH 7.4) and then stored at 40C.

A suspension of whole membranes [with OD880 (optical density at 880 nm) = 20 cm1] in 20 mM tris-HCl (pH 8.0; buffer A) was treated with 1% -octyl glucoside and stirred for 1 hour at room temperature in the dark. The extraction was centrifuged at 200,000g for 2 hours (Ti 70 rotor, 45,000 rpm) at 4C. The pellets were resuspended in 50 mM sodium acetate (pH 5.0; buffer B) and treated with 0.5% -dodecyl maltoside as above with 1% -octyl glucoside. The supernatant from the second ultracentrifugation was collected and filtered through a 0.22-m Millipore filter and subsequently loaded on a prepacked cation exchange chromatography column (SPHP5, GE Healthcare), which had been equilibrated with buffer B containing 0.04% -dodecyl maltoside (which makes up buffer C). The column was extensively washed with 50 mM NaCl in buffer C until the eluent was colorless. Last, the crude ACIII was eluted from the column by a sodium gradient from 0.1 M NaCl to 0.4 M NaCl with 50 ml of buffer C at 2 ml min1. The collected fractions were concentrated and further purified by Superdex-200 gel filtration in buffer D [100 mM NaCl, 0.02% -dodecyl maltoside, and 20 mM tris-HCl (pH 8.0)]. The fractions with an absorption ratio of A413/A280 higher than 1.38 were pooled and used for cryo-EM analysis.

The polypeptide composition of the purified complex was determined by SDS-PAGE and blue-native PAGE. The sample solubility was optimized by dissolving samples in buffer containing 5% 2-mercaptoethanol for 30 min at 65C; these conditions yielded the sharpest protein bands. The identity of SDS-PAGE and blue-native PAGE bands was confirmed by PMF using matrix-assisted laser desorption/ionizationtime-of-flight (MALDI-TOF) mass spectroscopy.

Stained bands from the SDS-PAGE were excised and destained and washed with 50% acetonitrile in 50 mM aqueous NH4HCO3. Proteins were then reduced with 10 mM dithiothreitol in 100 mM NH4HCO3 for 30 min. Cysteine residues in the proteins were further alkylated by 55 mM iodoacetamide in 100 mM NH4HCO3 for an additional 30 min. Trypsin (Promega Trypsin Gold, TPCK (L-1-tosylamido-2-phenylethyl chloromethyl ketone)treated) in 50 mM NH4HCO3 was added to the gel pieces, and the enzymatic reaction proceeded overnight at 37C. Afterward, peptides were extracted twice with 1% trifluoroacetic acid in 60% acetonitrile for 30 min. Extracted solutions were collected, dried completely in a speed-vac, and then redissolved in 50% acetonitrile containing 0.1% trifluoroacetic acid for mass spectrometry analysis.

The identities of proteins were determined by PMF using an ABI 4700 MALDI-TOF mass spectrometer. A mixture of the peptide sample and freshly prepared matrix solution (10 mg ml1 -cyano-4-hydroxycinnamic acid in 50% acetonitrile) was spotted on a stainless-steel target plate. Peptide mass value searches were performed against the National Center for Biotechnology Information (NCBI) database using Mascot software (www.matrixscience.com). The alkylation of cysteine was included as a possible modification. The mass tolerance for the monoisotopic peptide mass was set to 0.6 Da.

Three-microliter aliquots of air-oxidized ACIII (4 mg ml1) was placed on the glow-discharged GiG R1.2/1.3 300-mesh gold holey carbon grid (Jiangsu Lantuo Biotechnology, China) and blotted for 3.0 s under a blot force of 1 at 100% humidity and 16C before being flash-frozen in liquid ethane with a Mark IV Vitrobot system (FEI). Micrographs were acquired on a Titan Krios microscope (FEI) operated at 300 kV with a K2 Summit direct electron detector (Gatan). SerialEM (34) was used for automatic data collection. A nominal magnification of 22,500 was used for imaging, which yielded a pixel size of 1.04 . The defocus range was between 1.2 and 3.3 m. Each micrograph was dose-fractionated to 32 frames under a dose rate of 9.2 e/2 per second and an exposure time of 6.4 s, which resulted in a total dose of about 59 e/2.

For the sodium dithionitereduced ACIII, 3-l aliquots of a sample (4.5 mg ml1) were placed on the glow-discharged CryoMatrix R1.2/1.3 300-mesh amorphous alloy film (product no. M024-Au300-R12/13, Zhenjiang Lehua Technology Co. Ltd., China) and blotted for 3 s under a blot force of 0 at 100% humidity and 16C before being flash-frozen in liquid ethane with a Mark IV Vitrobot system (FEI). Micrographs were acquired on a Titan Krios microscope (FEI) operated at 300 kV with a K2 Summit direct electron detector (Gatan). SerialEM was used for automatic data collection. A nominal magnification of 22,500 was used for imaging, which yielded a pixel size of 1.04 . The defocus range was between 1.5 and 2.5 m. Each micrograph was dose-fractionated to 32 frames under a dose rate of 9.4 e/2 per second and an exposure time of 6.4 s, which resulted in a total dose of about 60 e/2.

Motion correction and exposure weighting was performed by the MotionCorr2 program (35), and the CTF (contrast transfer function) parameter was estimated using the Gctf program (36). The automatic particle picking was performed by Gautomatch (developed by K. Zhang, MRC Laboratory of Molecular Biology, Cambridge, UK) and Auto-picking module in RELION; an initial model was made by e2initialmodel.py in EMAN2 software package (37), and all other steps were performed using RELION (38). For the air-oxidized ACIII dataset, 600 particles were manually picked and extracted for two-dimensional (2D) classification. The resulting 2D class averages were used as the templates for the automated particle picking, which yielded 257,815 particles from 1700 micrographs. The picked particles were extracted at 2 2 binning and subjected to three rounds of 2D classification. A total of 197,496 particles were finally selected for 3D classification.

Good 2D class averages in different orientations were selected to generate the initial model. A total of 177,489 particles were left after two rounds of 3D classification and re-extracted into the original pixel size of 1.04 . The following 3D refinement and postprocessing yielded an EM map with a resolution of 3.45 . After performing CTF refinement in RELION3, the resolution was increased to 3.24 . Reported resolutions were estimated with a soft-edge mask around the protein complex and micelle densities and based on the gold-standard FSC (Fourier Shell Correlation) = 0.143 criterion. Local resolution was estimated with Resmap (39).

For the reduced ACIII dataset, 1970 unscreened micrographs were subjected to 3D referencebased auto-picking in RELION3; reconstruction of the ACIII dataset was the 3D reference low passfiltered to 20 . The resulting 488,581 particles were used to extract particles at 2 2 binning. After two rounds of 2D classification, 297,122 particles were selected for a 3D refinement and alignment-free 3D classification, and 219,913 particles from the best 3D class were re-extracted without downscaling. The following 3D refinement and postprocessing yielded an EM map with a resolution of 3.68 . CTF refinement and another alignment-free 3D classification improved the resolution to 3.51 and 3.46 , respectively. The final subset had 207,633 particles.

De novo atomic model building was conducted in Coot (40). Sequence assignments were guided by residues with bulky side chains. The starting models of the cofactors were taken from the CCP4 ligand library. The model was real spacerefined by PHENIX (41, 42) with intra-cofactor and protein-cofactor geometric constraints. The refinement and model statistics are listed in Table 1. All figures were prepared in PyMOL (www.pymol.org) or UCSF Chimera (43).

The difference map between air-oxidized and dithionite-reduced ACIII was calculated using EMAN2 (37). First, the cryo-EM map of dithionite-reduced ACIII was fitted to that of air-oxidized ACIII by Chimera and then was clipped into the same box size using e2proc3d.py in EMAN2. Then, the structural amplitudes of both maps were scaled using e2proc3d.py in EMAN2. Last, the difference map between the corrected maps was computed by the e2.py python tool in EMAN2 and further low-passfiltered at a quarter of the Nyquist criterion.

The rest is here:
Cryo-EM structures of the air-oxidized and dithionite-reduced photosynthetic alternative complex III from Roseiflexus castenholzii - Science Advances

Development of a pH-responsive polymersome inducing endoplasmic reticulum stress and autophagy blockade – Science Advances

INTRODUCTION

The important role of autophagy in health and disease has received unprecedented attention (1). As an essential and conservative physiological catabolic process, autophagy is responsible for the removal of protein aggregates, damaged organelles, and foreign bodies that invade cells (2). The autophagy contents are sequestered by double-membraned compartments (autophagosomes). Subsequently, the autophagosomes are fused with lysosomes to form autolysosomes, which degrade and circulate to produce nutrients (amino acids, fatty acids, and nucleotides) to be supplied to cells, and this dynamic process is called autophagic flux (3, 4). The unhindered autophagic flux is of great notable for maintaining homeostasis and protecting cells from attacks (5). The autophagic level is characterized by the amount of autophagy markers (e.g., autophagosomes and autolysosomes) and autophagy protein markers [e.g., LC3 (microtubule-associated protein-1 light chain-3)]. The upstream initiation or downstream blocking of autophagic flux will lead to the increase in autophagy markers (6). Malignant tumors are at a relatively high autophagic level compared with normal tissues to satisfy their metabolic demands, evasion, and resistance and allow tumor growth, survival, and malignancy (7). The involvement of autophagy in the occurrence and development of tumors suggests the reliable prospect of autophagy manipulation as an interventional means for tumor therapy (8). Autophagic flux blockade can disrupt the metabolism cycle of cancer cells, thereby reducing their fitness (9). Hydroxychloroquine (HCQ) and chloroquine (CQ) are the only clinically available autophagic blocking agents and they have been proven to be effective adjuvants for chemotherapeutics to increase their antitumor effects (10). HCQ/CQ, as a lysosomal alkalizing agent, can diffuse into lysosomes, causing the lysosomal pH to rise and dysfunction so that the lysosomes no longer fuse with the autophagosome, thereby blocking autophagic flux (11). However, the use of HCQ/CQ as a monotherapy strategy to block autophagic flux displays limited antitumor activity in clinical treatment (12). However, when HCQ is combined with autophagic stimulus, it can significantly increase its antitumor effect and reduce its dosage (13).

Aberrant endoplasmic reticulum (ER) status triggers autophagy stimulation (14). The ER acts as a reservoir of calcium ions in cells and is responsible for the correct folding and secretion of proteins (15). The accumulation and aggregation of misfolded proteins cause ER stress, triggering unfolded protein response (UPR) to significantly increase the autophagic level to restore homeostasis (16). As an ER stress initiator, tunicamycin (Tuni) blocks N-glycosylation and causes ER stressinduced autophagy to increase the autophagic level through PERK [protein kinase RNAlike ER kinase]/Akt (protein kinase B)/mTOR (mammalian target of rapamycin) signaling pathways, which are also closely related to matrix metalloproteinase-2 (MMP-2) expression (17).

Therefore, the combined application of the autophagic flux blocker HCQ and the ER stress initiator Tuni could cause cancer cells to have a special autophagic stress, which can severely disrupt cell homeostasis and cause cell death, resulting in a better therapeutic effect for tumor treatment. However, for a systemic administration of HCQ and Tuni, challenges such as poor hydrophilicity, poor biodistribution profile, low tumor accumulation, and tumor acid microenvironment prevent the drugs from penetrating the cell membranes, further affecting the application of free drugs in vivo (18). Moreover, high-dose HCQ in clinical application can only produce a moderate blockage of autophagic flux due to its poor efficacy, thus producing capricious therapeutic effects (19). Thus, the drug nanocarrier is considered to solve the above problems (20), as it has the following features: co-encapsulating hydrophilic and hydrophobic drugs, accumulating in tumor tissues through an enhanced permeability and retention (EPR) effect (21), entering the cells through the lysosomal pathway, and stimulating drug release with environment-responsive signals (22).

In addition, metastatic tumors undergo local migration and invasion in the early stage of tumor metastasis, and the migration speed depends on the focal adhesions (FAs) turnover (23). FAs are transmembrane multiprotein complexes containing integrins, paxillin, talin, zyxin, etc. Both cell-cell and cellextracellular matrix (ECM) adhesions form a stable connection via FAs (24). The decomposition of FAs at the cell rear by autophagy is critical for the forward movement and successful migration/invasion of tumor cells (25). In addition, MMPs are also an important factor in the selective regulation of tumor microenvironment to promote tumor metastasis, and are considered to be an inducer of epithelial-mesenchymal transition (26). The ER stress induced by Tuni regulates the PERK/Akt signaling pathway and down-regulates the expression of MMP-2 (27). Both the inhibition of the FAs turnover and the down-regulation of the expression of MMP-2 will reduce tumor metastasis.

Accordingly, in this study, we develop a pH-responsive polymersome for codelivering HCQ and Tuni drugs to simultaneously induce ER stress and block autophagic flux for achieving the antitumor effect and inhibiting tumor metastasis. A dual drugloaded, pH-responsive polymersome, Tuni/HCQ@CS-PAE, was designed to achieve this objective. The amphiphilic polymer chondroitin sulfate (CS)poly(-amino ester) was used to fabricate this polymersome, and hydrophilic HCQ and hydrophobic Tuni were loaded into the inner cavity and outer shell, respectively. Poly(-amino esters) with acid-stimulated responses are a class of highly biocompatible polymers and are believed to satisfy the performance of drug delivery (28). Repeated tertiary amine groups on the poly(-amino esters) are protonated by acid stimulation, thereby converting the hydrophobicity of the segment, resulting in the dissociation of the nanostructure and drug release (29). Simultaneously, the protonation process produces a similar HCQ effect to deacidify the lysosomes, swelling and rupturing the lysosomes, which can help the drugs to escape from the lysosomes and block the autophagic flux together with HCQ (30). Polymersomes with both a hydrophilic inner cavity and a hydrophobic shell are considered promising drug delivery platforms (31). In this work, the hydrophilic CS component can mask the surface positive charges of poly(-amino ester), prolonging the blood circulation time of the polymersomes. These polymersomes reached tumor tissues through the EPR effect, overcoming the nonselective distribution of the Tuni and HCQ drugs in vivo, increasing intratumoral accumulation, entering cells by endocytosis, and remaining in the lysosomes. Because of the pH response of poly(-amino ester), the polymersomes dissociated and produced a similar alkalization effect in lysosomes with HCQ, destroying and rapidly escaping the lysosomes, releasing the drugs Tuni and HCQ. Under the dual action of poly(-amino ester) and HCQ, the lysosomes in the tumor cells were destroyed, resulting in the blockade of autophagic flux. Moreover, the released Tuni triggered ER stress, further regulating the PERK/Akt signaling pathway to enhance the autophagic level and down-regulate the MMP-2 expression. The tumor cells were simultaneously attacked by both the inducement of autophagy due to the ER stress and the blockade of autophagic flux due to lysosomal destruction, resulting in a special autophagic stress, which seriously damaged the cell homeostasis and caused cell death.

The synthetic routes of CS-poly(-amino ester) are shown in fig. S1. The chemical structures of the block copolymers were confirmed using Fourier transform infrared spectra and nuclear magnetic resonance (NMR) spectra (figs. S2 to S4). The number-average molecular weight of CS-poly(-amino ester) was obtained as 8044 g/mol through gel permeation chromatography. The dual drugloaded Tuni/HCQ@CS-PAE polymersome was prepared by dialysis. The encapsulation efficiency (EE) and encapsulation content (EC) of Tuni were 38.5 and 10.5%, while those of HCQ were 56.1 and 11.2%, respectively. The morphologies of the Tuni/HCQ@CS-PAE polymersomes were characterized using transmission electron microscopy (TEM). Apparent vesicle structures with a size of ~180 nm can be observed in Fig. 1A, and the shell thickness of the vesicle in the enlarged image is ~30 nm. The average hydrodynamic size of the Tuni/HCQ@CS-PAE polymersomes was 230.0 9.3 nm, as measured using dynamic light scattering (DLS), with a polydispersity index of 0.156. The potential was 17.2 mV (Fig. 1B), and the negative charge indicated that it is suitable for drug carriers because it cannot be prematurely cleared in the blood circulation (32). The investigation of stability suggested that the polymersomes showed no significant changes (P > 0.05) in particle size when they were placed in phosphate-buffered saline (PBS) buffer and 10% fetal bovine serum (FBS) for 48 hours at 37C (fig. S5), indicating their potential for application in vivo. The pH response of the Tuni/HCQ@CS-PAE polymersomes was evaluated in a lysosomal acidic environment, and the CS-poly(-amino ester) was assayed to determine its pKa (where Ka is the acid dissociation constant) via acid-base titration. The results showed that CS-poly(-amino ester) had a pKa value of 5.4 (Fig. 1C), which was close to the lysosomal acidity (pH = ~5.0) (33). The TEM image obtained after the Tuni/HCQ@CS-PAE polymersomes were stored at pH 5.0 for 4 hours showed that the polymersome structure disappeared (Fig. 1D), indicating that the pH response of CS-poly(-amino ester) successfully caused the dissociation of the polymersomes. The 1H-NMR spectrum of CS-poly(-amino ester) in deuterium chloride at pH 5.0 (fig. S6) showed that the peak of poly(-amino ester) could be observed, indicating that it was hydrophilic at pH 5.0. DLS was further used to detect the pH response of the Tuni/HCQ@CS-PAE polymersomes. As shown in Fig. 1E, after the polymersomes were stored under the three acidic conditions of pH 7.4, pH 6.8, and pH 5.0 for 4 hours, the particle size distribution demonstrated that the polymersomes at both pH 7.4 and pH 6.8 (tumor ECM acidity) were stable; whereas at pH 5.0, the polymersome structure was destroyed, which is consistent with the TEM results. At pH 5.0, the potential of the Tuni/HCQ@CS-PAE polymersomes significantly shifted from 17.2 to 2.08 mV (Fig. 1F), indicating that the protonation of CS-poly(-amino ester) resulted in the capture of strong positive charges. The pH response of the polymersomes imparts them the ability to release drugs on-demand. As shown in Fig. 1 (G and H), the release of HCQ and Tuni at pH 6.8 was not significantly different (P > 0.05) from that at pH 7.4, suggesting that the polymersomes were stable in the tumor ECM and would not be released in advance. However, the 24-hour releases of HCQ and Tuni at pH 5.0 (lysosomal acidity) were 86.5 and 76.6%, respectively, which were 7.52 and 6.66 times the releases at pH 7.4, respectively. This result indicates that the Tuni/HCQ@CS-PAE polymersomes can rapidly release drugs in acidic lysosomes.

(A) TEM images of the Tuni/HCQ@CS-PAE polymersomes at pH 7.4. (B) Measurement results of the Tuni/HCQ@CS-PAE polymersomes by the Malvern laser particle size analyzer at pH 7.4. (C) Acid-base titration curve of CS-poly(-amino ester). (D) TEM images of Tuni/HCQ@CS-PAE at pH 5.0. (E) Hydrodynamic particle size distribution of the Tuni/HCQ@CS-PAE polymersomes at pH 7.4, pH 6.8, and pH 5.0. (F) potential of the Tuni/HCQ@CS-PAE polymersomes at pH 7.4, pH 6.8, and pH 5.0. (G) Release profiles of HCQ from the Tuni/HCQ@CS-PAE polymersomes. (H) Release profiles of Tuni from the Tuni/HCQ@CS-PAE polymersomes.

Before applying the polymersomes to cells and animals, both mouse breast cancer cells (4T1) and human umbilical vein endothelial cells (HUVECs) were used to evaluate the cytocompatibility of the polymersome delivery system. The blank material CS-PAE polymersomes exhibited good cytocompatibility at a concentration of 20 to 400 g/ml (cell viability over 85%, Alamar Blue assay; fig. S7, A and B). Only a small amount of red spots (representing dead cells) was observed in the fluorescence image of cells, with a polymersome concentration of up to 400 g/ml (live-dead cell staining; fig. S7C), also confirming the low cytotoxicity of the polymersomes.

The endocytic pathway of polymersomes was further examined in vitro. Fluorescein isothiocyanate (FITC)labeled (green) polymersomes were cocultured with adherent 4T1 cells, and the locations of the polymersomes in the cells and lysosomes labeled by LysoTracker Red DND-99 (red) were observed using fluorescence microscopy at 1 hour (fig. S8A) and 4 hours (fig. S8C), respectively. A large amount of yellow fluorescence in the cells was observed at 1 hour, which was the result of the overlap between green fluorescence and red fluorescence, suggesting that the polymersomes were in the lysosomes. At 4 hours, the yellow fluorescent signal decreased and the separated green and red fluorescent signals increased, indicating that the polymersomes were separated from the lysosomes. The figures (fig. S8, B and D) show the corresponding fluorescence intensity profiles of the white arrow regions in fig. S8 (A and C) obtained using ImagePro Plus, respectively. It can be observed that there was a large overlap between the two fluorescent signals at 1 hour, and their Pearsons correlation coefficient was calculated to be 0.88, indicating that the polymersomes and the lysosomes were strongly colocalized at 1 hour. At 4 hours, the Pearsons correlation coefficient was reduced to 0.04 according to fig. S8D, indicating that the polymersomes successfully escaped from the lysosomes. This result indicates that the polymersomes were endocytosed into the cells by the lysosomal pathway and could successfully escape the lysosomes at 4 hours in vitro.

The damage to the lysosomes by poly(-amino ester) and HCQ was marked by an increase in the lysosomal pH value. The LysoSensor Green-189 can monitor the acidity of the lysosomes, and its fluorescence reaches the highest value in normal lysosomes and decreases with increasing pH value. As shown in fig. S8E, it was observed via fluorescence microscopy that the green fluorescence in the HCQ, blank material CS-PAE polymersomes, and Tuni/HCQ@CS-PAE treatment groups was weakened to varying degrees. The results of the fluorescence-activated cell sorter (FACS) can be more intuitively observed (fig. S8F), and Tuni did not cause a change in the acidity of the lysosomes compared with that of untreated cells (control). Both the HCQ drug and CS-PAE polymersome had an alkalization ability for lysosomes, but HCQ performed better. This can be ascribed to the fact that CS-PAE polymersomes can only destroy lysosomes involved in endocytosis. The Tuni/HCQ@CS-PAE treatment group performed the best, and the median fluorescence intensity was only 14.3% of the control group, suggesting that the double action of HCQ and the polymersomes caused an increase in the intracellular lysosomal pH.

The relationship between various treatments and autophagy was further examined in vitro. Acridine orange (AO) is an acid-sensitive dye that stains the acidic organelles, including autophagosomes and autolysosomes in the cells red, whereas the DNA and cytoplasm in cells are green. Accordingly, the ratio of red to green signals can be used to evaluate the autophagic level (34). As shown in Fig. 2A, the number of red spots (observed via fluorescence microscopy) is positively correlated with the autophagic level. The red/green ratio calculated using FACS determines the autophagic level in each treatment group (Fig. 2B). The red/green ratios of the treatment groups increased compared with those of the untreated cells (control). The red/green ratio of the Tuni/HCQ@CS-PAE treatment group was approximately 68.0% higher than that of the Tuni/HCQ treatment group and was 1.91 and 2.21 times those of Tuni@CS-PAE and HCQ@CS-PAE, respectively. The red/green ratios of Tuni@CS-PAE and HCQ@CS-PAE also increased by 83.3 and 58.3%, respectively, compared with that of the blank material CS-PAE polymersomes. The red/green ratio of the CS-PAE polymersomes treatment group was also significantly increased by 71.4% compared with that of the control group. The results suggest that both Tuni and HCQ can cause an accumulation of acidic organelles, in addition to CS-PAE polymersomes. Unfortunately, the AO cannot distinguish whether the acidic organelles are autophagosomes or autolysosomes.

(A) Fluorescence images and (B) FACS analysis of AO-stained 4T1 cells after incubation with different treatments for 24 hours; ***P < 0.001. (C) Fluorescence images of mCherry-GFP-LC3 4T1 cells after incubation with different treatments for 48 hours. (D) Quantification of the number of LC3 puncta per cell (autophagosomes, yellow puncta; autolysosomes, red puncta). (E) TEM images of cells treated with saline or Tuni/HCQ@CS-PAE polymersomes (N, nucleus; green arrow, autophagosomes; red arrow, autolysosomes).

To track the autophagic flux, mCherrygreen fluorescent protein (GFP)LC3 adenovirustransfected cells were used. When autophagy occurs, a recognized autophagy marker, LC3, aggregates in both the inner and outer membranes of the autophagosomes. The LC3 in the transfected cells simultaneously expresses red fluorescence (mCherry) and green fluorescence (GFP). Thus, it will be observed in the form of yellow puncta in the autophagosomes. When the autophagosomes and lysosomes eventually fuse to form the autolysosomes, GFP is quenched by lysosomal acidity and only exhibits red puncta. Thus, the yellow and red puncta represent the autophagosomes and autolysosomes in the autophagic flux, respectively (Fig. 2C). The LC3 puncta statistic is shown in Fig. 2D. Comparing the LC3 puncta distribution of the Tuni@CS-PAE treatment group with that of the HCQ@CS-PAE treatment group, the former has more red puncta, indicating that the autophagic flux had entered the final stage, and the autolysosome had been formed. The large yellow puncta of the latter indicate that the autophagic flux mainly remained in the autophagosome stage, suggesting that HCQ@CS-PAE destroyed the lysosomes and prevented the autophagosomes from merging with the lysosomes. In contrast to CS-PAE polymersomes, Tuni@CS-PAE increased the autophagosome puncta and autolysosome puncta, indicating that it effectively increased the autophagic level in the cells. Compared with CS-PAE polymersomes, HCQ@CS-PAE showed a significant increase in the autophagosomes, but there was a decrease in the autolysosomes, which proved that HCQ@CS-PAE has a stronger ability to destroy the lysosomes and block the autophagic flux at the autophagosome stage. The autophagic level of the Tuni/HCQ@CS-PAE treatment group was greatly improved compared with that of Tuni/HCQ, whereas the number of autolysosomes was reduced. This result indicated that the dual drugloaded, pH-responsive polymersomes could increase the autophagic level and block the autophagic flux more evidently than free drugs.

From the TEM images (Fig. 2E), it can be observed that abundant autophagosomes (green arrows) and a few autolysosomes (red arrows) accumulated in the Tuni/HCQ@CS-PAE treatment group, in contrast to the control group (saline treatment). The increase in the autophagosomes and autolysosomes showed that the autophagic level of the Tuni/HCQ@CS-PAE treatment group was significantly enhanced. Furthermore, the amount of autophagosomes was significantly more than the amount of autolysosomes, indicating that the autophagic flux was blocked during the fusion process of the autophagosomes and the lysosomes.

The ability of the polymersomes to resist tumor metastasis was examined. A wound-healing assay (Fig. 3A) and the transwell invasion assay (Fig. 3B) were used to assess the cell migration and invasion in each group of treatments in vitro. The migration area (calculated by ImageJ) in the wound-healing assay is shown in Fig. 3C. The migration area of the Tuni/HCQ@CS-PAE treatment group is only 21.1% (P < 0.001) and 38.4% (P < 0.001) of those of Tuni@CS-PAE and HCQ@CS-PAE, respectively. Matrigel matrix (simulated ECM) was coated in the transwell upper chamber as an in vitro test tool for cell invasion. As shown in Fig. 3D, the number of cells (crystal violet staining) that arrived at the back of the polycarbonate membrane was counted as a quantitative index of invasive ability. The number of invasive cells in the Tuni/HCQ@CS-PAE treatment group was only 6.7% of that in the untreated group, 8.7% of that in the Tuni@CS-PAE treatment group, and 19.3% of that in the HCQ@CS-PAE treatment group. The above results show that the drug delivery system can effectively inhibit cell migration and invasion in vitro. Furthermore, Tuni@CS-PAE has a certain effect in inhibiting cell migration and invasion, but this effect is weaker than that of HCQ@CS-PAE.

(A) Typical images of wound-healing assay. (B) Cell invasion with the transwell assay (bottom). (C) Migration area of the wound-healing assay. (D) Number of invaded cells by the transwell assay. All data are represented as the means SD from three independent experiments; ***P < 0.001.

The in vitro cell viability of different treatment groups was firstly investigated. As shown in fig. S9A, the decrease in cell viability was positively correlated with increased autophagic level and autophagic flux blockade. On the basis of the concentration of fig. S9B, the median effect plots (fig. S9, C and D) of Tuni/HCQ and Tuni/HCQ@CS-PAE can be calculated to obtain their half maximal inhibitory concentration (IC50) values. According to the calculation method in the Supplementary Materials, the IC50 value of the Tuni/HCQ@CS-PAE treatment group is 8.2 M, which is 27.7% lower than that of the Tuni/HCQ treatment group.

The antitumor effect of the pH-responsive polymersome codelivering HCQ and Tuni drugs was further evaluated using the orthotopic luciferase genetransfected 4T1 (4T1-Luc) tumorbearing BALB/c mice. The treatment schedule is shown in Fig. 4A. After 7 days of orthotopic 4T1-Luc tumor implantation, the mice were randomly divided into six groups, and the drugs or drug-loaded polymersomes were administered intravenously at 0, 3, 6, and 9 days. The IVIS imaging system was used to monitor the bioluminescence signals of the tumors at days 0 and 30 (Fig. 4B). Ex vivo tumors were photographed on day 30 (Fig. 4C), and tumor volume was measured once in 3 days (Fig. 4D) and ex vivo tumors weighed on day 30 (Fig. 4E). Tumor growth inhibition (TGI; Fig. 4F) was calculated by tumor weight. The results indicated that three of the 4T1 tumors in the Tuni/HCQ@CS-PAE treatment group had successfully ablated, and the tumor weight was only 9.6% (P < 0.001) and 4.6% (P < 0.001) of those treated with Tuni@CS-PAE and HCQ@CS-PAE, respectively, whereas the TGI was as high as 97.5%. This proves that Tuni/HCQ@CS-PAE has an excellent antitumor effect. The body weight of the mice was monitored every 3 days (Fig. 4G), and it showed no difference in each treatment group on day 30 (P > 0.05), indicating the safety of the polymersome delivery system and the potential for application in vivo. Hematoxylin and eosin (H&E) staining of the main organs (heart, liver, spleen, and kidney) (fig. S10) also revealed no significant morphological changes in all the treatment groups.

(A) Treatment schedule for 4T1 breast tumor in BALB/c mice. (B) Bioluminescence images of 4T1-Luc tumorbearing BALB/c mice were taken on days 0 and 30 after various treatments. (C) Photographs of the tumors removed from the mice in the different treatment groups at the end of the experiment. (D) Tumor volume growth curves of the different treatment groups. (E) Weight of isolated tumors in the different treatment groups. (F) Tumor growth inhibition (TGI) after the different treatments. (G) Body weight changes of mice in the different treatment groups. (H) Hematoxylin and eosin (H&E) staining and immunohistochemical (IHC) analysis of tumor sections after the different treatments. All statistical data are presented as means SD. (n = 5; #P > 0.05; ***P < 0.001). [Photo credit for (B), (C), and (H): Funeng Xu, Southwest Jiaotong University].

H&E staining, terminal deoxynucleotidyl transferasemediated deoxyuridine triphosphate nick end labeling (TUNEL), and immunohistochemical (IHC) analyses (Ki67) were used to characterize the antitumor effects further (Fig. 4H). The H&E staining sections of the Tuni/HCQ@CS-PAE treatment group showed nuclear shrinkage and fragmentation, and the cell contour disappeared. Its TUNEL-positive signal (characterized apoptosis, brown) was the largest, and its Ki67-positive signal (characterized proliferation, brown) was the smallest. These results suggest that the lysosomal pH-responsive polymersomes entrapped with Tuni and HCQ can achieve excellent antitumor effects in tumor-bearing mouse models, demonstrating the success of autophagy regulation in antitumor applications.

The mouse 4T1 tumor is a metastatic tumor, corresponding mainly to lung and bone metastasis (35). The lung of the mouse was excised on day 30, and the lung metastasis of the tumor was observed using the bioluminescence images (Fig. 5A). There was no bioluminescence signal in the Tuni/HCQ@CS-PAE treatment group, indicating that there was no lung metastasis. Moreover, the pulmonary nodules are visualized using a Bouins fixative in Fig. 5B, which also supports this conclusion. The table summarizes the number of metastasis nodes (NOMN) (Fig. 5C), and the lung nodules are categorized by diameter: less than 0.5 mm, 0.5 to 1 mm, 1 to 2 mm, and greater than 2 mm, weighted 1 to 4 in turn. Because of the effective treatment of orthotopic tumors and the effective regulation of autophagy, Tuni/HCQ@CS-PAE has an excellent antimetastatic ability. The results of NOMN are shown in Fig. 5D. The average NOMN of the HCQ@CS-PAE treatment group was 52.89% that of the Tuni@CS-PAE treatment group and 22.49% that of the CS-PAE polymersomes treatment group. This indicates that both HCQ@CS-PAE and Tuni@CS-PAE can inhibit tumor metastasis to a certain extent, but the former performed better than the latter, which is also consistent with the results of in vitro antimetastasis evaluation. The H&E staining of the lungs can also demonstrate the antimetastatic effect (Fig. 5E). The red circle framed the foreign tissues of the lungs, and the foreign tissues were observed to be tumor tissues by comparison with the H&E staining of the tumors. No tumor tissue was observed in the H&E sections of the Tuni/HCQ@CS-PAE treatment group, and the area of the tumor tissue was significantly reduced in the Tuni@CS-PAE and HCQ@CS-PAE treatment groups compared with that in the saline group, which is consistent with the lung metastasis results of Fig. 5 (A and B).

(A) Bioluminescence images of tumor lung metastases in each treatment group in vitro. (B) Photographs of lung tissues; tumor metastasis was visualized by Bouins fixative, and metastatic nodules were white (represented by red arrows). (C and D) Counting the number of lung metastasis nodules, measurement of the diameter of metastatic tumors, and performing classification and counting. Number of metastasis nodes (NOMN) = I 1 + II 2 + III 3 + IV 4 (according to the diameter of the lung nodules for class 4: I < 0.5 mm, 0.5 mm II < 1 mm, 1 mm III 2 mm, and IV > 2 mm). (E) H&E staining of lung tissue after the various treatments. The red circle marks the metastatic tumor tissue. [Photo credit for (A), (B), and (E): Funeng Xu, Southwest Jiaotong University].

The dual drugloaded, pH-responsive polymersomes (Tuni/HCQ@CS-PAE) have made breakthroughs in the antitumor effect and metastasis inhibition effects in tumor-bearing mice. Western blot (WB) and IHC were further used to explore the mechanism of action of Tuni/HCQ@CS-PAE. ER stress and autophagy are closely related (Fig. 6A). It has been reported that the ER stress enhances the autophagic level by negatively regulating the Akt/mTOR pathway (36). In addition, the expression of MMP-2 is down-regulated by the down-regulation of Akt expression. Therefore, it can be concluded that the Tuni/HCQ@CS-PAE polymersome has two important functions in vivo: increasing autophagic levels and decreasing the MMP-2 expression and blocking the autophagic flow at the autophagosome stage by preventing the fusion of the autophagosomes and the lysosomes.

(A) Schematic diagram of Tuni causing ER stress, promoting autophagy, and reducing MMP-2 expression via signaling pathways in vivo. (B) WB analysis of key proteins of ER stress and downstream pathway protein of 4T1 tumor in BALB/c mice. (C) Relative expression level of key proteins in (B); ***P < 0.001 compared with control. (D) Expression of LC3 and p62 lanes of 4T1 tumor in BALB/c mice via WB. (E) Quantification of the ratio of LC3-II to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and p62 to GAPDH expression using ImageJ software. (F) IHC pictures of talin-1, paxillin, and MMP-2 in 4T1 tumorbearing BALB/c mice.

Under normal physiological conditions, GRP78/BiP (78-kDa glucose-regulated protein/immunoglobulin heavy chainbinding protein) acts as an ER chaperone and binds to ER receptors, which is in an inactive state. However, under ER stress, GRP78/BiP dissociates from ER receptors to activate and trigger UPR (37). The dissociation of GRP78/BiP from PERK (ER transmembrane receptor) triggers kinase dimerization and autophosphorylation to generate activated PERK (p-PERK) (38). Therefore, the expression of GRP78/BiP and p-PERK can be used as an indicator of ER stress. The expression of GRP78/BiP and p-PERK of the Tuni/HCQ@CS-PAE treatment group was significantly increased by 59.7% (P < 0.001) and 87.0% (P < 0.001), respectively, compared with that of the control group (Fig. 6, B and C). It indicated that Tuni/HCQ@CS-PAE can strongly trigger ER stress. The expressions of GRP78/BiP and p-PERK of the Tuni/HCQ treatment group were only 71.7% (P < 0.001) and 70.9% (P < 0.001), respectively, of that of the Tuni/HCQ@CS-PAE treatment group, suggesting that the polymersome system is more efficient than the free drugs at the same dose. The occurrence of ER stress triggered a series of downstream signaling pathways. The expressions of p-Akt and p-mTOR proteins in the Tuni/HCQ@CS-PAE treatment group were reduced by 80.0% (P < 0.001) and 67.2% (P < 0.001), respectively, compared to the control group, suggesting that the increase in the upstream event down-regulates Akt and mTOR activity. The expression of MMP-2 was significantly decreased in the Tuni/HCQ@CS-PAE and Tuni@CS-PAE treatment groups, which were only 32.8 and 41.0% of that of the control group, respectively, which was consistent with the trend of p-Akt expression.

When the autophagy occurs, LC3-I, which is in the cytoplasm of cells, is modified and processed to form LC3-II and expressed on the autophagosome membrane. The expression of p62 (sequestosome-1) as an autophagy substrate can characterize the smoothness of the autophagic flux. When the autophagic level is increased and the autophagic flux is smooth, the expression of LC3-II is increased and the expression of p62 is decreased; however, when the autophagy level is increased and the autophagic flux is blocked, the expression of both LC3-II and p62 is increased (39, 40). As shown in Fig. 6 (D and E), the expression of LC3-II and p62 was up-regulated in all the treatment groups compared with that in the control group, suggesting that the autophagic level of each treatment group was increased, and the autophagic flux was blocked to some extent. The highest expression of LC3-II was observed for Tuni/HCQ@CS-PAE and Tuni@CS-PAE, which was consistent with the results of down-regulation of p-mTOR. The expression of LC3-II of HCQ@CS-PAE was also significantly improved, indicating that, when autophagic flux was blocked by lysosomal destruction, the overall autophagic level of the cells also increased, and the autophagic flux mainly remained in the autophagosome stage. The expression of p62 was the highest in the Tuni/HCQ@CS-PAE and HCQ@CS-PAE treatment groups, i.e., 4.67 (P < 0.001) and 4.13 (P < 0.001) times that of the control group, respectively, suggesting that substrate degradation in the autophagosomes was largely blocked.

Talin-1 and paxillin are the constituent proteins of the FAs. The turnover of FAs is the basis of cell movement. The blockade of the autophagic flux leads to the failure of FAs degradation, which reduces the ability of cell movement. As shown in Fig. 6F, the IHC sections of Tuni/HCQ@CS-PAE and HCQ@CS-PAE showed the largest amounts of talin-1 and paxillin, indicating that the blockade of autophagic flux can significantly prevent FAs turnover. In the IHC section analysis of MMP-2, the expression of MMP-2 of the Tuni/HCQ@CS-PAE and Tuni@CS-PAE treatment groups was significantly inhibited, and the results were also consistent with the WB test in Fig. 6B, indicating that the MMP-2 expression was closely related to the ER stress induced by Tuni. It is suggested that based on the results of in vitro and in vivo antimetastasis experiments, it is known that HCQ@CS-PAE has stronger antimetastatic ability than Tuni@CS-PAE, also suggesting that the reduction in FAs turnover by autophagy affects tumor metastasis more than the decrease in the MMP-2 expression. Thus, Tuni/HCQ@CS-PAE achieved a considerable tumor-metastasis inhibition effect under the combined effect of down-regulation of MMP-2 expression and inhibition of FAs turnover.

CS was acetylated to increase its solubility in dimethyl sulfoxide (DMSO). Briefly, CS (1.0 g) was added to a round-bottom flask containing formamide (50.0 ml). The system was heated to 80C to promote dissolution and then cooled to room temperature. Pyridine (557.0 l) and acetic anhydride (500.0 l) were added to the round-bottom flask and magnetically stirred at room temperature for 12 hours. The reaction solution was dialyzed and lyophilized to obtain acetylated CS (Ac-CS; 0.91 g), which was stored for later use.

Ac-CS (0.41 g), 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (0.16 g), and N-hydroxysuccinimide (0.04 g) were dissolved in reverse osmosis (RO) water. Triethylamine (0.08 g) was added to this mixture, and magnetic stirring was performed to activate the carboxyl group in an ice bath. Subsequently, 1,6-hexanediamine (0.63 g) was added, and the mixture was stirred at room temperature for 24 hours. The product Had-Ac-CS (0.49 g) was obtained via the dialysis and lyophilization of the reaction solution.

CS-poly(-amino ester) was prepared via the Michael addition reaction. Had-Ac-CS (0.37 g), Hexane-1,6-dioldiacrylate (HDDA) (0.5 g), and 3-dibutylamino-1-propylamine (DBPA) (0.37 g) were dissolved in 15 ml of DMSO, and the round-bottom flask was purged with N2. The mixture was stirred at 50C for 5 days. CS-poly(-amino ester) (1.1 g) was obtained via the dialysis and lyophilization of the reaction solution.

Dialysis was used to prepare the dual drugloaded polymersomes. First, 20.0 mg of CS-poly(-amino ester) and 7.0 mg of Tuni were codissolved in a beaker containing 5.0 ml of DMSO. Then, 5.0 ml of RO water containing 5.1 mg of HCQ was added dropwise under high-speed stirring, and the system was continuously stirred for 20 min. The system was transferred to a dialysis bag (molecular weight cutoff, 3500) for 48 hours and then lyophilized for the next experiment. EE and EC were calculated by Eqs. 1 and 2, respectivelyEE(%)=Weight of the drug in polymersomesWeight of the drug in feed100(1)EC(%)=Weight of the drug in polymersomesWeight of drug-loaded polymersomes100(2)

CS-poly(-amino ester) was placed in deionized water, and HCl solution was added until it was completely dissolved. Then, 1 to 5 l of 0.1 M NaOH solution was added dropwise, and the pH was measured after each addition. The pKa of the polymer is the pH at which it is half ionized.

The pH response of polymersomes was characterized by DLS, TEM, and 1H-NMR, respectively. The polymersomes were placed at pH 5.0, pH 6.8, and pH 7.4, respectively. After 4 hours, DLS was used to measure the particle size distribution and potential. Samples at pH 5.0 were also used for TEM and 1H-NMR detection.

The release of Tuni and HCQ in Tuni/HCQ@CS-PAE was investigated under three acidity conditions of pH 7.4, pH 6.8, and pH 5.0 at 37C. The release solution was taken 1 ml each time at the planned time point, and the same volume of fresh medium was added. The release solution was treated and analyzed by high-performance liquid chromatography.

Size changes of Tuni/HCQ@CS-PAE polymersomes after incubation in PBS or in cell culture medium [containing 10% FBS (v/v)] were monitored by DLS. The polymersome concentration was 1 mg ml1, and the experimental conditions were 37C.

Alamar Blue assay and live-dead staining were used to determine the cytocompatibility of blank polymersomes. In Alamar Blue assay detection, 1 104 cells per well of 4T1 and HUVECs were seeded in 48-well plates. After 24 hours of culture, polymersomes with 20 to 400 g/ml were added to each well. After 48 hours, the culture medium was removed, and 300 l of Alamar Blue solution [10% Alamar Blue, 80% media 199 (Gibco), and 10% FBS, (v/v)] was added for a further 3-hour incubation. They were then transferred to 96-well plates and detected by automated microplate spectrophotometer. For live-dead staining, 2 104 cells per well of 4T1 and HUVECs were seeded in 24-well plates. The cells were stained by 2 mM calcein acetoxymethylester for 10 min and propidium iodide for 5 min after 48 hours incubation, with different concentrations of polymersomes. Live cells were stained green, and dead cells were stained red when visualized by fluorescence microscopy.

4T1 cells were cultured in confocal dishes for 12 hours in Dulbeccos modified Eagles medium with 10% FBS. FITC-labeled polymersomes were added to two sets of confocal dishes, and then the medium was discarded at 1 and 4 hours, respectively. Cells were washed three times with PBS before staining, and then lysosomes were labeled with the LysoTracker Red DND-99. The fluorescence signal was observed by fluorescence microscopy.

Adherent 4T1 cells were treated with saline, Tuni, HCQ, CS-PAE, and Tuni/HCQ@CS-PAE for 12 hours, and stained with the acid-sensitive dye LysoSensor Green-189. The fluorescence intensity of each group was measured by fluorescence microscope and FACS.

The adherent 4T1 cells were treated with saline, CS-PAE, Tuni/HCQ, Tuni@CS-PAE, HCQ@CS-PAE, and Tuni/HCQ@CS-PAE, respectively. After 24 hours, the cells were stained with AO (1 l) for 15 min and detected by fluorescence microscopy and FACS, respectively.

4T1 cells were inoculated with 5 105 per well in confocal dishes before infection. The density of cells before virus transfection reached 50%, and the amount of virus mother liquor added to the plate was plaque-forming units = cell number multiplicity of infection (MOI). MOI was 20, 24 hours after infection; 2 ml of fresh medium was added to each well to replace the virus-containing medium.

4T1 cells were seeded in culture flasks at a density of 1 106 cells/ml for 18 hours. Then, saline and Tuni/HCQ@CS-PAE were added for 48 hours, respectively. Cells were digested, collected by centrifugation, and then fixed overnight in 2.5% glutaraldehyde. Samples were prepared according to TEM standard procedures and photographed.

Alamar Blue assay was used to assess the in vitro cytotoxicity. 4T1 cells were seeded in 48-well plates at a density of 2 104 cells per well. After the cells were cultured for 24 hours, various preparations were added to the well plates for 48 hours. After the incubation, 300 l of Alamar Blue solution was added for further 3 hours, and then the Alamar Blue solution was transferred to a 96-well plate, and the absorbance was measured with an automated microplate spectrophotometer. The median effect plot was a straight line fit with X = log(D) versus Y = log[fa/(1 fa)] (41). The theoretical IC50 value is the drug concentration corresponding to the x axis intercept of the median effect plot.

4T1 cells were seeded in six-well plates. When the cell confluence reached 100%, scratches were made with a 200-l pipette tip, and cells were washed three times with PBS to remove the delineated cells. The treatments were added to each group. Various therapeutic agents were added to the treated six-well plates and cultured for 36 hours in serum-free medium. The entire process was monitored with a microscope, and the healing area was calculated by ImageJ.

One hundred microliters of the diluted Matrigel was added vertically in the center of the transwell upper chamber and incubated at 37C for 4 hours to form a gel. Six hundred microliters of 10% serum medium was added to the lower chamber, and 100 l of the cell suspension was added to the upper chamber, and incubation was continued for 24 hours. The transwell chamber was removed, fixed in methanol for 30 min, stained with 0.1% crystal violet for 20 min, and the uninjured cells in the upper layer were gently wiped off with a cotton swab, and the count was observed with a microscope.

4T1-Luc cells were injected into the mouse mammary fat pad to establish an orthotopic breast cancer model. The animal experiments were approved by the Institutional Animal Care and Use Committee of Sichuan University and carried out in compliance with its guidelines. When the tumor volume of the mouse reached approximately 35 mm3, it was defined as 0 day of treatment, and the mice were randomly divided into six groups of five mice each. Each group was administered through the tail vein at 0, 3, 6, and 9 days of treatment [Tuni (7.5 mg/kg)]. Tumor volumes were calculated using the following equation: V = 0.5 A B2 (A refers to tumor length, and B refers to the tumor width). TGI was calculated using the following equation: TGI (%) = 100 (mean tumor weight of saline group mean tumor weight of experimental group)/mean tumor weight of saline group.

4T1 tumorbearing BALB/c mice were sacrificed, and the heart, liver, spleen, lung, kidney, and tumor tissues were excised, fixed with 10% formalin, dehydrated with gradient ethanol, and embedded in paraffin block. After denitrification with xylene, 4-m-thick tissue sections were stained with H&E, or for TUNEL detection, or for IHC staining with rabbit antiKi-67 polyclonal antibody and lastly observed with an optical microscope.

The potential association of ER stress with autophagy and antimetastatic mechanisms were analyzed by WB and immunohistochemistry. BIP/GRP78, PERK, Akt, mTOR, LC3, and p62 were used for WB analysis to explore the ER stressautophagy signaling pathway based on relative expression levels. MMP-2, talin, and paxillin were used as indicators of antimetastasis to analyze changes in their expression through WB and immunohistochemistry.

SPSS software was used for the statistical data analysis. Data were presented as means SD. One-way analysis of variance (ANOVA) was performed to determine statistical significance of the data. The differences were considered significant for #P > 0.05, *P < 0.05, **P < 0.01, and ***P < 0.001.

Acknowledgments: We thank the Analytical and Testing Center of the Southwest Jiaotong University. Funding: This work was partially supported by the China National Funds for Distinguished Young Scientists (51725303), the National Natural Science Foundation of China (21574105), and the Sichuan Province Youth Science and Technology Innovation Team (2016TD0026). Author contributions: F.X., Y.W., and S.Z. designed research; F.X., X.L., and X.H. performed research; F.X. and J.P. analyzed data; and F.X. and S.Z. wrote the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

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Development of a pH-responsive polymersome inducing endoplasmic reticulum stress and autophagy blockade - Science Advances

The function of folding | Feature – Chemistry World

Molecules that fold are fundamental to life. If you look at biology as a chemist, you cant escape the conclusion that almost every complicated thing that biology does at the molecular level is carried out by a sequence-specific folded heteropolymer, says Sam Gellman from the University of WisconsinMadison in the US. Chemists have been trying to learn a few of these folding tricks from biology, but according to Jonathan Clayden from the University of Bristol in the UK, rather than just replicating these polymers, the aim now is [to] do better than nature with a bit of chemical ingenuity. Using a wider spectrum of starting blocks he and others are creating molecules called foldamers that might one day beat biology at its own folding game.

The idea of synthesising molecules that could fold into secondary structures stems from work on protein folding carried out in the 1980s. A key contribution was simulations from protein [modelling] specialist Ken Dill, says Gellman, an early adopter of the approach, who came up with the name foldamer.

Dill, now at Stony Brook University in New York state, US, had been working on protein folding and concluded that the process was driven by the juxtaposition of hydrophobic and hydrophilic amino acids in proteins. Before that, the view had been that hydrogen bonding was the magic that dictated how proteins get their structure, says Dill. Work carried out by his collaborator Ron Zuckermann, then at pharma company Chiron, showed this was not the case. He used peptoids made from poly-N-substituted glycines, which have side chains appended to the backbone nitrogen atom rather than the carbon. These molecules could adopt stable helices without the presence of hydrogen bonding, which convinced Dill and Zuckermann that folding was primarily due to the nature of amino acid side chains, with the backbone hydrogen bonding acting only as additional glue.

We walk in proteins footsteps, but we lag far behind

These ideas led Gellman to wonder what other molecules might be able to fold like peptides and he remembers questioning Dill after a conference talk, asking If I could make a polystyrene with a hydrophobic styrene sub-unit and a hydrophilic styrene sub-unit, would they fold? The response was Yes, I think so.

For Dill and collaborator Zuckermann, the folding process is where life started and is responsible for the chemistry to biology transition. While the prevailing theory marks RNA as the first self-replicating molecule, Dill thinks that there must have been a stage before the RNA world where molecules started folding, publishing his foldamer hypothesis in 2017.1 Dividing monomers into those with hydrophilic (polar) and those with hydrophobic side chains, he used a simple computer model to create chains where similar subunits were attracted to each other and found that even short chains can collapse into relatively compact structures.

Theres a natural elongation mechanism that is also selective and auto catalytic, Dill explains. This is because the collapsed structures expose what he calls landing pads for catalysing other nascent polymers, ultimately creating primitive enzymes. What it means is youre going to have a whole ensemble of potential protein functions that are coming out of this soup, just naturally, because of the variability of hydrophobicpolar sequences themselves. For biology you ultimately needed information storage via DNA, but first you needed folding, Dill says.

So if biology is about folding, could chemists also harness this power? Gellman started trying in the 1990s, coming up with the name foldamer for these types of synthetic molecules, typically 1020 monomer units. It turns out, you cant do this with polystyrene because nobody knows how to make a polystyrene where you [can] control which monomer goes where, so a lot of this work has ended up focusing on polyamides, explains Gellman. He has focused on -amino acids which have their amino group bonded to the -carbon rather than the as found in biology, but still fold into helices of various shapes, comparable to those found in proteins.

Others, such as supramolecular chemist Ivan Huc, from the University of Munich in Germany, have designed more exotic structures using aromatic oligoamides, and monomers bearing proteinogenic side chains that provide the folding impetus. Hucs apple peel helical capsule can be tuned in diameter according to monomer size, and specific attractive and repulsive interactions between the amide and the other functional groups can be substituted onto the aromatic rings. These foldamers can house a guest molecule in the resulting cavity.2 These shapes are very trivial to obtain with aromatic amides and they are completely out of the reach of peptides or nucleotides, says Huc.

Designing foldamers is still a mostly trial and error process based on an understanding of local conformational preferences. Computational tools are gaining ground but arent as advanced as tools to model proteins and peptides. We walk in their footsteps, but we lag far behind, says Huc.

One of the obvious dreams is to create catalytic versions [of foldamers], says Gellman, who recently took up this difficult challenge. In some cases, enzymes speed reactions up a million times by organising molecules within enclosed pockets. While Gellman cannot make this sort of tertiary structure yet, he did create a foldamer that allows two functional groups to be arranged in proximity to each other tethered to a helix.3 Gellmans foldamer contained a and amino acids, including residues with five-membered rings, which stabilised the foldamers helical structure by constraining the backbones flexibility.

This was used to catalyse the formation of large macrocycles, which are useful as potential drugs but difficult to make as the two ends of long chain molecules need to be close together to react. Using a primary and secondary amine group each attached to a residue, the foldamer is able to correctly position the ends and form a carboncarbon bond via an aldol condensation, creating 1222 carbon rings. Previous work had shown that such foldamer systems allowed similar reactions to proceed at least 100 times faster than using small molecule catalysts. The foldamers performance is still a long way from that of an enzyme though.

Gellman and others are also working on how foldamers could out-smart biology as drug molecules. There is a whole host of peptides which sometimes are used as drugs but they break down [in the body] very fast, says Dimitri Dimitriou, chief executive of Swiss drug company Immupharma. If you can effectively create a peptide analogue, which is stable, then [foldamers] have the potential to be as big as the monoclonal antibody industry thats the excitement from the commercial side. He is confident that within five years foldamer drugs will be on the market.

Gellman co-founded Longevity Biotech in 2010 to develop peptide drugs incorporating -amino acids.4 These peptides only have a quarter to a third of the residue, but because theyre distributed along the backbone, proteolytic enzymes will cut [them] very slowly, he explains.The company call these helical foldamers hybridtides and are trying to design hybridtide drugs that bind to G protein-coupled receptors (GPCRs), transmembrane proteins that transmit signals inside a cell when stimulated by molecules outside. They are currently conducting a pre-clinical biomarker study for a Parkinsons disease drug candidate.

During the coronavirus shutdown Gellman has continued to work on foldamers that may block the Sars-CoV-2 virus that causes Covid-19. The approach is based on work carried out in 2009 inspired by a drug for HIVAids.5 A 36-residue peptide, enfuvirtide, is effective in blocking the virus attaching itself to cells, but the drug has such a short half-life that patients needed to be injected twice a day. We made variants that were 300-fold less susceptible to proteolysis [digestion] because of the a [backbone] and thats what were trying to do with the coronavirus, says Gellman.

Its a very complicated and difficult challenge but this is what we are trying

Immupharma are also developing foldamer drugs alongside subsidiary company Ureka, based on the work of Giles Guichard at the University of Bordeaux in France. But their foldamers swap some amino acids for ureas, which have two amino groups joined by a carbonyl. Oligourea is particularly good to form helices and those helices are similar to peptide helices you have a good mixture of rigidity coming from the urea [backbone] and some flexibility coming from the sidechain groups, which can be substituted a little bit like an amino acid, explains Sebastien Goudreau, head of research at Ureka.

As proof-of-concept Ureka has started with glucagon-like peptide-1 (GLP-1), the 31-amino-acid hormone found in the pancreas that enhances the secretion of insulin and is used for the treatment of type 2 diabetes and the liver disease non-alcoholic-steatohepatitis. Their foldamer replaces four consecutive GLP-1 amino acids with three urea residues.6 We have shown that it works and proved that it can extend the half-life dramatically [in mice], say Dimitriou. This could mean a dose would only be needed once a month and if resistant enough to digestive enzymes it might be able to be taken orally, although Dimitriou says they have not proven this yet.

Also on the radar are complex proteinprotein interactions, traditionally considered undruggable. Its a very complicated and difficult challenge, says Huc. But this is what we are trying. He has been designing foldamer molecules that can match a binding site in terms of their size, shape and proteinogenic side chains as far they can predict, but the final trick is to tether it to the protein. Using disulfide linkers, foldamers bearing different proteinogenic side chains were attached via a cysteines thiol side chain. Hucs achiral foldamer will resonate between a left-handed and right-handed helix, but if it interacts with the protein surface, one version will become more favourable and predominate; this can be detected using circular dichroism spectroscopy.7 The sign of an interaction doesnt mean tight binding, says Huc, but from these interactions, I can design.

Not only has nature created folded molecules, but also molecules that can change their shapes. For example, GPCRs will undergo conformational switching as they respond to hormones and the molecules that stimulate our senses of taste and smell. Clayden has been using foldamers to try and recreate the action of these receptors. Weve been designing molecules that have exactly the same sort of features when they pick up a ligand for example, they change shape and as a result they transmit information through the structure of the molecule thats what we call dynamic foldamers.

Unlike nature, Clayden starts with an achiral amino acid, -aminoisobutyric acid (AIB). You end up with a helix that can either be left- or right-handed and can actually inter-convert very rapidly between those, he says. The switching mechanism is provided by a large cyclic amino-borate group on the amine end of the foldamer. When a bulky chiral diol ligand is added it will form a boronate ester which then forms a methanol-bridge to the amine group. The steric bulk of the ligand forces the foldamer to switch to one helical sense.8 Clayden has shown these artificial receptors work when embedded in phospho-lipid vesicles.9 [In] the long term we would like to get these things into real cells. Weve done some very preliminary work, he says. These dynamic foldamers could lead to smart drugs that could independently switch enzyme pathways on or off within cells depending on a specific stimulus.

Clayden has used the same approach to imitate our colour vision, which in nature relies on the GPCR receptor rhodopsin in the retinal rods. Our molecule is an azobenzene chromophore and thats attached to an AIB foldamer that changes shape when the azobenzene responds to light, he explains. In UV light the molecule switches to its cis conformation which induces a screw sense in the foldamer making what Clayden calls a conformational photo diode.10 He envisions future smart chemical systems made from dynamic foldamers for example, simply using different coloured lights to turn reactions on and off or switch from one enantiomeric product to another. Were currently working on a system that binds a catalyst, but releases it when its prompted to switch. That sort of idea could be used to release, for example, an enzyme inhibitor.

Dills foldamer hypothesis for the early stages of life supposes a move from secondary folded structures to the proteins we have today, with their complex tertiary structures, combining helices and sheets made from defined peptide sequences. The real power of biology in my view, and where I would love to see foldamers go, is hooking domains together, he says. But chemists are some way from this. Most proteins are over 100 residues thats pretty hard for chemical synthesis, says Gellman.

Most labs are using solid-phase synthetic methods and starting to introduce automation but synthesising the relevant monomers isnt trivial. Small molecule synthesis is not nearly as advanced a field as it should be, says Gellman. For peptide chemistry, many of the starting blocks are commercially available but for foldamers that isnt the case. We can buy some of the amino acids we need, but many of them, particularly when they have rings to constrain their local conformation, we cant, and we dont know how to make [them].

Most proteins are over 100 residues thats pretty hard for chemical synthesis

Nevertheless chemists are attempting some simple tertiary structures. Several groups have produced foldamers that mimic the zinc finger domain (a protein motif that is able to coordination one or more zinc ions and binds a wide variety of biological molecules). Foldamers have also re-created the four-helix bundle motif, with hydrophobic residues buried in the core. Huc has even formed helical bundles in non-polar organic solvents showing these structures can form in very different environments to nature.11

To create larger structures, Huc has suggested borrowing natures solution: ribosomes, the cells protein factory. [My] long term dream is to hijack this machinery, and teach or modify the ribosome to produce [non-natural] chemical entities. This hasnt been done yet and might not be so easy. Ribosomes are complexes of RNA and protein that are able to link amino acids together. They start with a messenger RNA (mRNA) template which base pairs with transfer RNA (tRNA) molecules that carry individual amino acids.

We need to think of other things that nature doesnt do at all

Hucs initial work with ribosomes in 2018 used novel RNA enzymes known as flexizymes, designed by Hiroaki Suga at the University of Tokyo in Japan, that are capable of attaching non-natural amino acids to tRNA. Huc was able to attach a dipeptide-appended aromatic helical foldamer. He then used an E. coli ribosome to synthesise a foldamerpeptide hybrid the foldamer needed to unfold to get through the ribosome exit tunnel.12 While the ribosome is not forming bonds within the foldamer itself, its certainly a small step in that direction.

Going back 30 years the question was whether biological polymers and their ability to fold were unique. Chemists have answered that: we can tell many different types of chemical backbones have a propensity to fold, says Huc. The question is now whether we can make increasingly complex large folded molecules and what can we do with them. Nature has taught us some tricks, but chemists have a wider palette to work from. [We need to] think of other things that nature doesnt do at all, suggests Huc. Perhaps the key developments will be in high temperature materials or micro-processors, who knows?

Rachel Brazil is a science writer based in London, UK

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