Daily Archives: July 27, 2021

Safe and effective vaccines offer hope for an end to the COVID-19 pandemic. However, the possible emergence of vaccine-resistant SARS-CoV-2 variants, as well as novel coronaviruses, make finding treatments that work against all coronaviruses as important as ever. Now, researchers reporting in ACS Journal of Proteome Research have analyzed viral proteins across 27 coronavirus species and thousands of samples from COVID-19 patients, identifying highly conserved sequences that could make the best drug targets.

Drugs often bind inside pockets on proteins that hold the drug snugly, causing it to interfere with the proteins function. Scientists can identify potential drug-binding pockets from the 3D structures of viral proteins. Over time, however, viruses can mutate their protein pockets so that drugs no longer fit. But some drug-binding pockets are so essential to the proteins function that they cant be mutated, and these sequences are generally conserved over time in the same and related viruses. Matthieu Schapira and colleagues wanted to find the most highly conserved drug-binding pockets in viral proteins from COVID-19 patient samples and from other coronaviruses, revealing the most promising targets for pan-coronavirus drugs.

The team used a computer algorithm to identify drug-binding pockets in the 3D structures of 15 SARS-CoV-2 proteins. The researchers then found corresponding proteins in 27 coronavirus species and compared their sequences in the drug-binding pockets. The two most conserved druggable sites were a pocket overlapping the RNA binding site of the helicase nsp13, and a binding pocket containing the catalytic site of the RNA-dependent RNA polymerase nsp12. Both of these proteins are involved in viral RNA replication and transcription. The drug-binding pocket on nsp13 was also the most highly conserved across thousands of SARS-CoV-2 samples taken from COVID-19 patients, with not a single mutation.

The researchers say that novel antiviral drugs targeting the catalytic site of nsp12 are currently in phase II and III clinical trials for COVID-19, and that the RNA binding site of nsp13 is a previously underexplored target that should be a high priority for drug development.

Reference: Genetic Variability of the SARS-CoV-2 Pocketome by Setayesh Yazdani, Nicola De Maio, Yining Ding, Vijay Shahani, Nick Goldman and Matthieu Schapira, 28 June 2021, Journal of Proteome Research.DOI: 10.1021/acs.jproteome.1c00206

The authors acknowledge funding from the Natural Sciences and Engineering Research Council of Canada, the European Molecular Biology Laboratory and the Structural Genomics Consortium.

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Ending the COVID-19 Pandemic: Progress Toward One Drug To Treat All Coronaviruses - SciTechDaily

I last wrote about Deepminds efforts to predict protein folding and structure here, with their AlphaFold software. AlphaFold really performed very strongly in the 2020 protein folding challenge, and that got a lot of attention. Well, theyve recently published a great deal of detail on how they did this, released their source code, andtheyve announced that theyre going to be releasing their computed structures of 350,000 proteins, to be followed in the coming months by up to 100 million more. Heres the database. And a group at the University of Washington has just published on their own similar approach (RosettaFold) and has also made this code freely available.

So its clear that the world of computational protein structure prediction is in a very different place than it was a couple of years ago. But Im already on record as (1) cheering this sort of thing on while (2) saying that it doesnt make as much difference to drug discovery as many stories and press releases have had it. Do the latest developments change my mind? What does this all mean? Ive been talking with colleagues and seeing comments from people in the field, so heres my attempt.

Well, for one thing, it means that a lot of people in academia are going to have to rewrite their research grants. If you have been working on computational protein folding yourself, odds are that you have had your doors blown off by these recent developments and will need to rethink. That doesnt mean theres nothing left to do (far from it read on) but anyone who was trying to do similar stuff to DeepMind was already in the position of the RosettaFold people, at best, and if you were trying to do similar work to RosettaFold, well. . .youd better target things carefully.

Another thing that were all going to have to get used to is that for years (decades) people have considered computational error to be the most likely source of error when a predicted structure and an experimental one dont match, and quite rightly so. Were getting to the point now where the ball is in the experimentalists court, and thats something new. Right now, if you have a big mismatch between the two, it is frankly more likely to be an experimental error, because the folding predictions are getting so solid. This is disorienting, to say the least.

Theres also the synergy with the experimental data. For the many, many of us who are not cystallographers, X-ray data can seem like its being delivered on golden tablets to the sound of trumpets. But protein X-ray structures depend on model-building as well; you try to see which structures best fit the experimental electron density data. And those data can very often be interpreted in different ways, especially when it comes to subtle details of conformation. I say subtle, but sometimes those small structural things can make huge differences in protein function just look at the prolyl isomerase enzymes, whose job it is to make proline residues sit in the cis or trans fashion in the overall chain, and at the number of proteins whose downstream activities depend on such state-switching. Having access to such well-attested structural models changes the way that X-ray data are handled, and for the better. There are also differences in protein structures depending on the method used to determine them, and these computations could help to resolve those, too.

But what this leads to is what I keep pointing out when I give my various talks on the effects of AI and ML methods on chemistry and drug discovery. These things redefine grunt work: they make larger and larger areas that were formerly the site of human labor into machine labor instead, which is faster, more tireless, and getting more accurate all the time. What does that do to us humans? It pushes us towards higher-level problems that are not yet subject to computational or automated solutions. In the case of protein folding and structure, it means that we now will spend more of our time on the harder stuff: protein complexes, the classification and function of protein surfaces in general, the effects of all the wide variety of post-translational modifications, the dynamics of protein conformation changes in real cell-biology time, the subtleties of how small-molecule ligands work their way in and out of binding sites, and the related question of how allosteric sites and cofactors modify these things from afar.

Its important to realize that the new protein computational tools do not make all these into solved problems. Not even close. They clear out a lot of obstacles so that we can get to these problems more easily and more productively, for sure, but they do not solve them once we get up to the actual rock faces in our particular gold mines. To pick an immediate example of this, Ive seen a comment from a structural biologist pointing out that when you ask AlphaFold for the structures of various key kinase enzymes, it gives you a very accurate one of what we already know to be the inactive form of the protein. Kinases have several regions that flop and scoot into different and easily accessible conformational states, and (at present, anyway) these structure prediction suites will not necessarily capture all of these, and they most certainly will not tell you which ones are associated with the active enzyme or would be more relevant to a proteins different functions in vivo.

Consider those prolines I just mentioned above: AlphaFold might give you a cis proline in one protein structure or it might give you atrans one at some particular residue in a particular protein, but it will not be able to tell you that both of these are found in a living cell, that they are interconverted by yet another enzyme, and that the two forms will have totally different functions. Meanwhile, other prolines in the same protein will never interconvert at all, and you wont know that, either. These details are up to us humans to work through. Similarly, many enzymes need cofactor molecules bound to them to do some of their work, and AlphaFold structures have no way to consider these nor the presence of things like zinc or calcium ions that can also have a profound effect on protein structure and function. These are the tougher problems that will be ironed out by humans (literally, in the case of iron-associated proteins), with machine help.

And thats why I talk the way I do about protein structure prediction and its effects on drug discovery. Drug discovery is all about those biological effects what else could it be concerned with? And these are higher-order things than just the naked protein structure, as valuable as that can be. Remember, our failure rate in the clinic is around 90% overall, and none of those failures were due to lack of a good protein structure. They were caused by much harder problems: what those proteins actually do in a living cell, how those functions differ in health and disease, how they differ between different sorts of human patients and between humans in general and the animal models that were used to develop the compounds, what other protein targets the drug candidate might have hit and the downstream effects (usually undesirable) that those kicked off, and on and on.

So structural biology has been greatly advanced by these new tools. But it has not been outmoded, replaced, or rendered irrelevant. Its more relevant than ever, and now we can get down to even bigger questions with it.

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More Protein Folding Progress What's It Mean? | In the Pipeline - Science Magazine

Even if Sale hits those targets in a rehab start late next week, the team will monitor his recovery from his increased workload before making a decision about whether to continue his build-up or activate him in the first week of August.

We want to get him up in that 80-pitch range and then make sure he can come back and do it again five days after that, said pitching coach Dave Bush. When you activate guys after a long injury, its not just that hes ready to pitch. You want him to pitch consistently.

You have to make sure the guys can recover, they can do it effectively, come back, throw a side in a couple days, and be on the mound again in five or so days. Each of those things is part of the equation right now.

Though its premature to circle a definitive date for Sales return, the Sox are excited both about what his potential impact and the opportunity hell have to be a difference-maker in a playoff push.

We know hes going to contribute. This is not a guy thats just going to come here and get innings to get ready for next year, said Cora. Hes on a mission. He loves the fact that these guys have put this team in a situation to compete the rest of the season.

As the rotation turns

Eduardo Rodriguez, who left Fridays game in the second inning due to a migraine, showed up briefly at Fenway Park on Saturday and reported improvement before being sent home to rest. The Sox are hopeful that the lefthander can avoid the injured list and start on Thursday in their fourth and final contest against the Blue Jays.

Well see how he feels, said Cora. Hopefully everything goes well tomorrow. Thats our goal and then from there we can map [his schedule] out for the week.

Tanner Houck, who was initially slated to be available out of the bullpen against Toronto, will instead start the third game of the series to give everyone in the rotation a fifth day of rest.

Houck and Sale arent the only ones adding to the teams rotation depth down the stretch. On Friday, righthander Connor Seabold almost exactly 11 months after the trade that landed him and Nick Pivetta from the Phillies made his first appearance for a Red Sox affiliate.

On the surface, it did not go particularly well. Pitching for Triple-A Worcester against many of his former minor league teammates with Philadelphias Triple-A affiliate in Lehigh Valley, Seabold allowed six runs (three earned) on three hits and four walks in 3 innings. But he threw all four of his pitches (four-seamer, changeup, slider, curve) and emerged healthy.

It was a huge step in the right direction for us, said Red Sox farm director Brian Abraham.

Draftees signed

The Red Sox announced the signings of 11 draftees, most notably righthander Elmer Rodriguez, a fourth-rounder taken out of high school in Puerto Rico. The team also announced the signings of pitchers Wyatt Olds (7th round), Hunter Dobbins (8th), Matt Litwicki (10th), Christopher Troye (12th), Jacob Webb (14th), and Tyler Uberstine (19th); utility player Daniel McElveny (6th); third baseman Tyler Miller (9th); second baseman B.J. Vela (16th); and outfielder Phillip Sikes (18th). That group joins first-rounder Marcelo Mayer and third-rounder Tyler McDonough as Sox signees . . . The most prominent unsigned player is second-rounder Jud Fabian. Fabian, 20, entered the year expected to go in the early- to mid-first round but slid due to early-season struggles. However, he had a strong finish to the year and is expected to seek a bonus above the MLB-recommended slot value of $1.856 million for the No. 40 overall pick in order to sign . . . The team also announced the signings of undrafted free agents Kier Meredith (Clemson) and righthander Jhonny Felix (Western Oklahoma State College). Felix attended Brighton High School . . . Rehabbing Yankees righthander Luis Severino threw a simulated game against Yankees teammates on Saturday afternoon. Among them: Gio Urshela, who could be activated from the COVID-19-related injured list on Sunday.

Alex Speier can be reached at alex.speier@globe.com. Follow him on Twitter at @alexspeier.

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Chris Sale continues to make progress, but the Red Sox still taking a cautious approach - The Boston Globe

BruinsWith eight goals and six assists in 16 games, Taylor Hall has had a lot to get excited about since joining the Bruins.

By Kevin Paul Dupont, The Boston Globe

Don Sweeney, who generally plays his cards so close to his vest that even his jokers wear frowns, said Thursday morning that significant progress has been made in re-signing left wing Taylor Hall.

So I hope that we will find a finish line, the Bruins general manager said during a 15-minute Zoom session ahead of this weekends NHL Draft (Round 1 Friday night). Looking forward to hopefully having him back as a big part of what were trying to do this year and moving forward made significant progress there.

A number of media outlets reported Wednesday, amid the buzz of the Seattle expansion draft, that Hall, an unrestricted free agent, was close to agreeing with the Bruins on a four-year contract extension carrying a $6 million cap hit.

Sweeneys optimistic characterization of negotiations all but makes it a lock that Hall, approaching his 30th birthday, will return. The cap figure would slot him behind fellow forwards Patrice Bergeron ($6.875 million), David Pastrnak (6.667 million), and Brad Marchand ($6.125 million).

Hall, who last offseason signed a one-year UFA deal with Buffalo for $8 million, in 2012 signed a seven-year, $42 million deal in Edmonton that carried the same $6 million-a-year cap hit. He has since played for the Devils, Sabres, and Bruins, joining the Black and Gold in April at the trading deadline and fitting in nicely at David Krejcis left wing on the clubs No. 2 line.

Meanwhile, Sweeney had his cards tucked tightly regarding Krejci, believed to be weighing a decision whether to continue his NHL career or pack up his family for a return to his native Czech Republic.

There remains a third option for Krejci, to test the free agent market when it opens Wednesday (noon Eastern time), but Krejci, 35, weeks ago did not sound inclined to play anywhere but in Boston if he chooses to continue his NHL career.

There is no reason to doubt Krejcis sentiments, but with the free agency period soon at hand, he could be enticed at least to hear what the leagues 31 other potential bidders might offer him. Their bids, if any, could influence what he would ask to return for his 15th season as a Bruin.

The Kraken, who called Bruins defenseman Jeremy Lauzons name first in the Wednesday night draft, came up notably shallow at center in the selection process. They could just be one of the bidders if Krejci remains unsigned.

At this point in time, he has not given firm indication as he referenced before, hes got some things that he wants to address, said Sweeney. Then hell let us know. But I have been in regular communication with David and there is no timeline to make decisions.

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Bruins have made significant progress in re-signing Taylor Hall, according to GM Don Sweeney - Boston.com