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Thermodynamics of spontaneous protein folding: role of …

Posted on October 8, 2019 by Prof Baldwin

Summary

Free energy change in individual transformations

It is standard practice in biochemistry to consider the Gibbs Free Energy of transformation of the sort A B in isolation in determining whether it will proceed spontaneously. A chemical reaction for which G is negative may generate heat (i.e. have a negative enthalpy change (H) ) which affects its aqueous surroundings, but it seems justified to consider the reaction in isolation as there is no sense that the change in the vibration of the water molecules is driving or coupled to the reaction.

This approach has been applied to the structural change of protein folding with the conclusion (consistent with the first explanation) that the change in enthalpy (H) is sufficient to produce a negative G and hence drive protein folding (Citation 1, below).

Free energy change in coupled transformationsMany biochemical changes involve transformations which individually have a positive free energy change, but are made possible by coupling to another reaction with negative free energy change, of greater magnitude:

A B , G1 = +x

C D , G2 = y

If y>x and these two reactions are coupled (generally through a complex reaction path on an enzyme) , then we have:

A + C B + D , Goverall = ve

Proteopathy – Wikipedia

Posted on October 1, 2019 by Prof Baldwin

In medicine, proteopathy (Proteo- [pref. protein]; -pathy [suff. disease]; proteopathies pl.; proteopathic adj.) refers to a class of diseases in which certain proteins become structurally abnormal, and thereby disrupt the function of cells, tissues and organs of the body.[1][2] Often the proteins fail to fold into their normal configuration; in this misfolded state, the proteins can become toxic in some way (a gain of toxic function) or they can lose their normal function.[3] The proteopathies (also known as proteinopathies, protein conformational disorders, or protein misfolding diseases) include such diseases as CreutzfeldtJakob disease and other prion diseases, Alzheimer's disease, Parkinson's disease, amyloidosis, Multiple System Atrophy, and a wide range of other disorders (see List of Proteopathies).[2][4][5][6][7][8]

The concept of proteopathy can trace its origins to the mid-19th century, when, in 1854, Rudolf Virchow coined the term amyloid ("starch-like") to describe a substance in cerebral corpora amylacea that exhibited a chemical reaction resembling that of cellulose. In 1859, Friedreich and Kekul demonstrated that, rather than consisting of cellulose, "amyloid" actually is rich in protein.[9] Subsequent research has shown that many different proteins can form amyloid, and that all amyloids have in common birefringence in cross-polarized light after staining with the dye Congo Red, as well as a fibrillar ultrastructure when viewed with an electron microscope.[9] However, some proteinaceous lesions lack birefringence and contain few or no classical amyloid fibrils, such as the diffuse deposits of A protein in the brains of Alzheimer patients.[10] Furthermore, evidence has emerged that small, non-fibrillar protein aggregates known as oligomers are toxic to the cells of an affected organ, and that amyloidogenic proteins in their fibrillar form may be relatively benign.[11][12]

In most, if not all proteopathies, a change in 3-dimensional folding (conformation) increases the tendency of a specific protein to bind to itself.[5] In this aggregated form, the protein is resistant to clearance and can interfere with the normal capacity of the affected organs. In some cases, misfolding of the protein results in a loss of its usual function. For example, cystic fibrosis is caused by a defective cystic fibrosis transmembrane conductance regulator (CFTR) protein,[3] and in amyotrophic lateral sclerosis / frontotemporal lobar degeneration (FTLD), certain gene-regulating proteins inappropriately aggregate in the cytoplasm, and thus are unable to perform their normal tasks within the nucleus.[13][14] Because proteins share a common structural feature known as the polypeptide backbone, all proteins have the potential to misfold under some circumstances.[15] However, only a relatively small number of proteins are linked to proteopathic disorders, possibly due to structural idiosyncrasies of the vulnerable proteins. For example, proteins that are normally unfolded or relatively unstable as monomers (that is, as single, unbound protein molecules) are more likely to misfold into an abnormal conformation.[5][15][16] In nearly all instances, the disease-causing molecular configuration involves an increase in beta-sheet secondary structure of the protein.[5][15][17][18] The abnormal proteins in some proteopathies have been shown to fold into multiple 3-dimensional shapes; these variant, proteinaceous structures are defined by their different pathogenic, biochemical, and conformational properties.[19] They have been most thoroughly studied with regard to prion disease, and are referred to as protein strains.[20][21]

The likelihood that proteopathy will develop is increased by certain risk factors that promote the self-assembly of a protein. These include destabilizing changes in the primary amino acid sequence of the protein, post-translational modifications (such as hyperphosphorylation), changes in temperature or pH, an increase in production of a protein, or a decrease in its clearance.[1][5][15] Advancing age is a strong risk factor,[1] as is traumatic brain injury.[22][23] In the aging brain, multiple proteopathies can overlap.[24] For example, in addition to tauopathy and A-amyloidosis (which coexist as key pathologic features of Alzheimer's disease), many Alzheimer patients have concomitant synucleinopathy (Lewy bodies) in the brain.[25]

It is hypothesized that chaperones and co-chaperones (proteins that assist protein folding) may antagonize proteotoxicity during aging and in protein misfolding-diseases to maintain proteostasis.[26][27][28]

Some proteins can be induced to form abnormal assemblies by exposure to the same (or similar) protein that has folded into a disease-causing conformation, a process called 'seeding' or 'permissive templating'.[29][30] In this way, the disease state can be brought about in a susceptible host by the introduction of diseased tissue extract from an afflicted donor. The best known form of such inducible proteopathy is prion disease,[31] which can be transmitted by exposure of a host organism to purified prion protein in a disease-causing conformation.[32][33] There is now evidence that other proteopathies can be induced by a similar mechanism, including A amyloidosis, amyloid A (AA) amyloidosis, and apolipoprotein AII amyloidosis,[30][34] tauopathy,[35] synucleinopathy,[36][37][38][39] and the aggregation of superoxide dismutase-1 (SOD1),[40][41] polyglutamine,[42][43] and TAR DNA-binding protein-43 (TDP-43).[44]

In all of these instances, an aberrant form of the protein itself appears to be the pathogenic agent. In some cases, the deposition of one type of protein can be experimentally induced by aggregated assemblies of other proteins that are rich in -sheet structure, possibly because of structural complementarity of the protein molecules. For example, AA amyloidosis can be stimulated in mice by such diverse macromolecules as silk, the yeast amyloid Sup35, and curli fibrils from the bacterium Escherichia coli.[45] In addition, apolipoprotein AII amyloid can be induced in mice by a variety of -sheet rich amyloid fibrils,[46] and cerebral tauopathy can be induced by brain extracts that are rich in aggregated A.[47] There is also experimental evidence for cross-seeding between prion protein and A.[48] In general, such heterologous seeding is less efficient than is seeding by a corrupted form of the same protein.

The development of effective treatments for many proteopathies has been challenging.[73][74] Because the proteopathies often involve different proteins arising from different sources, treatment strategies must be customized to each disorder; however, general therapeutic approaches include maintaining the function of affected organs, reducing the formation of the disease-causing proteins, preventing the proteins from misfolding and/or aggregating, or promoting their removal.[75][73][76] For example, in Alzheimer's disease, researchers are seeking ways to reduce the production of the disease-associated protein A by inhibiting the enzymes that free it from its parent protein.[74] Another strategy is to use antibodies to neutralize specific proteins by active or passive immunization.[77] In some proteopathies, inhibiting the toxic effects of protein oligomers might be beneficial.[78] Amyloid A (AA) amyloidosis can be reduced by treating the inflammatory state that increases the amount of the protein in the blood (referred to as serum amyloid A, or SAA).[73] In immunoglobulin light chain amyloidosis (AL amyloidosis), chemotherapy can be used to lower the number of the blood cells that make the light chain protein that forms amyloid in various bodily organs.[79] Transthyretin (TTR) amyloidosis (ATTR) results from the deposition of misfolded TTR in multiple organs.[80] Because TTR is mainly produced in the liver, TTR amyloidosis can be slowed in some hereditary cases by liver transplantation.[81] TTR amyloidosis also can be treated by stabilizing the normal assemblies of the protein (called tetramers because they consist of four TTR molecules bound together). Stabilization prevents individual TTR molecules from escaping, misfolding, and aggregating into amyloid.[82][83]

Several other treatment strategies for proteopathies are being investigated, including small molecules and biologic medicines such as small interfering RNAs, antisense oligonucleotides, peptides, and engineered immune cells.[82][79][84][85] In some cases, multiple therapeutic agents may be combined to improve effectiveness.[79][86]

Micrograph of tauopathy (brown) in a neuronal cell body (arrow) and process (arrowhead) in the cerebral cortex of a patient with Alzheimer's disease. Bar = 25 microns (0.025mm).

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Proteopathy - Wikipedia

Folding@home – Wikipedia

Posted on October 1, 2019 by Prof Baldwin

Distributed computing project simulating protein folding

Folding@home (FAH or F@h) is a distributed computing project for disease research that simulates protein folding, computational drug design, and other types of molecular dynamics. The project uses the idle processing resources of thousands of personal computers owned by volunteers who have installed the software on their systems. Its main purpose is to determine the mechanisms of protein folding, which is the process by which proteins reach their final three-dimensional structure, and to examine the causes of protein misfolding. This is of significant academic interest with major implications for medical research into Alzheimer's disease, Huntington's disease, and many forms of cancer, among other diseases. To a lesser extent, Folding@home also tries to predict a protein's final structure and determine how other molecules may interact with it, which has applications in drug design. Folding@home is developed and operated by the Pande Laboratory at Stanford University, under the direction of Prof. Vijay Pande, and is shared by various scientific institutions and research laboratories across the world.[4]

The project has pioneered the use of graphics processing units (GPUs), PlayStation3s, Message Passing Interface (used for computing on multi-core processors), and some Sony Xperia smartphones for distributed computing and scientific research. The project uses statistical simulation methodology that is a paradigm shift from traditional computing methods.[5] As part of the clientserver model network architecture, the volunteered machines each receive pieces of a simulation (work units), complete them, and return them to the project's database servers, where the units are compiled into an overall simulation. Volunteers can track their contributions on the Folding@home website, which makes volunteers' participation competitive and encourages long-term involvement.

Folding@home is one of the world's fastest computing systems, with a speed of approximately 98.7petaFLOPS[6] as of June 2019[update]. This performance from its large-scale computing network has allowed researchers to run computationally costly atomic-level simulations of protein folding thousands of times longer than formerly achieved. Since its launch on 1Oct2000, the Pande Lab has produced 212 scientific research papers as a direct result of Folding@home.[7] Results from the project's simulations agree well with experiments.[8][9][10]

Proteins are an essential component to many biological functions and participate in virtually all processes within biological cells. They often act as enzymes, performing biochemical reactions including cell signaling, molecular transportation, and cellular regulation. As structural elements, some proteins act as a type of skeleton for cells, and as antibodies, while other proteins participate in the immune system. Before a protein can take on these roles, it must fold into a functional three-dimensional structure, a process that often occurs spontaneously and is dependent on interactions within its amino acid sequence and interactions of the amino acids with their surroundings. Protein folding is driven by the search to find the most energetically favorable conformation of the protein, i.e., its native state. Thus, understanding protein folding is critical to understanding what a protein does and how it works, and is considered a holy grail of computational biology.[11][12] Despite folding occurring within a crowded cellular environment, it typically proceeds smoothly. However, due to a protein's chemical properties or other factors, proteins may misfold, that is, fold down the wrong pathway and end up misshapen. Unless cellular mechanisms can destroy or refold misfolded proteins, they can subsequently aggregate and cause a variety of debilitating diseases.[13] Laboratory experiments studying these processes can be limited in scope and atomic detail, leading scientists to use physics-based computing models that, when complementing experiments, seek to provide a more complete picture of protein folding, misfolding, and aggregation.[14][15]

Due to the complexity of proteins' conformation or configuration space (the set of possible shapes a protein can take), and limits in computing power, all-atom molecular dynamics simulations have been severely limited in the timescales which they can study. While most proteins typically fold in the order of milliseconds,[14][16] before 2010, simulations could only reach nanosecond to microsecond timescales.[8] General-purpose supercomputers have been used to simulate protein folding, but such systems are intrinsically costly and typically shared among many research groups. Further, because the computations in kinetic models occur serially, strong scaling of traditional molecular simulations to these architectures is exceptionally difficult.[17][18] Moreover, as protein folding is a stochastic process and can statistically vary over time, it is challenging computationally to use long simulations for comprehensive views of the folding process.[19][20]

Protein folding does not occur in one step.[13] Instead, proteins spend most of their folding time, nearly 96% in some cases,[21] waiting in various intermediate conformational states, each a local thermodynamic free energy minimum in the protein's energy landscape. Through a process known as adaptive sampling, these conformations are used by Folding@home as starting points for a set of simulation trajectories. As the simulations discover more conformations, the trajectories are restarted from them, and a Markov state model (MSM) is gradually created from this cyclic process. MSMs are discrete-time master equation models which describe a biomolecule's conformational and energy landscape as a set of distinct structures and the short transitions between them. The adaptive sampling Markov state model method significantly increases the efficiency of simulation as it avoids computation inside the local energy minimum itself, and is amenable to distributed computing (including on GPUGRID) as it allows for the statistical aggregation of short, independent simulation trajectories.[22] The amount of time it takes to construct a Markov state model is inversely proportional to the number of parallel simulations run, i.e., the number of processors available. In other words, it achieves linear parallelization, leading to an approximately four orders of magnitude reduction in overall serial calculation time. A completed MSM may contain tens of thousands of sample states from the protein's phase space (all the conformations a protein can take on) and the transitions between them. The model illustrates folding events and pathways (i.e., routes) and researchers can later use kinetic clustering to view a coarse-grained representation of the otherwise highly detailed model. They can use these MSMs to reveal how proteins misfold and to quantitatively compare simulations with experiments.[5][19][23]

Between 2000 and 2010, the length of the proteins Folding@home has studied have increased by a factor of four, while its timescales for protein folding simulations have increased by six orders of magnitude.[24] In 2002, Folding@home used Markov state models to complete approximately a million CPU days of simulations over the span of several months,[10] and in 2011, MSMs parallelized another simulation that required an aggregate 10million CPU hours of computing.[25] In January 2010, Folding@home used MSMs to simulate the dynamics of the slow-folding 32-residue NTL9 protein out to 1.52milliseconds, a timescale consistent with experimental folding rate predictions but a thousand times longer than formerly achieved. The model consisted of many individual trajectories, each two orders of magnitude shorter, and provided an unprecedented level of detail into the protein's energy landscape.[5][8][26] In 2010, Folding@home researcher Gregory Bowman was awarded the Thomas Kuhn Paradigm Shift Award from the American Chemical Society for the development of the open-source MSMBuilder software and for attaining quantitative agreement between theory and experiment.[27][28] For his work, Pande was awarded the 2012 Michael and Kate Brny Award for Young Investigators for "developing field-defining and field-changing computational methods to produce leading theoretical models for protein and RNA folding",[29] and the 2006 Irving Sigal Young Investigator Award for his simulation results which "have stimulated a re-examination of the meaning of both ensemble and single-molecule measurements, making Dr. Pande's efforts pioneering contributions to simulation methodology."[30]

Protein misfolding can result in a variety of diseases including Alzheimer's disease, cancer, CreutzfeldtJakob disease, cystic fibrosis, Huntington's disease, sickle-cell anemia, and typeII diabetes.[13][31][32] Cellular infection by viruses such as HIV and influenza also involve folding events on cell membranes.[33] Once protein misfolding is better understood, therapies can be developed that augment cells' natural ability to regulate protein folding. Such therapies include the use of engineered molecules to alter the production of a given protein, help destroy a misfolded protein, or assist in the folding process.[34] The combination of computational molecular modeling and experimental analysis has the possibility to fundamentally shape the future of molecular medicine and the rational design of therapeutics,[15] such as expediting and lowering the costs of drug discovery.[35] The goal of the first five years of Folding@home was to make advances in understanding folding, while the current goal is to understand misfolding and related disease, especially Alzheimer's.[36]

The simulations run on Folding@home are used in conjunction with laboratory experiments,[19] but researchers can use them to study how folding in vitro differs from folding in native cellular environments. This is advantageous in studying aspects of folding, misfolding, and their relationships to disease that are difficult to observe experimentally. For example, in 2011, Folding@home simulated protein folding inside a ribosomal exit tunnel, to help scientists better understand how natural confinement and crowding might influence the folding process.[37][38] Furthermore, scientists typically employ chemical denaturants to unfold proteins from their stable native state. It is not generally known how the denaturant affects the protein's refolding, and it is difficult to experimentally determine if these denatured states contain residual structures which may influence folding behavior. In 2010, Folding@home used GPUs to simulate the unfolded states of ProteinL, and predicted its collapse rate in strong agreement with experimental results.[39]

The Pande Lab is part of Stanford University, a non-profit entity, and does not sell the results generated by Folding@home.[40] The large data sets from the project are freely available for other researchers to use upon request and some can be accessed from the Folding@home website.[41][42] The Pande lab has collaborated with other molecular dynamics systems such as the Blue Gene supercomputer,[43] and they share Folding@home's key software with other researchers, so that the algorithms which benefited Folding@home may aid other scientific areas.[41] In 2011, they released the open-source Copernicus software, which is based on Folding@home's MSM and other parallelizing methods and aims to improve the efficiency and scaling of molecular simulations on large computer clusters or supercomputers.[44][45] Summaries of all scientific findings from Folding@home are posted on the Folding@home website after publication.[7]

Alzheimer's disease is linked to the aggregation of amyloid beta protein fragments in the brain (right). Researchers have used Folding@home to simulate this aggregation process, to better understand the cause of the disease.

Alzheimer's disease is an incurable neurodegenerative disease which most often affects the elderly and accounts for more than half of all cases of dementia. Its exact cause remains unknown, but the disease is identified as a protein misfolding disease. Alzheimer's is associated with toxic aggregations of the amyloid beta (A) peptide, caused by A misfolding and clumping together with other A peptides. These A aggregates then grow into significantly larger senile plaques, a pathological marker of Alzheimer's disease.[46][47][48] Due to the heterogeneous nature of these aggregates, experimental methods such as X-ray crystallography and nuclear magnetic resonance (NMR) have had difficulty characterizing their structures. Moreover, atomic simulations of A aggregation are highly demanding computationally due to their size and complexity.[49][50]

Preventing A aggregation is a promising method to developing therapeutic drugs for Alzheimer's disease, according to Drs. Naeem and Fazili in a literature review article.[51] In 2008, Folding@home simulated the dynamics of A aggregation in atomic detail over timescales of the order of tens of seconds. Prior studies were only able to simulate about 10 microseconds. Folding@home was able to simulate A folding for six orders of magnitude longer than formerly possible. Researchers used the results of this study to identify a beta hairpin that was a major source of molecular interactions within the structure.[52] The study helped prepare the Pande lab for future aggregation studies and for further research to find a small peptide which may stabilize the aggregation process.[49]

In December 2008, Folding@home found several small drug candidates which appear to inhibit the toxicity of A aggregates.[53] In 2010, in close cooperation with the Center for Protein Folding Machinery, these drug leads began to be tested on biological tissue.[32] In 2011, Folding@home completed simulations of several mutations of A that appear to stabilize the aggregate formation, which could aid in the development of therapeutic drug therapies for the disease and greatly assist with experimental nuclear magnetic resonance spectroscopy studies of A oligomers.[50][54] Later that year, Folding@home began simulations of various A fragments to determine how various natural enzymes affect the structure and folding of A.[55][56]

Huntington's disease is a neurodegenerative genetic disorder that is associated with protein misfolding and aggregation. Excessive repeats of the glutamine amino acid at the N-terminus of the Huntingtin protein cause aggregation, and although the behavior of the repeats is not completely understood, it does lead to the cognitive decline associated with the disease.[57] As with other aggregates, there is difficulty in experimentally determining its structure.[58] Scientists are using Folding@home to study the structure of the Huntingtin protein aggregate and to predict how it forms, assisting with rational drug design methods to stop the aggregate formation.[32] The N17 fragment of the Huntington protein accelerates this aggregation, and while there have been several mechanisms proposed, its exact role in this process remains largely unknown.[59] Folding@home has simulated this and other fragments to clarify their roles in the disease.[60] Since 2008, its drug design methods for Alzheimer's disease have been applied to Huntington's.[32]

More than half of all known cancers involve mutations of p53, a tumor suppressor protein present in every cell which regulates the cell cycle and signals for cell death in the event of damage to DNA. Specific mutations in p53 can disrupt these functions, allowing an abnormal cell to continue growing unchecked, resulting in the development of tumors. Analysis of these mutations helps explain the root causes of p53-related cancers.[61] In 2004, Folding@home was used to perform the first molecular dynamics study of the refolding of p53's protein dimer in an all-atom simulation of water. The simulation's results agreed with experimental observations and gave insights into the refolding of the dimer that were formerly unobtainable.[62] This was the first peer reviewed publication on cancer from a distributed computing project.[63] The following year, Folding@home powered a new method to identify the amino acids crucial for the stability of a given protein, which was then used to study mutations of p53. The method was reasonably successful in identifying cancer-promoting mutations and determined the effects of specific mutations which could not otherwise be measured experimentally.[64]

Folding@home is also used to study protein chaperones,[32] heat shock proteins which play essential roles in cell survival by assisting with the folding of other proteins in the crowded and chemically stressful environment within a cell. Rapidly growing cancer cells rely on specific chaperones, and some chaperones play key roles in chemotherapy resistance. Inhibitions to these specific chaperones are seen as potential modes of action for efficient chemotherapy drugs or for reducing the spread of cancer.[65] Using Folding@home and working closely with the Center for Protein Folding Machinery, the Pande lab hopes to find a drug which inhibits those chaperones involved in cancerous cells.[66] Researchers are also using Folding@home to study other molecules related to cancer, such as the enzyme Src kinase, and some forms of the engrailed homeodomain: a large protein which may be involved in many diseases, including cancer.[67][68] In 2011, Folding@home began simulations of the dynamics of the small knottin protein EETI, which can identify carcinomas in imaging scans by binding to surface receptors of cancer cells.[69][70]

Interleukin 2 (IL-2) is a protein that helps T cells of the immune system attack pathogens and tumors. However, its use as a cancer treatment is restricted due to serious side effects such as pulmonary edema. IL-2 binds to these pulmonary cells differently than it does to T cells, so IL-2 research involves understanding the differences between these binding mechanisms. In 2012, Folding@home assisted with the discovery of a mutant form of IL-2 which is three hundred times more effective in its immune system role but carries fewer side effects. In experiments, this altered form significantly outperformed natural IL-2 in impeding tumor growth. Pharmaceutical companies have expressed interest in the mutant molecule, and the National Institutes of Health are testing it against a large variety of tumor models to try to accelerate its development as a therapeutic.[71][72]

Osteogenesis imperfecta, known as brittle bone disease, is an incurable genetic bone disorder which can be lethal. Those with the disease are unable to make functional connective bone tissue. This is most commonly due to a mutation in Type-I collagen,[73] which fulfills a variety of structural roles and is the most abundant protein in mammals.[74] The mutation causes a deformation in collagen's triple helix structure, which if not naturally destroyed, leads to abnormal and weakened bone tissue.[75] In 2005, Folding@home tested a new quantum mechanical method that improved upon prior simulation methods, and which may be useful for future computing studies of collagen.[76] Although researchers have used Folding@home to study collagen folding and misfolding, the interest stands as a pilot project compared to Alzheimer's and Huntington's research.[32]

Folding@home is assisting in research towards preventing some viruses, such as influenza and HIV, from recognizing and entering biological cells.[32] In 2011, Folding@home began simulations of the dynamics of the enzyme RNase H, a key component of HIV, to try to design drugs to deactivate it.[77] Folding@home has also been used to study membrane fusion, an essential event for viral infection and a wide range of biological functions. This fusion involves conformational changes of viral fusion proteins and protein docking,[33] but the exact molecular mechanisms behind fusion remain largely unknown.[78] Fusion events may consist of over a half million atoms interacting for hundreds of microseconds. This complexity limits typical computer simulations to about ten thousand atoms over tens of nanoseconds: a difference of several orders of magnitude.[52] The development of models to predict the mechanisms of membrane fusion will assist in the scientific understanding of how to target the process with antiviral drugs.[79] In 2006, scientists applied Markov state models and the Folding@home network to discover two pathways for fusion and gain other mechanistic insights.[52]

Following detailed simulations from Folding@home of small cells known as vesicles, in 2007, the Pande lab introduced a new computing method to measure the topology of its structural changes during fusion.[80] In 2009, researchers used Folding@home to study mutations of influenza hemagglutinin, a protein that attaches a virus to its host cell and assists with viral entry. Mutations to hemagglutinin affect how well the protein binds to a host's cell surface receptor molecules, which determines how infective the virus strain is to the host organism. Knowledge of the effects of hemagglutinin mutations assists in the development of antiviral drugs.[81][82] As of 2012, Folding@home continues to simulate the folding and interactions of hemagglutinin, complementing experimental studies at the University of Virginia.[32][83]

Drugs function by binding to specific locations on target molecules and causing some desired change, such as disabling a target or causing a conformational change. Ideally, a drug should act very specifically, and bind only to its target without interfering with other biological functions. However, it is difficult to precisely determine where and how tightly two molecules will bind. Due to limits in computing power, current in silico methods usually must trade speed for accuracy; e.g., use rapid protein docking methods instead of computationally costly free energy calculations. Folding@home's computing performance allows researchers to use both methods, and evaluate their efficiency and reliability.[36][84][85] Computer-assisted drug design has the potential to expedite and lower the costs of drug discovery.[35] In 2010, Folding@home used MSMs and free energy calculations to predict the native state of the villin protein to within 1.8 angstrom () root mean square deviation (RMSD) from the crystalline structure experimentally determined through X-ray crystallography. This accuracy has implications to future protein structure prediction methods, including for intrinsically unstructured proteins.[52] Scientists have used Folding@home to research drug resistance by studying vancomycin, an antibiotic drug of last resort, and beta-lactamase, a protein that can break down antibiotics like penicillin.[86][87]

Chemical activity occurs along a protein's active site. Traditional drug design methods involve tightly binding to this site and blocking its activity, under the assumption that the target protein exists in one rigid structure. However, this approach works for approximately only 15% of all proteins. Proteins contain allosteric sites which, when bound to by small molecules, can alter a protein's conformation and ultimately affect the protein's activity. These sites are attractive drug targets, but locating them is very computationally costly. In 2012, Folding@home and MSMs were used to identify allosteric sites in three medically relevant proteins: beta-lactamase, interleukin-2, and RNase H.[87][88]

Approximately half of all known antibiotics interfere with the workings of a bacteria's ribosome, a large and complex biochemical machine that performs protein biosynthesis by translating messenger RNA into proteins. Macrolide antibiotics clog the ribosome's exit tunnel, preventing synthesis of essential bacterial proteins. In 2007, the Pande lab received a grant to study and design new antibiotics.[32] In 2008, they used Folding@home to study the interior of this tunnel and how specific molecules may affect it.[89] The full structure of the ribosome was determined only as of 2011, and Folding@home has also simulated ribosomal proteins, as many of their functions remain largely unknown.[90]

There are many more protein misfolding promoted diseases that can be benefited from Folding@home to either discern the misfolded protein structure or the misfolding kinetics, and assist in drug design in the future. The often fatal prion diseases is among the most significant.

Prion (PrP) is a transmembrane cellular protein found widely in eukaryotic cells. In mammals, it is more abundant in the central nervous system. Although its function is unknown, its high conservation among species indicates an important role in the cellular function. The conformational change from the normal prion protein (PrPc, stands for cellular) to the disease causing isoform PrPSc (stands for prototypical prion diseasescrapie) causes a host of diseases collectly known as transmissible spongiform encephalopathies (TSEs), including Bovine spongiform encephalopathy (BSE) in bovine, Creutzfeldt-Jakob disease (CJD) and fatal insomnia in human, chronic wasting disease (CWD) in the deer family. The conformational change is widely accepted as the result of protein misfolding. What distinguishes TSEs from other protein misfolding diseases is its transmissible nature. The seeding of the infectious PrPSc, either arising spontaneously, hereditary or acquired via exposure to contaminated tissues,[91] can cause a chain reaction of transforming normal PrPc into fibrils aggregates or amyloid like plaques consist of PrPSc.[92]

The molecular structure of PrPSc has not been fully characterized due to its aggregated nature. Neither is known much about the mechanism of the protein misfolding nor its kinetics. Using the known structure of PrPc and the results of the in vitro and in vivo studies described below, Folding@home could be valuable in elucidating how PrPSc is formed and how the infectious protein arrange themselves to form fibrils and amyloid like plaques, bypassing the requirement to purify PrPSc or dissolve the aggregates.

The PrPc has been enzymatically dissociated from the membrane and purified, its structure studied using structure characterization techniques such as NMR spectroscopy and X-ray crystallography. Post-translational PrPc has 231 amino acids (aa) in murine. The molecule consists of a long and unstructured amino terminal region spanning up to aa residue 121 and a structured carboxy terminal domain.[92] This globular domain harbours two short sheet-forming anti-parallel -strands (aa 128 to 130 and aa 160 to 162 in murine PrPc) and three -helices (helix I: aa 143 to 153; helix II: aa 171 to 192; helix III: aa 199 to 226 in murine PrPc),[93] Helices II and III are anti-parallel orientated and connected by a short loop. Their structural stability is supported by a disulfide bridge, which is parallel to both sheet-forming -strands. These -helices and the -sheet form the rigid core of the globular domain of PrPc.[94]

The disease causing PrPSc is proteinase K resistant and insoluble. Attempts to purify it from the brains of infected animals invariably yield heterogeneous mixtures and aggregated states that are not amenable to characterization by NMR spectroscopy or X-ray crystallography. However, it is a general consensus that PrPSc contains a high percentage of tightly stacked -sheets than the normal PrPc that renders the protein insoluble and resistant to proteinase. Using techniques of cryoelectron microscopy and structural modeling based on similar common protein structures, it has been discovered that PrPSc contains -sheets in the region of aa 81-95 to aa 171, while the carboxy terminal structure is supposedly preserved, retaining the disulfide-linked -helical conformation in the normal PrPc. These -sheets form a parallel left-handed beta-helix.[92] Three PrPSc molecules are believed to form a primary unit and therefore build the basis for the so-called scrapie-associated fibrils.[95] The catalytic activity depends on the size of the particle. PrPSc particles which consist of only 14-28 PrPc molecules exhibit the highest rate of infectivity and conversion.[96]

Despite the difficulty to purify and characterize PrPSc, from the known molecular structure of PrPc and using transgenic mice and N-terminal deletion,[97] the potential hot spots of protein misfolding leading to the pathogenic PrPSc could be deduced and Folding@home could be of great value in confirming these. Studies found that both the primary and secondary structure of the prion protein can be of significance of the conversion.

There are more than twenty mutations of the prion protein gene (PRNP) that are known to be associated with or that are directly linked to the hereditary form of human TSEs [56], indicating single amino acids at certain position, likely within the carboxy domain,[93] of the PrPc can affect the susceptibility to TSEs.

The post-translational amino terminal region of PrPc consists of residues 23-120 which make up nearly half of the amino sequence of full-length matured PrPc. There are two sections in the amino terminal region that may influence conversion. First, residues 52-90 contains an octapeptide repeat (5 times) region that likely influences the initial binding (via the octapeptide repeats) and also the actual conversion via the second section of aa 108-124.[98] The highly hydrophobic AGAAAAGA is located between aa residue 113 and 120 and is described as putative aggregation site,[99] although this sequence requires its flanking parts to form fibrillar aggregates.[100]

In the carboxy globular domain,[94] among the three helices, study show that helix II has a significant higher propensity to -strand conformation.[101] Due to the high conformational flexvoribility seen between residues 114-125 (part of the unstructured N-terminus chain) and the high -strand propensity of helix II, only moderate changes in the environmental conditions or interactions might be sufficient to induce misfolding of PrPc and subsequent fibril formation.[92]

Other studies of NMR structures of PrPc showed that these residues (~108189) contain most of the folded domain including both -strands, the first two -helices, and the loop/turn regions connecting them, but not the helix III.[97] Small changes within the loop/turn structures of PrPc itself could be important in the conversion as well.[102] In another study, Riek et al. showed that the two small regions of -strand upstream of the loop regions act as a nucleation site for the conformational conversion of the loop/turn and -helical structures in PrPc to -sheet.[93]

The energy threshold for the conversion are not necessarily high. The folding stability, i.e. the free energy of a globular protein in its environment is in the range of one or two hydrogen bonds thus allows the transition to an isoform without the requirement of high transition energy.[92]

From the respective of the interactions among the PrPc molecules, hydrophobic interactions play a crucial role in the formation of -sheets, a hallmark of PrPSc, as the sheets bring fragments of polypeptide chains into close proximity.[103] Indeed, Kutznetsov and Rackovsky [104] showed that disease-promoting mutations in the human PrPc had a statistically significant tendency towards increasing local hydrophobicity.

In vitro experiments showed the kinetics of misfolding has an initial lag phase followed by a rapid growth phase of fibril formation.[105] It is likely that PrPc goes through some intermediate states, such as at least partially unfolded or degraded, before finally ending up as part of an amyloid fibril.[92]

This section needs to be updated. Please update this article to reflect recent events or newly available information. (June 2016)

Like other distributed computing projects, Folding@home is an online citizen science project. In these projects non-specialists contribute computer processing power or help to analyse data produced by professional scientists. Participants in these projects play an invaluable role in facilitating research for little or no obvious reward.

Research has been carried out into the motivations of citizen scientists and most of these studies have found that participants are motivated to take part because of altruistic reasons, that is, they want to help scientists and make a contribution to the advancement of their research.[106][107][108][109] Many participants in citizen science have an underlying interest in the topic of the research and gravitate towards projects that are in disciplines of interest to them. Folding@home is no different in that respect.[110] Research carried out recently on over 400 active participants revealed that they wanted to help make a contribution to research and that many had friends or relatives affected by the diseases that the Folding@home scientists investigate.

Folding@home attracts participants who are computer hardware enthusiasts (sometimes called overclockers). These groups bring considerable expertise to the project and are able to build computers with advanced processing power.[111] Other distributed computing projects attract these types of participants and projects are often used to benchmark the performance of modified computers, and this aspect of the hobby is accommodated through the competitive nature of the project. Individuals and teams can compete to see who can process the most computer processing units (CPUs).

This latest research on Folding@home involving interview and ethnographic observation of online groups showed that teams of hardware enthusiasts can sometimes work together, sharing best practice with regard to maximising processing output. Such teams can become communities of practice, with a shared language and online culture. This pattern of participation has been observed in other distributed computing projects.[112][113]

Another key observation of Folding@home participants is that many are male.[110] This has also been observed in other distributed projects. Furthermore, many participants work in computer and technology-based jobs and careers.[110][114][115]

Not all Folding@home participants are hardware enthusiasts. Many participants run the project software on unmodified machines and do take part competitively. Over 100,000 participants are involved in Folding@home. However, it is difficult to ascertain what proportion of participants are hardware enthusiasts. Although, according to the project managers, the contribution of the enthusiast community is substantially larger in terms of processing power.[116]

On September 16, 2007, due in large part to the participation of PlayStation 3 consoles, the Folding@home project officially attained a sustained performance level higher than one native petaFLOPS, becoming the first computing system of any kind to do so.[122][123] Top500's fastest supercomputer at the time was BlueGene/L, at 0.280 petaFLOPS.[124] The following year, on May 7, 2008, the project attained a sustained performance level higher than two native petaFLOPS,[125] followed by the three and four native petaFLOPS milestones on August 2008[126][127] and September 28, 2008 respectively.[128] On February 18, 2009, Folding@home achieved five native petaFLOPS,[129][130] and was the first computing project to meet these five levels.[132] In comparison, November 2008's fastest supercomputer was IBM's Roadrunner at 1.105 petaFLOPS.[133] On November 10, 2011, Folding@home's performance exceeded six native petaFLOPS with the equivalent of nearly eight x86 petaFLOPS.[123][134] In mid-May 2013, Folding@home attained over seven native petaFLOPS, with the equivalent of 14.87 x86 petaFLOPS. It then reached eight native petaFLOPS on June 21, followed by nine on September 9 of that year, with 17.9 x86 petaFLOPS.[135] On May 11, 2016 Folding@home announced that it was moving towards reaching the 100 x86 petaFLOPS mark.[136]

Similarly to other distributed computing projects, Folding@home quantitatively assesses user computing contributions to the project through a credit system.[137] All units from a given protein project have uniform base credit, which is determined by benchmarking one or more work units from that project on an official reference machine before the project is released.[137] Each user receives these base points for completing every work unit, though through the use of a passkey they can receive added bonus points for reliably and rapidly completing units which are more demanding computationally or have a greater scientific priority.[138][139] Users may also receive credit for their work by clients on multiple machines.[40] This point system attempts to align awarded credit with the value of the scientific results.[137]

Users can register their contributions under a team, which combine the points of all their members. A user can start their own team, or they can join an existing team.[140] In some cases, a team may have their own community-driven sources of help or recruitment such as an Internet forum.[141] The points can foster friendly competition between individuals and teams to compute the most for the project, which can benefit the folding community and accelerate scientific research.[137][142][143] Individual and team statistics are posted on the Folding@home website.[137]

If a user does not form a new team, or does not join an existing team, that user automatically becomes part of a "Default" team. This "Default" team has a team number of "0". Statistics are accumulated for this "Default" team as well as for specially named teams.

Folding@home software at the user's end involves three primary components: work units, cores, and a client.

A work unit is the protein data that the client is asked to process. Work units are a fraction of the simulation between the states in a Markov state model. After the work unit has been downloaded and completely processed by a volunteer's computer, it is returned to Folding@home servers, which then award the volunteer the credit points. This cycle repeats automatically.[142] All work units have associated deadlines, and if this deadline is exceeded, the user may not get credit and the unit will be automatically reissued to another participant. As protein folding occurs serially, and many work units are generated from their predecessors, this allows the overall simulation process to proceed normally if a work unit is not returned after a reasonable period of time. Due to these deadlines, the minimum system requirement for Folding@home is a Pentium3 450MHz CPU with Streaming SIMD Extensions (SSE).[40] However, work units for high-performance clients have a much shorter deadline than those for the uniprocessor client, as a major part of the scientific benefit is dependent on rapidly completing simulations.[144]

Before public release, work units go through several quality assurance steps to keep problematic ones from becoming fully available. These testing stages include internal, beta, and advanced, before a final full release across Folding@home.[145] Folding@home's work units are normally processed only once, except in the rare event that errors occur during processing. If this occurs for three different users, the unit is automatically pulled from distribution.[146][147] The Folding@home support forum can be used to differentiate between issues arising from problematic hardware and bad work units.[148]

Specialized molecular dynamics programs, referred to as "FahCores" and often abbreviated "cores", perform the calculations on the work unit as a background process. A large majority of Folding@home's cores are based on GROMACS,[142] one of the fastest and most popular molecular dynamics software packages, which largely consists of manually optimized assembly language code and hardware optimizations.[149][150] Although GROMACS is open-source software and there is a cooperative effort between the Pande lab and GROMACS developers, Folding@home uses a closed-source license to help ensure data validity.[151] Less active cores include ProtoMol and SHARPEN. Folding@home has used AMBER, CPMD, Desmond, and TINKER, but these have since been retired and are no longer in active service.[3][152][153] Some of these cores perform explicit solvation calculations in which the surrounding solvent (usually water) is modeled atom-by-atom; while others perform implicit solvation methods, where the solvent is treated as a mathematical continuum.[154][155] The core is separate from the client to enable the scientific methods to be updated automatically without requiring a client update. The cores periodically create calculation checkpoints so that if they are interrupted they can resume work from that point upon startup.[142]

A Folding@home participant installs a client program on their personal computer. The user interacts with the client, which manages the other software components in the background. Through the client, the user may pause the folding process, open an event log, check the work progress, or view personal statistics.[156] The computer clients run continuously in the background at a very low priority, using idle processing power so that normal computer use is unaffected.[40][140] The maximum CPU use can be adjusted via client settings.[156][157] The client connects to a Folding@home server and retrieves a work unit and may also download the appropriate core for the client's settings, operating system, and the underlying hardware architecture. After processing, the work unit is returned to the Folding@home servers. Computer clients are tailored to uniprocessor and multi-core processor systems, and graphics processing units. The diversity and power of each hardware architecture provides Folding@home with the ability to efficiently complete many types of simulations in a timely manner (in a few weeks or months rather than years), which is of significant scientific value. Together, these clients allow researchers to study biomedical questions formerly considered impractical to tackle computationally.[36][142][144]

Professional software developers are responsible for most of Folding@home's code, both for the client and server-side. The development team includes programmers from Nvidia, ATI, Sony, and Cauldron Development.[158] Clients can be downloaded only from the official Folding@home website or its commercial partners, and will only interact with Folding@home computer files. They will upload and download data with Folding@home's data servers (over port8080, with 80 as an alternate), and the communication is verified using 2048-bit digital signatures.[40][159] While the client's graphical user interface (GUI) is open-source,[160] the client is proprietary software citing security and scientific integrity as the reasons.[161][162][163]

However, this rationale of using proprietary software is disputed since while the license could be enforceable in the legal domain retrospectively, it doesn't practically prevent the modification (also known as patching) of the executable binary files. Likewise, binary-only distribution does not prevent the malicious modification of executable binary-code, either through a man-in-the-middle attack while being downloaded via the internet,[164] or by the redistribution of binaries by a third-party that have been previously modified either in their binary state (i.e. patched),[165] or by decompiling[166] and recompiling them after modification.[167][168] Unless the binary files and the transport channel are signed and the recipient person/system is able to verify the digital signature, in which case unwarranted modifications should be detectable, but not always.[169] Either way, since in the case of Folding@Home the input data and output result processed by the client-software are both digitally signed,[40][159] the integrity of work can be verified independently from the integrity of the client software itself.

Folding@home uses the Cosm software libraries for networking.[142][158] Folding@home was launched on October1, 2000, and was the first distributed computing project aimed at bio-molecular systems.[170] Its first client was a screensaver, which would run while the computer was not otherwise in use.[171][172] In 2004, the Pande lab collaborated with David P. Anderson to test a supplemental client on the open-source BOINC framework. This client was released to closed beta in April 2005;[173] however, the method became unworkable and was shelved in June 2006.[174]

The specialized hardware of graphics processing units (GPU) is designed to accelerate rendering of 3-Dgraphics applications such as video games and can significantly outperform CPUs for some types of calculations. GPUs are one of the most powerful and rapidly growing computing platforms, and many scientists and researchers are pursuing general-purpose computing on graphics processing units (GPGPU). However, GPU hardware is difficult to use for non-graphics tasks and usually requires significant algorithm restructuring and an advanced understanding of the underlying architecture.[175] Such customization is challenging, more so to researchers with limited software development resources. Folding@home uses the open-source OpenMM library, which uses a bridge design pattern with two application programming interface (API) levels to interface molecular simulation software to an underlying hardware architecture. With the addition of hardware optimizations, OpenMM-based GPU simulations need no significant modification but achieve performance nearly equal to hand-tuned GPU code, and greatly outperform CPU implementations.[154][176]

Before 2010, the computing reliability of GPGPU consumer-grade hardware was largely unknown, and circumstantial evidence related to the lack of built-in error detection and correction in GPU memory raised reliability concerns. In the first large-scale test of GPU scientific accuracy, a 2010 study of over 20,000 hosts on the Folding@home network detected soft errors in the memory subsystems of two-thirds of the tested GPUs. These errors strongly correlated to board architecture, though the study concluded that reliable GPU computing was very feasible as long as attention is paid to the hardware traits, such as software-side error detection.[177]

The first generation of Folding@home's GPU client (GPU1) was released to the public on October2, 2006,[174] delivering a 2030 times speedup for some calculations over its CPU-based GROMACS counterparts.[178] It was the first time GPUs had been used for either distributed computing or major molecular dynamics calculations.[179][180] GPU1 gave researchers significant knowledge and experience with the development of GPGPU software, but in response to scientific inaccuracies with DirectX, on April10, 2008 it was succeeded by GPU2, the second generation of the client.[178][181] Following the introduction of GPU2, GPU1 was officially retired on June6.[178] Compared to GPU1, GPU2 was more scientifically reliable and productive, ran on ATI and CUDA-enabled Nvidia GPUs, and supported more advanced algorithms, larger proteins, and real-time visualization of the protein simulation.[182][183] Following this, the third generation of Folding@home's GPU client (GPU3) was released on May25, 2010. While backward compatible with GPU2, GPU3 was more stable, efficient, and flexibile in its scientific abilities,[184] and used OpenMM on top of an OpenCL framework.[184][185] Although these GPU3 clients did not natively support the operating systems Linux and macOS, Linux users with Nvidia graphics cards were able to run them through the Wine software application.[186][187] GPUs remain Folding@home's most powerful platform in FLOPS. As of November 2012, GPU clients account for 87% of the entire project's x86 FLOPS throughput.[188]

Native support for Nvidia and AMD graphics cards under Linux was introduced with FahCore 17, which uses OpenCL rather than CUDA.[189]

From March 2007 until November 2012, Folding@home took advantage of the computing power of PlayStation 3s. At the time of its inception, its main streaming Cell processor delivered a 20 times speed increase over PCs for some calculations, processing power which could not be found on other systems such as the Xbox 360.[36][190] The PS3's high speed and efficiency introduced other opportunities for worthwhile optimizations according to Amdahl's law, and significantly changed the tradeoff between computing efficiency and overall accuracy, allowing the use of more complex molecular models at little added computing cost.[191] This allowed Folding@home to run biomedical calculations that would have been otherwise infeasible computationally.[192]

The PS3 client was developed in a collaborative effort between Sony and the Pande lab and was first released as a standalone client on March23, 2007.[36][193] Its release made Folding@home the first distributed computing project to use PS3s.[194] On September18 of the following year, the PS3 client became a channel of Life with PlayStation on its launch.[195][196] In the types of calculations it can perform, at the time of its introduction, the client fit in between a CPU's flexibility and a GPU's speed.[142] However, unlike clients running on personal computers, users were unable to perform other activities on their PS3 while running Folding@home.[192] The PS3's uniform console environment made technical support easier and made Folding@home more user friendly.[36] The PS3 also had the ability to stream data quickly to its GPU, which was used for real-time atomic-level visualizing of the current protein dynamics.[191]

On November 6, 2012, Sony ended support for the Folding@home PS3 client and other services available under Life with PlayStation. Over its lifetime of five years and seven months, more than 15 million users contributed over 100 million hours of computing to Folding@home, greatly assisting the project with disease research. Following discussions with the Pande lab, Sony decided to terminate the application. Pande considered the PlayStation 3 client a "game changer" for the project.[197][198][199]

Folding@home can use the parallel computing abilities of modern multi-core processors. The ability to use several CPU cores simultaneously allows completing the full simulation far faster. Working together, these CPU cores complete single work units proportionately faster than the standard uniprocessor client. This method is scientifically valuable because it enables much longer simulation trajectories to be performed in the same amount of time, and reduces the traditional difficulties of scaling a large simulation to many separate processors.[200] A 2007 publication in the Journal of Molecular Biology relied on multi-core processing to simulate the folding of part of the villin protein approximately 10 times longer than was possible with a single-processor client, in agreement with experimental folding rates.[201]

In November 2006, first-generation symmetric multiprocessing (SMP) clients were publicly released for open beta testing, referred to as SMP1.[174] These clients used Message Passing Interface (MPI) communication protocols for parallel processing, as at that time the GROMACS cores were not designed to be used with multiple threads.[144] This was the first time a distributed computing project had used MPI.[202] Although the clients performed well in Unix-based operating systems such as Linux and macOS, they were troublesome under Windows.[200][202] On January24, 2010, SMP2, the second generation of the SMP clients and the successor to SMP1, was released as an open beta and replaced the complex MPI with a more reliable thread-based implementation.[139][158]

SMP2 supports a trial of a special category of bigadv work units, designed to simulate proteins that are unusually large and computationally intensive and have a great scientific priority. These units originally required a minimum of eight CPU cores,[203] which was raised to sixteen later, on February7, 2012.[204] Along with these added hardware requirements over standard SMP2 work units, they require more system resources such as random-access memory (RAM) and Internet bandwidth. In return, users who run these are rewarded with a 20% increase over SMP2's bonus point system.[205] The bigadv category allows Folding@home to run especially demanding simulations for long times that had formerly required use of supercomputing clusters and could not be performed anywhere else on Folding@home.[203] Many users with hardware able to run bigadv units have later had their hardware setup deemed ineligible for bigadv work units when CPU core minimums were increased, leaving them only able to run the normal SMP work units. This frustrated many users who invested significant amounts of money into the program only to have their hardware be obsolete for bigadv purposes shortly after. As a result, Pande announced in January 2014 that the bigadv program would end on January 31, 2015.[206]

The V7 client is the seventh and latest generation of the Folding@home client software, and is a full rewrite and unification of the prior clients for Windows, macOS, and Linux operating systems.[207][208] It was released on March22, 2012.[209] Like its predecessors, V7 can run Folding@home in the background at a very low priority, allowing other applications to use CPU resources as they need. It is designed to make the installation, start-up, and operation more user-friendly for novices, and offer greater scientific flexibility to researchers than prior clients.[210] V7 uses Trac for managing its bug tickets so that users can see its development process and provide feedback.[208]

V7 consists of four integrated elements. The user typically interacts with V7's open-source GUI, named FAHControl.[160][211] This has Novice, Advanced, and Expert user interface modes, and has the ability to monitor, configure, and control many remote folding clients from one computer. FAHControl directs FAHClient, a back-end application that in turn manages each FAHSlot (or slot). Each slot acts as replacement for the formerly distinct Folding@home v6 uniprocessor, SMP, or GPU computer clients, as it can download, process, and upload work units independently. The FAHViewer function, modeled after the PS3's viewer, displays a real-time 3-D rendering, if available, of the protein currently being processed.[207][208]

In 2014, a client for the Google Chrome and Chromium web browsers was released, allowing users to run Folding@home in their web browser. The client uses Google's Native Client (NaCl) feature on Chromium-based web browsers to run the Folding@Home code at near-native speed in a sandbox on the user's machine.[212] Due to the phasing out of NaCL and changes at Folding@Home, the web client was permanently shut down in June 2019.[213]

In July 2015, a client for Android mobile phones was released on Google Play for devices running Android 4.4 KitKat or newer.[214][215]

On the 16th of February 2018 the android client, which was offered in cooperation with Sony, was removed from the Google Play. Plans were announced to offer an open source alternative in the future.[216]

Rosetta@home is a distributed computing project aimed at protein structure prediction and is one of the most accurate tertiary structure predictors.[217][218] The conformational states from Rosetta's software can be used to initialize a Markov state model as starting points for Folding@home simulations.[22] Conversely, structure prediction algorithms can be improved from thermodynamic and kinetic models and the sampling aspects of protein folding simulations.[219] As Rosetta only tries to predict the final folded state, and not how folding proceeds, Rosetta@home and Folding@home are complementary and address very different molecular questions.[22][220]

Anton is a special-purpose supercomputer built for molecular dynamics simulations. In October 2011, Anton and Folding@home were the two most powerful molecular dynamics systems.[221] Anton is unique in its ability to produce single ultra-long computationally costly molecular trajectories,[222] such as one in 2010 which reached the millisecond range.[223][224] These long trajectories may be especially helpful for some types of biochemical problems.[225][226] However, Anton does not use Markov state models (MSM) for analysis. In 2011, the Pande lab constructed a MSM from two 100-s Anton simulations and found alternative folding pathways that were not visible through Anton's traditional analysis. They concluded that there was little difference between MSMs constructed from a limited number of long trajectories or one assembled from many shorter trajectories.[222] In June 2011 Folding@home began added sampling of an Anton simulation in an effort to better determine how its methods compare to Anton's.[227][228] However, unlike Folding@home's shorter trajectories, which are more amenable to distributed computing and other parallelizing methods, longer trajectories do not require adaptive sampling to sufficiently sample the protein's phase space. Due to this, it is possible that a combination of Anton's and Folding@home's simulation methods would provide a more thorough sampling of this space.[222]

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Folding@home - Wikipedia

Protein Folding: The Good, the Bad, and the Ugly – Science …

Posted on September 13, 2019 by Prof Baldwin

We often think of proteins as nutrients in the food we eat or the main component of muscles, but proteins are also microscopic molecules inside of cells that perform diverse and vital jobs. With the Human Genome Project complete, scientists are turning their attention to the human proteome, the catalog of all human proteins. This work has shown that the world of proteins is a fascinating one, full of molecules with such intricate shapes and precise functions that they seem almost fanciful.

A proteins function depends on its shape, and when protein formation goes awry, the resulting misshapen proteins cause problems that range from bad, when proteins neglect their important work, to ugly, when they form a sticky, clumpy mess inside of cells. Current research suggests that the world of proteins is far from pristine. Protein formation is an error-prone process, and mistakes along the way have been linked to a number of human diseases.

There are 20,000 to over 100,000 unique types of proteins within a typical human cell. Why so many? Proteins are the workhorses of the cell. Each expertly performs a specific task. Some are structural, lending stiffness and rigidity to muscle cells or long thin neurons, for example. Others bind to specific molecules and shuttle them to new locations, and still others catalyze reactions that allow cells to divide and grow. This wealth of diversity and specificity in function is made possible by a seemingly simple property of proteins: they fold.

A protein starts off in the cell as a long chain of, on average, 300 building blocks called amino acids. There are 22 different types of amino acids, and their ordering determines how the protein chain will fold upon itself. When folding, two types of structures usually form first. Some regions of the protein chain coil up into slinky-like formations called alpha helices, while other regions fold into zigzag patterns called beta sheets, which resemble the folds of a paper fan. These two structures can interact to form more complex structures. For example, in one protein structure, several beta sheets wrap around themselves to form a hollow tube with a few alpha helices jutting out from one end. The tube is short and squat such that the overall structure resembles snakes (alpha helices) emerging from a can (beta sheet tube). A few other protein structures with descriptive names include the beta barrel, the beta propeller, the alpha/beta horseshoe, and the jelly-roll fold.

These complex structures allow proteins to perform their diverse jobs in the cell. The snakes in a can protein, when embedded in a cell membrane, creates a tunnel that allows traffic into and out of cells. Other proteins form shapes with pockets called active sites that are perfectly shaped to bind to a particular molecule, like a lock and key. By folding into distinct shapes, proteins can perform very different roles despite being composed of the same basic building blocks. To draw an analogy, all vehicles are made from steel, but a racecars sleek shape wins races, while a bus, dump truck, crane, or zamboni are each shaped to perform their own unique tasks.

Folding allows a protein to adopt a functional shape, but it is a complex process that sometimes fails. Protein folding can go wrong for three major reasons:

1: A person might possess a mutation that changes an amino acid in the protein chain, making it difficult for a particular protein to find its preferred fold or native state. This is the case for inherited mutations, for example, those leading to cystic fibrosis or sickle cell anemia. These mutations are located in the DNA sequence or gene that encodes one particular protein. Therefore, these types of inherited mutations affect only that particular protein and its related function.

2: On the other hand, protein folding failure can be viewed as an ongoing and more general process that affects many proteins. When proteins are created, the machine that reads the directions from DNA to create the long chains of amino acids can make mistakes. Scientists estimate that this machine, the ribosome, makes mistakes in as many as 1 in every 7 proteins! These mistakes can make the resulting proteins less likely to fold properly.

3: Even if an amino acid chain has no mutations or mistakes, it may still not reach its preferred folded shape simply because proteins do not fold correctly 100% of the time. Protein folding becomes even more difficult if the conditions in the cell, like acidity and temperature, change from those to which the organism is accustomed.

A failure in protein folding causes several known diseases, and scientists hypothesize that many more diseases may be related to folding problems. There are two completely different problems that occur in cells when their proteins do not fold properly.

One type of problem, called loss of function, results when not enough of a particular protein folds properly, causing a shortage of specialized workers needed to do a specific job. For example, imagine that a properly folded protein is perfectly shaped to bind a toxin and break it into less toxic byproducts. Without enough of the properly folded protein available, the toxin will build up to damaging levels. As another example, a protein may be responsible for metabolizing sugar so that the cell can use it for energy. The cell will grow slowly due to lack of energy if not enough of the protein is present in its functional state. The reason the cell gets sick, in these cases, is due to a lack of one specific, properly folded, functional protein. Cystic fibrosis, Tay-Sachs disease, Marfan syndrome, and some forms of cancer are examples of diseases that result when one type of protein is not able to perform its job. Who knew that one type of protein among tens of thousands could be so important?

Proteins that fold improperly may also impact the health of the cell regardless of the function of the protein. When proteins fail to fold into their functional state, the resulting misfolded proteins can be contorted into shapes that are unfavorable to the crowded cellular environment. Most proteins possess sticky, water-hating amino acids that they bury deep inside their core. Misfolded proteins wear these inner parts on the outside, like a chocolate-covered candy that has been crushed to reveal a gooey caramel center. These misfolded proteins often stick together forming clumps called aggregates. Scientists hypothesize that the accumulation of misfolded proteins plays a role in several neurological diseases, including Alzheimers, Parkinsons, Huntingtons, and Lou Gehrigs (ALS) disease, but scientists are still working to discover exactly how these misfolded, sticky molecules inflict their damage on cells.

One misfolded protein stands out among the rest to deserve special attention. The prion protein in Creutzfeldt-Jakob disease, also known as mad cow disease, is an example of a misfolded protein gone rogue. This protein is not only irreversibly misfolded, but it converts other functional proteins into its twisted state.

Recent research shows that protein misfolding happens frequently inside of cells. Fortunately, cells are accustomed to coping with this problem and have several systems in place to refold or destroy aberrant protein formations.

Chaperones are one such system. Appropriately named, they accompany proteins through the folding process, improving a proteins chances of folding properly and even allowing some misfolded proteins the opportunity to refold. Interestingly, chaperones are proteins themselves! There are many different types of chaperones. Some cater specifically to helping one type of protein fold, while others act more generally. Some chaperones are shaped like large hollow chambers and provide proteins with a safe space, isolated from other molecules, in which to fold. Production of several chaperones is boosted when a cell encounters high temperatures or other conditions making protein folding more difficult, thus earning these chaperones the alias, heat shock proteins.

Another line of cell defense against misfolded proteins is called the proteasome. If misfolded proteins linger in the cell, they will be targeted for destruction by this machine, which chews up proteins and spits them out as small fragments of amino acids. The proteasome is like a recycling center, allowing the cell to reuse amino acids to make more proteins. The proteasome itself is not one protein but many acting together. Proteins frequently interact to form larger structures with important cellular functions. For example, the tail of a human sperm is a structure composed of many types of proteins that work together to form a complex rotary engine that propels the sperm forward.

Why is it that some misfolded proteins are able to evade systems like chaperones and the proteasome? How can sticky misfolded proteins cause the neurodegenerative diseases listed above? Do some proteins misfold more often than others? These questions are at the forefront of current research seeking to understand basic protein biology and the diseases that result when protein folding goes awry.

The wide world of proteins, with its great assortment of shapes, bestows cells with capabilities that allow for life to exist and allow for its diversity (e.g., the differences between eye, skin, lung or heart cells, and the differences between species). Perhaps for this reason, the word protein is from the Greek word protas, meaning of primary importance.

Contributed by Kerry Geiler, a 4th year Ph.D student in the Harvard Department of Organismic and Evolutionary Biology

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Protein Folding: The Good, the Bad, and the Ugly - Science ...

Protein Folding – Chemistry LibreTexts

Posted on September 14, 2019 by Prof Baldwin

Introduction and Protein Structure

Proteins have several layers of structure each of which is important in the process of protein folding. The first most basic level of this structure is the sequence of amino acids themselves.1 The sequencing is important because it will determine the types of interactions seen in the protein as it is folding. A novel sequence-based method based on the assumption that protein-protein interactions are more related to amino acids at the surface than those at the core.2 This study shows that not only is the amino acids that are in a protein important but also the order in which they are sequenced. The interactions of the amino acids will determine what the secondary and tertiary structure of the protein will be.

The next layer in protein structure is the secondary structure. The secondary structure includes architectural structures that extend in one dimension.1 Secondary structure includes -Helixes (Figure 1) and -sheets (Figure 2). The -helices, the most common secondary structure in proteins, the peptide CONHgroups in the backbone form chains held together by NH OC hydrogen bonds.3 The -helices form the backbone of proteins and help to aid in the folding process. The -sheets form in two distinct ways. They are able to form in both parallel -pleated sheets and anti parallel -pleated sheets.1 When the -helix or -sheet is formed, the excluded volumes generated by the backbone and side chains overlap, leading to an increase in the total volume available to the translational displacement of water molecules.4 This is important because it leads to a more thermodynamically stable conformation and leads to less strain on the protein as a whole and thus are aided by the conformation.

Figure 1: (left) typical example to an -helix, from Wikimedia CommonsFigure 2: (right) typical example of an -sheet, from Wikimedia Commons

The tertiary structure is the next layer in protein structure. This takes the -Helixes and -sheets and allows them to fold into a three dimensional structure.1 Most proteins take on a globular structure once folded. The description of globular protein structures as an ensemble of contiguous closed loops or tightened end fragments reveals fold elements crucial for the formation of stable structures and for navigating the very process of protein folding.5 The globular proteins generally have a hydrophobic core surrounded by a hydrophilic outer layer. These interactions are important because they lead to the global structure and help create channels and binding sites for enzymes.

The last layer of protein structure is the quaternary structure. The folding transition and the functional transitions between useful states are encoded in the linear sequence of amino acids, and a long- term goal of structural biology is to be able to predict both the structure and function of molecules from the information in the sequence.6 The Subunit organization is the last level of structure in protein molecules.1 The organization of the subunits is important because that determines the types of interactions that can form and dictates its use in the body.

Proteins are folded and held together by several forms of molecular interactions. The molecular interactions include the thermodynamic stability of the complex, the hydrophobic interactions and the disulfide bonds formed in the proteins. The figure below (figure 3) is an example of protein folding.

Figure 3: Protein Folding, from Wikimedia Commons

The biggest factor in a proteins ability to fold is the thermodynamics of the structure. The interaction scheme includes the short-range propensity to form extended conformations, residue-dependent long-range contact potentials, and orientation-dependent hydrogen bonds.7 The thermodynamics are a main stabilizing force within a protein because if it is not in the lowest energy conformation it will continue to move and adjust until it finds its most stable state. The use of energy diagrams and maps are key in finding out when the protein is in the most stable form possible.

The next type of interaction in protein folding is the hydrophobic interactions within the protein. The framework model and the hydrophobic collapse model represent two canonical descriptions of the protein folding process. The first places primary reliance on the short-range interactions of secondary structure and the second assigns greater importance to the long-range interactions of tertiary structure.6 These hydrophobic interactions have an impact not just on the primary structure but then lead to changes seen in the secondary and tertiary structure as well. Globular proteins acquire distinct compact native con- formations in water as a result of the hydrophobic effect.7 When a protein has been folded in the correct way it usually exists with the hydrophobic core as a result of being hydrated by waters in the system around it which is important because it creates a charged core to the protein and can lead to the creation of channels within the protein. The hydrophobic interactions are found to affect time correlation functions in the vicinity of the native state even though they have no impact on same time characteristics of the structure fluctuations around the native state.7 The hydrophobic interactions are shown to have an impact on the protein even after it has found the most stable conformation in how the proteins can interact with each other as well as folding themselves.

Another type of interaction seen when the protein is folding is the disulfide linkages that form in the protein. (See figure 4) The disulfide bond, a sulfur- sulfur chemical bond that results from an oxidative process that links nonadjacent (in most cases) cysteines of a protein.9 These are a major way that proteins get into their folded form. The types of disulfide bonds are cysteine-cysteine linkage is a stable part of their final folded structure and those in which pairs of cysteines alternate between the reduced and oxidized states.9 The more common is the linkages that cause the protein to fold together and link back on itself compared to the cysteines that are changing oxidation states because the bonds between cysteines once created are fairly stable.

Figure 4: Disulfide Bonds, shown in the picture in yellow, from Wikimedia Commons

Proteins can miss function for several reasons. When a protein is miss folded it can lead to denaturation of the protein. Denaturation is the loss of protein structure and function.1 The miss folding does not always lead to complete lack of function but only partial loss of functionality. The miss functioning of proteins can sometimes lead to diseases in the human body.

Alzheimer's Disease (AD) is a neurological degenerative disease that affects around 5 million Americans, including nearly half of those who are age 85 or older.10 The predominant risk factors of AD are age, family history, and heredity. Alzheimers disease typically results in memory loss, confusion of time and place, misplacing places, and changes in mood and behavior.11 AD results in dense plaques in the brain that are comprised of fibrillar -amyloid proteins with a well-orders -sheet secondary structure.12 These plaques visually look like voids in the brain matter (see figure 5) and are directly connected to the deterioration of thought processes. It has been determined that AD is a protein misfolding disease, where the misfolded protein is directly related to the formation of these plaques in the brain.13

Figure 5: Comparison of healthy brain (left) with brian with Alzheimer's (right)From Wikimedia Commons

It is yet to be fully understood what exactly causes this protein misfolding to begin, but several theories point to oxidative stress in the brain to be the initiating factor. This oxidation results in damage to the phospholipids in the brain, which has been found to result in a faster accumulation of amyloid -proteins.14

Figure 6: Beta-Amyloid Plaque Formation, from Wikimedia Commons

Cystic Fibrosis (CF) is a chronic disease that affects 30,000 Americans. The typical affects of CF is a production of thick, sticky mucus that clogs the lungs and leads to life-threatening lung infection, and obstructs the pancreas preventing proper food processing.15 CF is caused by protein misfolding. This misfolding then results in some change in the protein known as cystic fibrosis transmembrane conductance regulator (CFTR), which can result in this potentially fatal disease.16 In approximately 70% of CF cases, a deletion of phenylalanine at position 508 in the CFTR is deleted. This deletion of Phe508 seems to be directly connected to the formation of CF.17 The protein misfolding that results in CF occurs prior to birth, but it is not entirely clear as to why.

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Protein Folding - Chemistry LibreTexts

Protein Structure and Folding

Posted on September 19, 2019 by Prof Baldwin

After a polypeptide is produced in protein synthesis, it's not necessarily a functional protein yet! Explore protein folding that occurs within levels of protein structure with the Amoeba Sisters! Primary, secondary, tertiary, and quaternary protein structure levels are briefly discussed. Video also mentions chaperonins (chaperone proteins) and how proteins can be denatured.

Table of Contents:0:41 Reminder of Protein Roles1:06 Modifications of Proteins1:25 Importance of Shape for Proteins1:56 Levels of Protein Structure2:06 Primary Structure3:10 Secondary Structure3:45 Tertiary Structure4:58 Quaternary Structure [not in all proteins]6:01 Proteins often have help in folding [introduces chaperonins]6:40 Denaturing Proteins

*Further Reading Suggestions*

Related to Protein Misfoldings:

https://www.nature.com/scitable/topic...https://www.scientificamerican.com/ar...

Learn About "The Protein Folding Problem":https://www.ncbi.nlm.nih.gov/pmc/arti...

Factual References:

OpenStax, Biology. OpenStax CNX. Jun 1, 2018 http://cnx.org/contents/185cbf87-c72e....

Reece, J. B., & Campbell, N. A. (2011). Campbell biology. Boston: Benjamin Cummings / Pearson.

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Protein Structure and Folding

Protein folding – Wikipedia

Posted on September 11, 2019 by Prof Baldwin

"Protein thermodynamics" redirects here. For the thermodynamics of reactions catalyzed by proteins, see Enzyme.

Protein folding is the physical process by which a protein chain acquires its native 3-dimensional structure, a conformation that is usually biologically functional, in an expeditious and reproducible manner. It is the physical process by which a polypeptide folds into its characteristic and functional three-dimensional structure from random coil.[1]Each protein exists as an unfolded polypeptide or random coil when translated from a sequence of mRNA to a linear chain of amino acids. This polypeptide lacks any stable (long-lasting) three-dimensional structure (the left hand side of the first figure). As the polypeptide chain is being synthesized by a ribosome, the linear chain begins to fold into its three-dimensional structure. Folding begins to occur even during translation of the polypeptide chain. Amino acids interact with each other to produce a well-defined three-dimensional structure, the folded protein (the right hand side of the figure), known as the native state. The resulting three-dimensional structure is determined by the amino acid sequence or primary structure (Anfinsen's dogma).[2]

The correct three-dimensional structure is essential to function, although some parts of functional proteins may remain unfolded,[3] so that protein dynamics is important. Failure to fold into native structure generally produces inactive proteins, but in some instances misfolded proteins have modified or toxic functionality. Several neurodegenerative and other diseases are believed to result from the accumulation of amyloid fibrils formed by misfolded proteins.[4] Many allergies are caused by incorrect folding of some proteins, because the immune system does not produce antibodies for certain protein structures.[5]

Denaturation of proteins is a process of transition from the folded to the unfolded state. It happens in cooking, in burns, in proteinopathies, and in other contexts.[6]

The duration of the folding process varies dramatically depending on the protein of interest. When studied outside the cell, the slowest folding proteins require many minutes or hours to fold primarily due to proline isomerization, and must pass through a number of intermediate states, like checkpoints, before the process is complete.[7] On the other hand, very small single-domain proteins with lengths of up to a hundred amino acids typically fold in a single step.[8] Time scales of milliseconds are the norm and the very fastest known protein folding reactions are complete within a few microseconds.[9]

The primary structure of a protein, its linear amino-acid sequence, determines its native conformation.[10] The specific amino acid residues and their position in the polypeptide chain are the determining factors for which portions of the protein fold closely together and form its three-dimensional conformation. The amino acid composition is not as important as the sequence.[11] The essential fact of folding, however, remains that the amino acid sequence of each protein contains the information that specifies both the native structure and the pathway to attain that state. This is not to say that nearly identical amino acid sequences always fold similarly.[12] Conformations differ based on environmental factors as well; similar proteins fold differently based on where they are found.

Formation of a secondary structure is the first step in the folding process that a protein takes to assume its native structure. Characteristic of secondary structure are the structures known as alpha helices and beta sheets that fold rapidly because they are stabilized by intramolecular hydrogen bonds, as was first characterized by Linus Pauling. Formation of intramolecular hydrogen bonds provides another important contribution to protein stability.[13] -helices are formed by hydrogen bonding of the backbone to form a spiral shape (refer to figure on the right).[11] The pleated sheet is a structure that forms with the backbone bending over itself to form the hydrogen bonds (as displayed in the figure to the left). The hydrogen bonds are between the amide hydrogen and carbonyl oxygen of the peptide bond. There exists anti-parallel pleated sheets and parallel pleated sheets where the stability of the hydrogen bonds is stronger in the anti-parallel sheet as it hydrogen bonds with the ideal 180 degree angle compared to the slanted hydrogen bonds formed by parallel sheets.[11]

The alpha helices and beta pleated sheets can be amphipathic in nature, or contain a hydrophilic portion and a hydrophobic portion. This property of secondary structures aids in the tertiary structure of a protein in which the folding occurs so that the hydrophilic sides are facing the aqueous environment surrounding the protein and the hydrophobic sides are facing the hydrophobic core of the protein.[14] Secondary structure hierarchically gives way to tertiary structure formation. Once the protein's tertiary structure is formed and stabilized by the hydrophobic interactions, there may also be covalent bonding in the form of disulfide bridges formed between two cysteine residues. Tertiary structure of a protein involves a single polypeptide chain; however, additional interactions of folded polypeptide chains give rise to quaternary structure formation.[15]

Tertiary structure may give way to the formation of quaternary structure in some proteins, which usually involves the "assembly" or "coassembly" of subunits that have already folded; in other words, multiple polypeptide chains could interact to form a fully functional quaternary protein.[11]

Folding is a spontaneous process that is mainly guided by hydrophobic interactions, formation of intramolecular hydrogen bonds, van der Waals forces, and it is opposed by conformational entropy.[16] The process of folding often begins co-translationally, so that the N-terminus of the protein begins to fold while the C-terminal portion of the protein is still being synthesized by the ribosome; however, a protein molecule may fold spontaneously during or after biosynthesis.[17] While these macromolecules may be regarded as "folding themselves", the process also depends on the solvent (water or lipid bilayer),[18] the concentration of salts, the pH, the temperature, the possible presence of cofactors and of molecular chaperones.Proteins will have limitations on their folding abilities by the restricted bending angles or conformations that are possible. These allowable angles of protein folding are described with a two-dimensional plot known as the Ramachandran plot, depicted with psi and phi angles of allowable rotation.[19]

Protein folding must be thermodynamically favorable within a cell in order for it to be a spontaneous reaction. Since it is known that protein folding is a spontaneous reaction, then it must assume a negative Gibbs free energy value. Gibbs free energy in protein folding is directly related to enthalpy and entropy.[11] For a negative delta G to arise and for protein folding to become thermodynamically favorable, then either enthalpy, entropy, or both terms must be favorable.

Minimizing the number of hydrophobic side-chains exposed to water is an important driving force behind the folding process.[20] The hydrophobic effect is the phenomenon in which the hydrophobic chains of a protein collapse into the core of the protein (away from the hydrophilic environment).[11] In an aqueous environment, the water molecules tend to aggregate around the hydrophobic regions or side chains of the protein, creating water shells of ordered water molecules.[21] An ordering of water molecules around a hydrophobic region increases order in a system and therefore contributes a negative change in entropy (less entropy in the system). The water molecules are fixed in these water cages which drives the hydrophobic collapse, or the inward folding of the hydrophobic groups. The hydrophobic collapse introduces entropy back to the system via the breaking of the water cages which frees the ordered water molecules.[11] The multitude of hydrophobic groups interacting within the core of the globular folded protein contributes a significant amount to protein stability after folding, because of the vastly accumulated van der Waals forces (specifically London Dispersion forces).[11] The hydrophobic effect exists as a driving force in thermodynamics only if there is the presence of an aqueous medium with an amphiphilic molecule containing a large hydrophobic region.[22] The strength of hydrogen bonds depends on their environment; thus, H-bonds enveloped in a hydrophobic core contribute more than H-bonds exposed to the aqueous environment to the stability of the native state.[23]

In proteins with globular folds, hydrophobic amino acids tend to be interspersed along the primary sequence, rather than randomly distributed or clustered together.[24][25] However, proteins that have recently been born de novo, which tend to be intrinsically disordered[26][27], show the opposite pattern of hydrophobic amino acid clustering along the primary sequence.[28]

Molecular chaperones are a class of proteins that aid in the correct folding of other proteins in vivo. Chaperones exist in all cellular compartments and interact with the polypeptide chain in order to allow the native three-dimensional conformation of the protein to form; however, chaperones themselves are not included in the final structure of the protein they are assisting in.[29] Chaperones may assist in folding even when the nascent polypeptide is being synthesized by the ribosome.[30] Molecular chaperones operate by binding to stabilize an otherwise unstable structure of a protein in its folding pathway, but chaperones do not contain the necessary information to know the correct native structure of the protein they are aiding; rather, chaperones work by preventing incorrect folding conformations.[30] In this way, chaperones do not actually increase the rate of individual steps involved in the folding pathway toward the native structure; instead, they work by reducing possible unwanted aggregations of the polypeptide chain that might otherwise slow down the search for the proper intermediate and they provide a more efficient pathway for the polypeptide chain to assume the correct conformations.[29] Chaperones are not to be confused with folding catalysts, which actually do catalyze the otherwise slow steps in the folding pathway. Examples of folding catalysts are protein disulfide isomerases and peptidyl-prolyl isomerases that may be involved in formation of disulfide bonds or interconversion between cis and trans stereoisomers, respectively.[30] Chaperones are shown to be critical in the process of protein folding in vivo because they provide the protein with the aid needed to assume its proper alignments and conformations efficiently enough to become "biologically relevant".[31] This means that the polypeptide chain could theoretically fold into its native structure without the aid of chaperones, as demonstrated by protein folding experiments conducted in vitro;[31] however, this process proves to be too inefficient or too slow to exist in biological systems; therefore, chaperones are necessary for protein folding in vivo. Along with its role in aiding native structure formation, chaperones are shown to be involved in various roles such as protein transport, degradation, and even allow denatured proteins exposed to certain external denaturant factors an opportunity to refold into their correct native structures.[32]

A fully denatured protein lacks both tertiary and secondary structure, and exists as a so-called random coil. Under certain conditions some proteins can refold; however, in many cases, denaturation is irreversible.[33] Cells sometimes protect their proteins against the denaturing influence of heat with enzymes known as heat shock proteins (a type of chaperone), which assist other proteins both in folding and in remaining folded. Some proteins never fold in cells at all except with the assistance of chaperones which either isolate individual proteins so that their folding is not interrupted by interactions with other proteins or help to unfold misfolded proteins, allowing them to refold into the correct native structure.[34] This function is crucial to prevent the risk of precipitation into insoluble amorphous aggregates. The external factors involved in protein denaturation or disruption of the native state include temperature, external fields (electric, magnetic),[35] molecular crowding,[36] and even the limitation of space, which can have a big influence on the folding of proteins.[37] High concentrations of solutes, extremes of pH, mechanical forces, and the presence of chemical denaturants can contribute to protein denaturation, as well. These individual factors are categorized together as stresses. Chaperones are shown to exist in increasing concentrations during times of cellular stress and help the proper folding of emerging proteins as well as denatured or misfolded ones.[29]

Under some conditions proteins will not fold into their biochemically functional forms. Temperatures above or below the range that cells tend to live in will cause thermally unstable proteins to unfold or denature (this is why boiling makes an egg white turn opaque). Protein thermal stability is far from constant, however; for example, hyperthermophilic bacteria have been found that grow at temperatures as high as 122C,[38] which of course requires that their full complement of vital proteins and protein assemblies be stable at that temperature or above.

A protein is considered to be misfolded if it cannot achieve its normal native state. This can be due to mutations in the amino acid sequence or a disruption of the normal folding process by external factors.[39] The misfolded protein typically contains -sheets that are organized in a supramolecular arrangement known as a cross- structure. These -sheet-rich assemblies are very stable, very insoluble, and generally resistant to proteolysis.[40] The structural stability of these fibrillar assemblies is caused by extensive interactions between the protein monomers, formed by backbone hydrogen bonds between their -strands.[40] The misfolding of proteins can trigger the further misfolding and accumulation of other proteins into aggregates or oligomers. The increased levels of aggregated proteins in the cell leads to formation of amyloid-like structures which can cause degenerative disorders and cell death.[39] The amyloids are fibrillary structures that contain intermolecular hydrogen bonds which are highly insoluble and made from converted protein aggregates.[39] Therefore, the proteasome pathway may not be efficient enough to degrade the misfolded proteins prior to aggregation. Misfolded proteins can interact with one another and form structured aggregates and gain toxicity through intermolecular interactions.[39]

Aggregated proteins are associated with prion-related illnesses such as CreutzfeldtJakob disease, bovine spongiform encephalopathy (mad cow disease), amyloid-related illnesses such as Alzheimer's disease and familial amyloid cardiomyopathy or polyneuropathy,[41] as well as intracellular aggregation diseases such as Huntington's and Parkinson's disease.[4][42] These age onset degenerative diseases are associated with the aggregation of misfolded proteins into insoluble, extracellular aggregates and/or intracellular inclusions including cross- amyloid fibrils. It is not completely clear whether the aggregates are the cause or merely a reflection of the loss of protein homeostasis, the balance between synthesis, folding, aggregation and protein turnover. Recently the European Medicines Agency approved the use of Tafamidis or Vyndaqel (a kinetic stabilizer of tetrameric transthyretin) for the treatment of transthyretin amyloid diseases. This suggests that the process of amyloid fibril formation (and not the fibrils themselves) causes the degeneration of post-mitotic tissue in human amyloid diseases.[43] Misfolding and excessive degradation instead of folding and function leads to a number of proteopathy diseases such as antitrypsin-associated emphysema, cystic fibrosis and the lysosomal storage diseases, where loss of function is the origin of the disorder. While protein replacement therapy has historically been used to correct the latter disorders, an emerging approach is to use pharmaceutical chaperones to fold mutated proteins to render them functional.

While inferences about protein folding can be made through mutation studies, typically, experimental techniques for studying protein folding rely on the gradual unfolding or folding of proteins and observing conformational changes using standard non-crystallographic techniques.

X-ray crystallography is one of the more efficient and important methods for attempting to decipher the three dimensional configuration of a folded protein.[44] To be able to conduct X-ray crystallography, the protein under investigation must be located inside a crystal lattice. To place a protein inside a crystal lattice, one must have a suitable solvent for crystallization, obtain a pure protein at supersaturated levels in solution, and precipitate the crystals in solution.[45] Once a protein is crystallized, x-ray beams can be concentrated through the crystal lattice which would diffract the beams or shoot them outwards in various directions. These exiting beams are correlated to the specific three-dimensional configuration of the protein enclosed within. The x-rays specifically interact with the electron clouds surrounding the individual atoms within the protein crystal lattice and produce a discernible diffraction pattern.[14] Only by relating the electron density clouds with the amplitude of the x-rays can this pattern be read and lead to assumptions of the phases or phase angles involved that complicate this method.[46] Without the relation established through a mathematical basis known as Fourier transform, the "phase problem" would render predicting the diffraction patterns very difficult.[14] Emerging methods like multiple isomorphous replacement use the presence of a heavy metal ion to diffract the x-rays into a more predictable manner, reducing the number of variables involved and resolving the phase problem.[44]

Fluorescence spectroscopy is a highly sensitive method for studying the folding state of proteins. Three amino acids, phenylalanine (Phe), tyrosine (Tyr) and tryptophan (Trp), have intrinsic fluorescence properties, but only Tyr and Trp are used experimentally because their quantum yields are high enough to give good fluorescence signals. Both Trp and Tyr are excited by a wavelength of 280nm, whereas only Trp is excited by a wavelength of 295nm. Because of their aromatic character, Trp and Tyr residues are often found fully or partially buried in the hydrophobic core of proteins, at the interface between two protein domains, or at the interface between subunits of oligomeric proteins. In this apolar environment, they have high quantum yields and therefore high fluorescence intensities. Upon disruption of the proteins tertiary or quaternary structure, these side chains become more exposed to the hydrophilic environment of the solvent, and their quantum yields decrease, leading to low fluorescence intensities. For Trp residues, the wavelength of their maximal fluorescence emission also depend on their environment.

Fluorescence spectroscopy can be used to characterize the equilibrium unfolding of proteins by measuring the variation in the intensity of fluorescence emission or in the wavelength of maximal emission as functions of a denaturant value.[47][48] The denaturant can be a chemical molecule (urea, guanidinium hydrochloride), temperature, pH, pressure, etc. The equilibrium between the different but discrete protein states, i.e. native state, intermediate states, unfolded state, depends on the denaturant value; therefore, the global fluorescence signal of their equilibrium mixture also depends on this value. One thus obtains a profile relating the global protein signal to the denaturant value. The profile of equilibrium unfolding may enable one to detect and identify intermediates of unfolding.[49][50] General equations have been developed by Hugues Bedouelle to obtain the thermodynamic parameters that characterize the unfolding equilibria for homomeric or heteromeric proteins, up to trimers and potentially tetramers, from such profiles.[47] Fluorescence spectroscopy can be combined with fast-mixing devices such as stopped flow, to measure protein folding kinetics,[51] generate a chevron plot and derive a Phi value analysis.

Circular dichroism is one of the most general and basic tools to study protein folding. Circular dichroism spectroscopy measures the absorption of circularly polarized light. In proteins, structures such as alpha helices and beta sheets are chiral, and thus absorb such light. The absorption of this light acts as a marker of the degree of foldedness of the protein ensemble. This technique has been used to measure equilibrium unfolding of the protein by measuring the change in this absorption as a function of denaturant concentration or temperature. A denaturant melt measures the free energy of unfolding as well as the protein's m value, or denaturant dependence. A temperature melt measures the denaturation temperature (Tm) of the protein.[47] As for fluorescence spectroscopy, circular-dichroism spectroscopy can be combined with fast-mixing devices such as stopped flow to measure protein folding kinetics and to generate chevron plots.

The more recent developments of vibrational circular dichroism (VCD) techniques for proteins, currently involving Fourier transform (FFT) instruments, provide powerful means for determining protein conformations in solution even for very large protein molecules. Such VCD studies of proteins are often combined with X-ray diffraction of protein crystals, FT-IR data for protein solutions in heavy water (D2O), or ab initio quantum computations to provide unambiguous structural assignments that are unobtainable from CD.[citation needed]

Protein folding is routinely studied using NMR spectroscopy, for example by monitoring hydrogen-deuterium exchange of backbone amide protons of proteins in their native state, which provides both the residue-specific stability and overall stability of proteins.[52]

Dual polarisation interferometry is a surface-based technique for measuring the optical properties of molecular layers. When used to characterize protein folding, it measures the conformation by determining the overall size of a monolayer of the protein and its density in real time at sub-Angstrom resolution,[53] although real-time measurement of the kinetics of protein folding are limited to processes that occur slower than ~10Hz. Similar to circular dichroism, the stimulus for folding can be a denaturant or temperature.

The study of protein folding has been greatly advanced in recent years by the development of fast, time-resolved techniques. Experimenters rapidly trigger the folding of a sample of unfolded protein and observe the resulting dynamics. Fast techniques in use include neutron scattering,[54] ultrafast mixing of solutions, photochemical methods, and laser temperature jump spectroscopy. Among the many scientists who have contributed to the development of these techniques are Jeremy Cook, Heinrich Roder, Harry Gray, Martin Gruebele, Brian Dyer, William Eaton, Sheena Radford, Chris Dobson, Alan Fersht, Bengt Nlting and Lars Konermann.

Proteolysis is routinely used to probe the fraction unfolded under a wide range of solution conditions (e.g. Fast parallel proteolysis (FASTpp).[55][56]

Single molecule techniques such as optical tweezers and AFM have been used to understand protein folding mechanisms of isolated proteins as well as proteins with chaperones.[57] Optical tweezers have been used to stretch single protein molecules from their C- and N-termini and unfold them to allow study of the subsequent refolding.[58] The technique allows one to measure folding rates at single-molecule level; for example, optical tweezers have been recently applied to study folding and unfolding of proteins involved in blood coagulation. von Willebrand factor (vWF) is a protein with an essential role in blood clot formation process. It discovered using single molecule optical tweezers measurement that calcium-bound vWF acts as a shear force sensor in the blood. Shear force leads to unfolding of the A2 domain of vWF, whose refolding rate is dramatically enhanced in the presence of calcium.[59] Recently, it was also shown that the simple src SH3 domain accesses multiple unfolding pathways under force.[60]

Biotin painting enables condition-specific cellular snapshots of (un)folded proteins. Biotin 'painting' shows a bias towards predicted Intrinsically disordered proteins [61].

Computational studies of protein folding includes three main aspects related to the prediction of protein stability, kinetics, and structure. A recent review summarizes the available computational methods for protein folding. [62]

In 1969, Cyrus Levinthal noted that, because of the very large number of degrees of freedom in an unfolded polypeptide chain, the molecule has an astronomical number of possible conformations. An estimate of 3300 or 10143 was made in one of his papers.[63] Levinthal's paradox is a thought experiment based on the observation that if a protein were folded by sequentially sampling of all possible conformations, it would take an astronomical amount of time to do so, even if the conformations were sampled at a rapid rate (on the nanosecond or picosecond scale).[64] Based upon the observation that proteins fold much faster than this, Levinthal then proposed that a random conformational search does not occur, and the protein must, therefore, fold through a series of meta-stable intermediate states.

The configuration space of a protein during folding can be visualized as energy landscape. According to Joseph Bryngelson and Peter Wolynes, proteins follow the principle of minimal frustration meaning that naturally evolved proteins have optimized their folding energy landscapes.[65], and that nature has chosen amino acid sequences so that the folded state of the protein is sufficiently stable. In addition, the acquisition of the folded state had to become a sufficiently fast process. Even though nature has reduced the level of frustration in proteins, some degree of it remains up to now as can be observed in the presence of local minima in the energy landscape of proteins.

A consequence of these evolutionarily selected sequences is that proteins are generally thought to have globally "funneled energy landscapes" (coined by Jos Onuchic)[66] that are largely directed toward the native state. This "folding funnel" landscape allows the protein to fold to the native state through any of a large number of pathways and intermediates, rather than being restricted to a single mechanism. The theory is supported by both computational simulations of model proteins and experimental studies,[65] and it has been used to improve methods for protein structure prediction and design.[65] The description of protein folding by the leveling free-energy landscape is also consistent with the 2nd law of thermodynamics.[67] Physically, thinking of landscapes in terms of visualizable potential or total energy surfaces simply with maxima, saddle points, minima, and funnels, rather like geographic landscapes, is perhaps a little misleading. The relevant description is really a high-dimensional phase space in which manifolds might take a variety of more complicated topological forms.[68]

The unfolded polypeptide chain begins at the top of the funnel where it may assume the largest number of unfolded variations and is in its highest energy state. Energy landscapes such as these indicate that there are a large number of initial possibilities, but only a single native state is possible; however, it does not reveal the numerous folding pathways that are possible. A different molecule of the same exact protein may be able to follow marginally different folding pathways, seeking different lower energy intermediates, as long as the same native structure is reached.[69] Different pathways may have different frequencies of utilization depending on the thermodynamic favorability of each pathway. This means that if one pathway is found to be more thermodynamically favorable than another, it is likely to be used more frequently in the pursuit of the native structure.[69] As the protein begins to fold and assume its various conformations, it always seeks a more thermodynamically favorable structure than before and thus continues through the energy funnel. Formation of secondary structures is a strong indication of increased stability within the protein, and only one combination of secondary structures assumed by the polypeptide backbone will have the lowest energy and therefore be present in the native state of the protein.[69] Among the first structures to form once the polypeptide begins to fold are alpha helices and beta turns, where alpha helices can form in as little as 100 nanoseconds and beta turns in 1 microsecond.[29]

There exists a saddle point in the energy funnel landscape where the transition state for a particular protein is found.[29] The transition state in the energy funnel diagram is the conformation that must be assumed by every molecule of that protein if the protein wishes to finally assume the native structure. No protein may assume the native structure without first passing through the transition state.[29] The transition state can be referred to as a variant or premature form of the native state rather than just another intermediary step.[70] The folding of the transition state is shown to be rate-determining, and even though it exists in a higher energy state than the native fold, it greatly resembles the native structure. Within the transition state, there exists a nucleus around which the protein is able to fold, formed by a process referred to as "nucleation condensation" where the structure begins to collapse onto the nucleus.[70]

De novo or ab initio techniques for computational protein structure prediction are related to, but strictly distinct from, experimental studies of protein folding. Molecular Dynamics (MD) is an important tool for studying protein folding and dynamics in silico.[71] First equilibrium folding simulations were done using implicit solvent model and umbrella sampling.[72] Because of computational cost, ab initio MD folding simulations with explicit water are limited to peptides and very small proteins.[73][74] MD simulations of larger proteins remain restricted to dynamics of the experimental structure or its high-temperature unfolding. Long-time folding processes (beyond about 1 millisecond), like folding of small-size proteins (about 50 residues) or larger, can be accessed using coarse-grained models.[75][76][77]

The 100-petaFLOP distributed computing project Folding@home created by Vijay Pande's group at Stanford University simulates protein folding using the idle processing time of CPUs and GPUs of personal computers from volunteers. The project aims to understand protein misfolding and accelerate drug design for disease research.

Long continuous-trajectory simulations have been performed on Anton, a massively parallel supercomputer designed and built around custom ASICs and interconnects by D. E. Shaw Research. The longest published result of a simulation performed using Anton is a 2.936 millisecond simulation of NTL9 at 355 K.[78]

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Protein folding - Wikipedia

Stanford study finds high energy use provides little benefit for health and well-being in richer nations – Stanford University News

Posted on April 18, 2022 by Prof Baldwin

April 12, 2022

Analysis of data from 140 countries suggests many rich countries could use less energy per capita without compromising health, happiness or prosperity. Countries struggling with energy poverty may be able to maximize well-being with less energy than previously thought.

By Josie Garthwaite

A good, long life requires energy: to illuminate hospitals, homes and schools, and make it possible to work, cook meals and study without inhaling toxic smoke or spending a full day collecting fuel. But at some point, energy stops being the limiting factor for well-being.

A child studies by lantern light. Globally, 1.2 billion people live without access to electricity. (Image credit: Triloks/iStock)

New research from Stanford University suggests that point the threshold beyond which greater energy use loses its link to national-level improvements in measures of health, economy and environment is surprisingly low.

The results, published April 12 in Ecosphere, suggest nations with high per capita energy use, such as the United States and Canada, could scale back consumption while maintaining or even improving well-being. Countries where energy poverty remains a challenge, meanwhile, may be able to maximize national health and prosperity with far less energy than scholars once thought.

The authors found todays average global energy consumption of 79 gigajoules per person could, in principle, allow everyone on Earth to approach the maximum health, happiness and environmental well-being of the most prosperous countries today, if distributed equitably.

Other scholars have sought for decades to pin down the bare minimum of energy supply required per capita to achieve a decent quality of life. Early estimates suggested a range of 10 to 65 gigajoules per person. Its one thing to identify where people dont have enough energy; its another to identify what our target might be, said lead study author Rob Jackson, professor of Earth system science at Stanfords School of Earth, Energy & Environmental Sciences (Stanford Earth). How much additional energy needs to be provided?

Answering this question is not just an academic exercise. It is central to mapping out how the world can achieve international climate goals while building out modern energy services for the 1.2 billion people who live without electricity and the 2.7 billion who cook on stoves linked to 3.5 million premature deaths each year from household air pollution.

We need to address equity in energy use and greenhouse gas emissions. Among the least sustainable ways to do that would be to raise everyone to the levels of consumption we have in the United States, said Jackson, who is the Michelle and Kevin Douglas Provostial Professor at Stanford and a senior fellow at the Stanford Woods Institute for the Environment and at the Precourt Institute for Energy. Even using renewables, that would have serious, possibly catastrophic consequences for the environment, because of the materials, land and resources required to supply hundreds of gigajoules per year for each of the 8.5 billion people projected to inhabit Earth in 2030.

Reducing global population size would also tamp down total energy and resource needs, Jackson said. But there are other ways to close the global energy gap with fewer emissions. The new research provides a gauge for measuring some of the human impacts of one of them: reducing per capita energy use in what Jackson called energy profligate countries, while raising the rest of the worlds energy supply to comparable levels.

The new conclusions derive from statistical analysis of energy-use data for 140 countries from 1971 to 2018, as well as global data for nine metrics related to human well-being. Many of those metrics align with the United Nations Sustainable Development Goals, a set of objectives aimed at ending an array of inequities while taking the risks of climate change into account.

The researchers looked at the primary energy supply, which includes all energy production minus exports, international marine and aviation bunkers, and changes in the amount of fuel held in storage, for each of the 140 countries. They then separated out the total energy that goes into increasing well-being from the energy that is wasted or employed for other purposes, such as trade.

Recognizing that well-being is likely to be limited by multiple factors, including income and GDP, the authors examined whether per capita energy use could decline in some countries while maintaining quality of life.

Across most metrics, including life expectancy, infant mortality, happiness, food supply, access to basic sanitation services and access to electricity, the authors found performance improved steeply, then peaked with annual energy use averaging 10 to 75 gigajoules per person. Thats less than the 2018 world average of 79 gigajoules per capita, and, at the higher end of the range, about a quarter of the U.S. average of 284 gigajoules per person.

U.S. energy use per capita has fallen slightly since the late 1970s, largely because of improvements in energy efficiency, but it remains high in part because of the nations outsize demands for energy for transportation.

In most countries that consume much more energy than the global average, further increasing energy use per capita might only marginally improve human well-being, said coauthor Chenghao Wang, a postdoctoral scholar in Jacksons lab and also a research fellow at the Stanford Center for Longevity.

The new study reveals at least 10 countries punching above their weight, with greater well-being than most other countries using similar amounts of energy per capita. The high performers include Albania, Bangladesh, Cuba, Denmark, Finland, Iceland, Malta, Morocco, Norway and Sri Lanka.

Air quality stands apart from the other metrics examined by the authors, in that across 133 countries, it continued to improve with per capita energy use as high as 125 gigajoules. Thats on par with the annual per capita energy use of Denmark in 2018, and slightly higher than that of China. One reason may be that the early stages of energy development have historically been dominated by dirtier fossil fuels.

In the U.S., energy use rose steeply after World War II decades before federally imposed limits on pollution from tailpipes and smokestacks spurred improvements in the nations air quality. Wealthier countries like the U.S. tend to clean up their air only after they have built up wealth and the populace demands action, Jackson said.

Past research has shown that higher income doesnt necessarily lead to better and happier lives, said study co-author Anders Ahlstrm, a climate scientist at Lund University who worked on the research as a postdoctoral scholar in Jacksons lab at Stanford. Energy supply is similar to income in that way: Excess energy supply has marginal returns.

Co-authors are affiliated with Stockholm University, Princeton University and Jadavpur University.

This research was supported by Stanfords Center for Advanced Study in the Behavioral Sciences and the Stanford Center on Longevitys New Map of Life initiative.

To read all stories about Stanford science, subscribe to the biweeklyStanford Science Digest.

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Stanford study finds high energy use provides little benefit for health and well-being in richer nations - Stanford University News

Scientists De-Aged a Woman’s Skin Cells by 30 Years – The Daily Beast

Posted on April 18, 2022 by Prof Baldwin

While the Fountain of Youth is the stuff of legend, the search for a way to stop humans from aging is happening as we speakinside the laboratory.

In a study published in the journal eLife on April 8, scientists at Babraham Institute in the U.K. managed to de-age the skin cells of a 53-year-old woman by 30 years in a petri dish. Looking at age-related biological changes in the DNA, these genetically-modified younger cells appeared and behaved as any 23-year-old skin cell should. Notably, the team was also able to de-age the cells in less than two weeks.

The techniques used in this experiment have been around for the last few decades. However, with the woman's skin cells, the researchers managed to shave off time from the usually long process while also avoiding the problems reprogrammed cells can often run into, like inadvertently turning cancerous.

This kind of work is very important, Dr. Ivona Percec, a plastic surgeon and stem cell researcher at the University of Pennsylvania School of Medicine, who was not involved in the study, told The Daily Beast. And its one thats been sought out by many scientists in order to reverse or delay aging.

Most rejuvenation or regeneration research makes use of human stem cells, which have the unique ability to develop into any other type of cell our body needs, such as muscle and brain cells. Stem cells can also renew themselves over time and serve as an internal repair system, replacing lost or damaged cells during a persons lifetime. But stem cells are quite difficult to produce in the laband are often rejected by the body when used in different types of therapies.

To get around these hurdles, scientists have been creating their own lab-grown stem cells called induced pluripotent stem cells (iPSCs). They are created by taking any cell in our body and genetically editing it to resemble an embryonic stem cell, George Sen, a molecular biologist at the University of California San Diego who was not involved in the study, told The Daily Beast in an email.

To make their iPSCs, the Babraham researchers reversed the cellular clock on their 53-year-old skin cells by bathing them in a chemical solution that encourages the growth of proteins that reshape a cells DNA. To control how far they de-age the cells, the researchers allowed the bath to run for a little less than two weeks than the typical 50 days. Then they assessed the age of the skin cells by looking for age-related biological changes.

I remember the day I got the results back and I didn't quite believe that some of the cells were 30 years younger than they were supposed to be, Dilgeet Gill, a biomedical researcher at Babraham Institute and lead author of the study, told the BBC. It was a very exciting day!"

Young fibroblasts in the first image. The next two images are after 10 days, right with treatment. The last two images are after 13 days, right with treatment. Red shows collagen production which has been restored.

Ftima Santos

These newly minted young skin cells, called fibroblasts, produce collagen, which is a protein responsible for healthy joints and elastic skin throughout the body. When researchers cut through the cell layer (like how if you injure your skin), the fibroblasts moved into the gash quickly to fill it, unlike the older cells.

Though the findings are quite encouraging, were still some ways from seeing this new de-aging technique used in a clinical setting. Experts also have some lingering questions regarding how long exactly this rejuvenation lasts and whether the new technique actually improves a cells lifespan.

The authors only looked for a short period of time after [applying Yamanaka factors] but what happens once the cell has divided a few times? Does the molecular clock catch up? asked Sen. The authors also never tested whether the de-aged fibroblasts behaved as younger fibroblasts in live animal models. This question would need to be addressed before this can be used as therapy.

Whether this is the key to the Fountain of Youth remains to be seen.

Dr. Johann Gudjonsson, University of Michigan

Dr. Johann Gudjonsson, a dermatologist who studies inflammatory skin conditions at The University of Michigan and wasn't involved in the study, is also skeptical of the experiment.

Whether this is the key to the Fountain of Youth remains to be seen, Gudjonsson told The Daily Beast in an email. He explained that telomeres, which are the caps binding the ends of DNA and shorten as we age, didnt appear to improve with the new studys treatment. Therefore while the function and state of the cells are rejuvenated it may not mean that their lifespan has changed, he said.

Even if longevity and immediate clinical applications arent in the cards, this new study does offer an interesting proof of concept for future medical research and potentially combating aging.

If this process can be applied to other cell types, one can imagine rejuvenating that particular cell type and using it to restore an aged/failing organ, said Sen. I believe this line of research has a lot of potential and we are just starting to understand the rules of how to reprogram cells.

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Scientists De-Aged a Woman's Skin Cells by 30 Years - The Daily Beast

How to have a longevity mindset for anti-aging technology – Fast Company

Posted on April 18, 2022 by Prof Baldwin

The worlds billionaires arepouringmoney into age-reversal investments.

Last September, it came out thatJeff Bezos had invested in Altos Labs, a company pursuing biological reprogramming technology. Reprogramming is the scientific term for turning old cells young again. It was discovered in 2012 by Japanese scientist Shinya Yamanaka, who called it a potential elixir of life. The Nobel Prize in Medicine Committeeseemed to agree.

Bezosand Altosarent the only ones.

Theres Google-backedCalico Labs, also focused on longevity via reprogramming. AndLineage Cell Therapeutics, backed by BlackRock, Raffles Capital Management, Wells Fargo, and others.

Coinbase Co-founder and CEO Brian Armstrong recently invested in a company working to radically extend human healthspan using epigenetic reprogramming therapies. Altogether, the anti-aging industry isexpected to grow toover $64 billionby 2026, a 45% increase from its 2020 value ($44 billion).

So, why are billionaires like Jeff Bezos investing in age-reversal or anti-aging tech?

Because they have aLongevity Mindset.

One way to understand the Longevity Mindset is by looking at its opposite.

Most people take the aging process for granted. If theyre disciplined, healthy, and lucky, theyll get 20 or so years of youth, start declining in their 40s, and die sometime between 60 and 80.

They accept that life expectancy is 81.2 years for females and 76.4 years for malesnothing they can do, just take the lemons and make lemonade.

And who can blame them? Nearly every human institutiongovernments, the insurance industry, medicine, religionis organized around this mindset.

The anti-Longevity Mindset is: mortality is inevitable, youth is fleeting.

So, the Longevity Mindset is: mortality is avoidable, youth is extendable.

If that sounds shocking to you, youre not the only one. For years, scientists supporting a Longevity Mindset were shunned, and as a result longevity studies were tabled for fear of losing grant funding.

But medicine has evolved.

Weve entered a period ofexponential medicine: Innovations like genome sequencing, RNA transcriptomics, Wnt pathway modifiers, vaccines, CRISPR, liquid biopsies, CAR-T cells, Gene Therapy, exosomes, and stem cells are just a sampling of the technologies that the worlds billionaires are fast-tracking.

Free from the narrow paradigm of academia, these scientists earn as much as five to tentimesa top professors salary by working for Altos and others.

Ultimately,aging is a diseasea disease that many of the most powerful people on the planet believe can be slowed, stopped, even reversed.

Thats the spirit of the Longevity Mindset.

Examine and assess the six basic areas of life that everyone, whether you live on the margins or in a mansion, must negotiate.

Laying the foundation of a Longevity Mindset doesnt take any capital investment. Everyone has beliefs, a media diet, and a community. Everyone has to sleep, eat, and move around.

In the background, billionaires like Bezos are accelerating the industry, working to bring cutting-edge longevity tech to human beings.

When they do, will you be ready?

This article originally appeared in Minutes and is reprinted with permission.

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How to have a longevity mindset for anti-aging technology - Fast Company

Gigantism Is a Never-Ending Temptation for Engineers and Designers – IEEE Spectrum

Posted on December 25, 2021 by Prof Baldwin

There is a fundamental difference between what can be designed and built and what makes sense. History provides a lesson in the shape of record-setting behemoths that have never since been equaled.

The Egyptian pyramids started small, and in just a few generations, some 4,500 years ago, there came Khufus enormous pyramid, which nobody has ever tried to surpass. Shipbuilders in ancient Greece kept on expanding the size of their oared vessels until they built, during the third century BCE, a tessarakonteres, with 4,000 oarsmen. That vessel was too heavy, too ponderous, and therefore a naval failure. And architect Filippo Brunelleschis vast cupola for Florences Cathedral of Santa Maria del Fiore, built without scaffolding and finished in 1436, was never replicated.

The modern era has no shortage of such obvious overshoots. The boom in oil consumption following the Second World War led to ever-larger oil tankers, with sizes rising from 50,000 to 100,000 and 250,000 deadweight tonnes (dwt). Seven tankers exceeded 500,000 dwt, but their lives were short, and nobody has built a million-dwt tanker. Technically, it would have been possible, but such a ship would not fit through the Suez or Panama canals, and its draft would limit its operation to just a few ports.

The economy-class-only configuration of the Airbus A380 airliner was certified to carry up to 853 passengers, but it has not been a success. In 2021, just 16 years after it entered service, the last plane was delivered, a very truncated lifespan. Compare it with the hardly puny Boeing 747, which will see its final delivery in 2022, 53 years after the planes first flight, an almost human longevity. Clearly, the 747 was the right-sized record-breaker.

Of course, the most infamous overshoot of all airplane designs was Howard Hughess H-4 Hercules, dubbed the Spruce Goose, the largest plane ever made out of wood. It had a wingspan of nearly 100 meters, and it was propelled by eight reciprocating engines, but it became airborne only once, for less than a minute, on 2 November 1947, with Hughes himself at the controls.

Another right-size giant is Fords heavy and powerful F-150, now in its 14th generation: In the United States, it has been the bestselling pickup since 1977 and the best-selling vehicle since 1981. In contrast, the Hummer, a civilian version of a military assault vehicle, had a brief career but is now being resurrected in an even heavier electric version: The largest version using an internal combustion engine, the H1, weighed nearly 3.5 tonnes, the electric Hummer, 4.1 tonnes. I doubt we will see 14 generations of this beast.

But these lessons of excess carry little weight with designers and promoters pursuing record sizes. Architects discuss buildings taller than a mile, cruise ship designers have already packed nearly 7,000 people into a single vessel (Symphony of the Seas, built 2018) and people are dreaming about much larger floating cities (perfect for spreading the next pandemic virus). There are engineers who think that we will soon have wind turbines whose more than 200-meter diameter blades will fold, like palm fronds, in hurricanes.

Depending on where you stand you might see all of this either as an admirable quest for new horizons (a quintessential human striving) or irrational and wasteful overreach (a quintessential human hubris).

This article appears in the January 2022 print issue as Extreme Designs.

From Your Site Articles

The plight of Tamils of Indian origin in Sri Lanka – The New Indian Express

Posted on December 25, 2021 by Prof Baldwin

In a highly commendable move, the Rajapaksa brothers, who hold the reins of power in Sri Lanka, invited the UN Human Rights Council dealing with contemporary forms of slavery to visit Sri Lanka, study the living conditions of the most exploited sections of society like people working in garment firms in export promotion zones, tea plantation workers and migrants. Sri Lanka is the first country in South Asia to take this imaginative initiative. Will other countries in the region emulate the Sri Lankan example?Tomoya Obokata, UN Special Rapporteur, visited Sri Lanka between November 26 and December 3 for an on-the-spot study of the problems and met a cross section of workers, government officials, trade union leaders and NGOs involved in the subject. The rapporteur presented the preliminary findings in a meeting held on November 26. The final report would be submitted to the UN in September 2022.The workers in the tea plantations are of Indian Tamil origin. Apply any yardstickper capita income, living conditions, longevity of life, educational attainments and status of womenthey are at the bottom of the ladder. The UN Special Rapporteur has highlighted: Contemporary forms of slavery have an ethnic dimension. In particular, Malaiyaha Tamilswho were brought from India to work in the plantation sector 200 years agocontinue to face multiple forms of discrimination based on their origin. In 2017, Sri Lanka celebrated the 150th anniversary of its tea industry. The government and the planters organised a number of seminars and conferences to highlight the role of the tea industry in the economy, how to increase production in the sector and how to modernise it. The Institute of Social Development in Kandy was the only organisation that convened a seminar on those who produce the Two leaves and a Bud (novel written by Dr Mulk Raj Anand) that brings cheer early in the morning to millions across the world.The contrasting lives of the planters and workers should be highlighted. Given below are two quotations that describe the contrast. The BBC, in 2005, telecast a documentary titled How the British Reinvented Slavery. The documentary portrays the lives of the planters as follows: You can sit in your veranda, and sip the lemonade and be fanned by a servant and have your toenails cut at the same time by some coolie, and you can watch your labourers working, you could sleep with any woman you wanted, more or less everything was done for you from the time you wake up and the time you went to bed. People looked after you, people obeyed you, people are afraid of you, your single word as a plantation owner could deny life.Vanachirahu, a young poet from Malaiyaham, gave expression to the innermost feelings of his people in times of communal troubles. In a poem titled Dawn, the poet writes: Our nights are uncertain, dear, let us look at each other, before we go to bed. This may be our last meaningful moment. Finally press your lips on the cheeks of our children. Then let us think about our relatives for a moment. Lastly let us wipe our own tears.The most important feature of the Malaiyaha Tamils is the sharp decline in their population. At the time of independence in 1948, they were more in number than Sri Lankan Tamils. Because of the two agreements signed in 1964 and 1974 between Colombo and New Delhi, and repatriation of a large number of people as Indian citizens, their number declined. Today, according to census statistics, they number only 5.5% of the population.For the first few decades after independence, the major problem confronting the Indian Tamil population was the issue of statelessness. With a judicious mix of parliamentary and extra-parliamentary struggles, the community, under the leadership of Savumiamoorthy Thondaman, was able to extract citizenship rights from a recalcitrant Sinhalese-dominated government. All those born in Sri Lanka after October 1964 were granted citizenship, which also included the residue of the Sirimavo-Shastri pact, yet to be repatriated to India. With the introduction of the proportional system of representation under the 1978 Republican Constitution, the community was able to send more representatives to Parliament.The community is now engaged in a struggle for equality and dignity. The living conditions are improving but much more remains to be done before they can enjoy the status of perfect equality. First and foremost, human rights violations continue to take place. Though the political parties representing the Malaiyaha Tamils never subscribed to the demand for a separate state, they were subjected to vicious and savage attacks by lumpen sections of Sinhalese in 1977, 1981 and 1983. I happened to be in Hatton after the Bindunewa massacre in 2006. Indira, a young lady, confided that she was scared to move around Hatton because of insecurity. She contrasted that to her life with her brother in Perambur, Chennai, where she could go without any fear for late-night film shows. Second, the tea workers daily wage is around 1,000 Sri Lankan rupees, which is not even sufficient to meet their daily needs. Many, therefore, absent themselves from the plantations and go to work in vegetable farms where they are able to get double the wages, in addition to breakfast and lunch. Finally, while every boy and girl goes to school, there are many dropouts. Very few enter the university level. I was associated with the University of Peradeniya as a SAARC Professor for International Relations in 2006. In the final-year BA class, in Tamil medium, there were 10 students, of whom eight were Muslim girls, a boy was from Batticaloa and a girl from the plantation area. In the same year, the number of teachers from the Indian Tamil community in the university was less than 10.In his plan of action for three years, Sri Lankan High Commissioner Milinda Moragoda has highlighted that there should be more educational exchanges between the two countries. For instance, the Chennai Centre for Global Studies is very keen to step into the scene and assist the Tamil children, especially from the hill country, to come to India for secondary and college education, and is prepared to meet all their expenditures and also offer them scholarships. The community can come up only if they have good value-based education. Tamil Nadu can play a benign role in this direction.The transformation from Thottakattan (barbarian from the plantations), a contemptuous term used by Jaffna Vellalars, to the noble appellation Malaiyaha Tamil is an illustration of the qualitative change that has taken place in the hill country. But much more remains to be done before they become equal citizens enjoying equality of opportunity. Let me conclude with a poem written by M A Nuhman whom I had the privilege to know at the University of Peradeniya: Where there is no equality, there is no peace, where there is no peace, there is no freedom, these are my last words, equality, peace and freedom.

V SuryanarayanSenior professor (retd), Centre for South and Southeast Asian Studies, University of Madras(The author was the Founding Director of the Centre in the University of Madras)(suryageeth@gmail.com)

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The plight of Tamils of Indian origin in Sri Lanka - The New Indian Express

Big Review Confirms Power of Fasting Diets for Weight Loss – HealthDay News

Posted on December 25, 2021 by Prof Baldwin

TUESDAY, Dec. 21, 2021 (HealthDay News) -- Intermittent fasting is all the rage due to its potential health benefits, and now a new review shows this style of eating really does produce weight loss and may even improve certain markers of heart health.

Intermittent fasting is an umbrella term for several diets that alternate between feasts and fasts. The 5:2 diet involves eating normally five days of the week and restricting your calories on the other two days. Alternate-day fasting calls for a fast day-feast day-fast day pattern. In contrast, time-restricted eating refers to eating only during specific time windows each day.

"The new study demonstrates that the different forms of intermittent fasting, i.e., alternate-day fasting, the 5:2 diet and time-restricted feeding, are all effective weight loss interventions for people with obesity," said study author Krista Varady, director of the Human Nutrition Research Unit at the University of Illinois, in Chicago.

"Intermittent fasting may be an effective means of lowering heart disease risk by decreasing blood pressure, low-density lipoprotein [LDL] or 'bad' cholesterol, and triglycerides," she said. What's more, these diets may help prevent type 2 diabetes by lowering insulin resistance and fasting insulin levels.

Most of these benefits likely stem from weight loss.

"All of these regimens induce a calorie restriction of 15% to 30% daily, which results in weight loss," Varady said. "When an obese person loses weight, they almost always see reductions in LDL cholesterol, triglycerides, blood pressure and insulin resistance."

For the review, the researchers analyzed 11 studies that comprised 130 trials of various intermittent fasting regimens. When the investigators looked at all of the studies as a whole, intermittent fasting did produce weight loss and improvements in risk factors for heart health. However, only alternate-day fasting and the 5:2 diet resulted in a clinically significant weight loss of more than 5%, the study showed.

The findings were published online Dec. 17 in JAMA Network Open.

So, should you or shouldn't you jump on the intermittent fasting bandwagon, and if you do, which method is right for you?

Two experts who were not involved with the study agreed that it's too early to make any blanket recommendations.

"The study provides strong evidence that some, but not all, of the regimens result in weight loss and related decreases in body mass metrics and improvements in cardiometabolic risk factors, such as cholesterol levels, blood pressure and measures of insulin resistance," said Benjamin Horne. He is the director of cardiovascular and genetic epidemiology at the Intermountain Heart Institute in Salt Lake City, Utah.

The methods in this study that showed the most profound benefits tend to be the most difficult to follow, he noted. "Future studies should evaluate the ability of the average person to adhere to these regimens, because it is unclear that they are sustainable over the long term," Horne said.

The study also could not address if intermittent fasting reduces heart attacks or strokes or extends longevity. "It is unknown whether the average person can adhere to any of the four intermittent fasting regimens for a long enough period of time [years or decades] to affect those outcomes," Horne added.

And importantly, he asked, can weight loss can be sustained without continuing the regimen?

There are also safety considerations. "The hype surrounding intermittent fasting may be leading to harms to unsuspecting people who want to achieve better health," Horne explained, "especially people with diagnosed chronic diseases and asymptomatic health conditions."

New York City dietician Robin Foroutan isn't a fan of the difficult-to-stick-with intermittent fasting regimens that showed the greatest benefits in this study.

"I only recommend time-restricted eating and fasting-mimicking diets," said Foroutan. Fasting-mimicking diets work by tricking your body into thinking that you're fasting even though you're still eating. These methods are easier to follow so people are more likely to stay the course.

The bottom line? Always talk to your doctor before starting a new eating regimen, she said.

More information

The Academy of Nutrition and Dietetics has more on the various types of intermittent fasting.

SOURCES: Krista Varady, PhD, professor, nutrition, and director, Human Nutrition Research Unit, University of Illinois, Chicago; Robin Foroutan, MS, RDN, dietitian, New York City; Benjamin Horne, PhD, director, cardiovascular and genetic epidemiology, Intermountain Heart Institute, Salt Lake City, Utah; JAMA Network Open, Dec. 17, 2021, online

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Big Review Confirms Power of Fasting Diets for Weight Loss - HealthDay News

Crypto experts break-down their 2022 industry predictions – Yahoo Finance

Posted on December 25, 2021 by Prof Baldwin

As the final presents are bought and wrapped, and the sherry begins to flow, one question is hot on the tongue of families world-wide this festive season: When will you put down your phone and stop checking crypto?

Little do they understand the woes of a turbulent month of bearish Bitcoin divergence, nor do they understand the endless possibilities of what could happen next only one thing is certain its Christmas and its time to enjoy it.

In the festive spirit, Coin Rivet has compiled a barometer reading of experts crypto market sentiments for 2022 so you dont have to this holiday season.

For many of the experts, Web 3.0 has been veritably left out this year, although the significance of the sub-sector will continue to grow into 2022. Web 3.0 is focused on extending user utility in a decentralised capacity, and naturally this will place users as the central focus within the emergent technology.

Julian Sawyer, CEO of Bitstamp the worlds longest-standing crypto exchange, was keen to assert the viewpoint that customer interaction is a vitally human component of high tech systems.

In crypto especially, we use tech to drive our products and our business, however, our customer service is a space where we can be human, he explained.

The technical jargon in our industry is what causes customers to get confused or frustrated and we strive to be a place where people can enter the market with confidence.

In 2022, the focus should be on innovating products that provide a better customer experience, not to use the technology to separate potential customers out. As more people talk about metaverses, cyborgs and alternative realities, Im betting that people are going to want to talk to real people.

And Matt Zhang, the Founder of Hivemind Capital (a $1.5bn crypto fund built on the back of Algorand), concurs with this opinion adding the decentralised autonomous organisations (DAOs) will revolutionise user engagement in the future of industry, and the tech sector will be first.

Story continues

In 2022, we will see more companies explore alternative governance models using DAO and blockchain technology, highlighted Zhang.

This trend will be particularly obvious in the consumer tech sector, where consumers feedback on products shapes the longevity of the companies that provide those services in the first place.

Many have been quick to label 2021 as the year of institutional crypto adoption, however, the experts seem to suggest this moment is far from over amid economic concerns and the current state of adoption.

Diogo Monica, President of Anchorage Digital the first federally chartered crypto bank, explained how institutional adoption of crypto represented a generational wealth transfer that is evidenced by a maturing multi-asset class industry.

Its no longer just speculative investing in Bitcoin or Ethereum; were talking about NFTs, DeFi, remittances, capital preservation, and many other verticals, explained Diogo.

Well also see Bitcoin continue to act as a hedge against inflation, which continues to be important as rates rise.

Finally, banks and fintechs will continue to add support for crypto services across the board, as 2021 has shown us that the massive transfer of wealth to the millennial generation is well under way, and their needs are much different than their predecessors.

And Matthew Gould, CEO of Unstoppable Domains, a leading NFT domain name platform, highlighted how the standout performance of stablecoins in 2021 demonstrated the genuine utility of crypto to individuals and banks alike.

Stablecoins had a breakout year in 2021, reaching a market cap of over $152 billion. I predict that by 2024, the total market cap of stablecoins will reach $1 trillion, said Gould.

The biggest thing thats going to win over crypto skeptics is utility, and stablecoins are the best example of this stablecoins represent everything good about crypto without the speculation or the FOMO aspect, especially when you look at regulated stablecoins like USDC.

Kosala Hemachandra, the CEO of MyEtherWallet, believes that 2022 will deliver a new wave of NFT hype as the real use-cases finally emerge and come to fruition.

In 2022, Im looking forward to physical items such as car titles and house deeds becoming NFTs, said Hemachandra.

This will introduce a whole new game to crypto. NFTs are easy to understand, similar to collectibles in the real world.

Every wave of NFTs brings something new to the table, which means we havent even seen the full glory of NFTs yet.

Speaking to the metaverse, Colin Pape (Founder of Presearch), argued 2022 would be a battleground year that would see centralised entities and decentralised networks duke out ownership of online interactions.

Our collective shift towards the metaverse will continue to accelerate. This raises major concerns about privacy, explained Pape.

Its not just your Facebook account, its a shift to everything being online. Centralised companies like Facebook, Google, and Amazon will vie for control over our digital lives, so we need to focus on building a future that is a net positive.

The best way to do this is by offering alternatives to big tech platforms. As we shift towards a future in the metaverse, we should prioritise decentralised, open-source platforms, and educate people on alternatives to the centralised big tech platforms they use every day.

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Crypto experts break-down their 2022 industry predictions - Yahoo Finance

What was the Mossad director thinking? – Haaretz

Posted on December 12, 2021 by Prof Baldwin

Here is what Mossad director David Barnea said: Iran will never have nuclear weapons not in the coming years, and not ever. This is my pledge; this is the Mossads pledge.

I couldnt believe my ears. I wanted to see it with my own eyes. A video of this official event shows the president lighting Hanukkah candles, the prime minister spouting historical nonsense and the Mossad director spouting clichs. But the sentence quoted above nothing. Its disappeared.

Presumably it was left on the cutting room floor in the hopes it would be forgotten. Nevertheless, theres no doubt the Mossad chief said what he did, and his comments deserve to be discussed.

First, the Mossad director needs to grasp a painful truth he doesnt decide anything. Not whether Iran will have nuclear weapons, and not whether Iran wont have nuclear weapons. Because what can you do, the Mossad director only belongs to the servant class, not the decision-making class. And like all service providers (including secret services), the Mossad director is authorized to do only what hes told to do.

Heres an incident from the past that proves the point. Some decades ago, the heads of the secret services were ordered to assist the (evil) secret services of Irans then-ruler by providing equipment and training. And of course, they obeyed.

And thats what will happen in the future as well. If any Mossad director, including the current one, is again asked to help an Iranian tyrant (perhaps because of his support for the settlements or something like that), he too will obey. After all, thats the essence of his job obedience. Perhaps not blind obedience, but definitely squinting obedience.

Moving on, the Mossad director also declared that his pledge was forever. Thats a bit presumptuous, isnt it? Especially coming from someone whose term will end in another five and a half years at most.

His lifespan to everyones great regret, of course also isnt eternal. In just another 55 years, hell turn 120. And that, as everyone knows, is the upper limit God set for human longevity, according to Jewish tradition.

But its still permissible to hope that the world will go on for a few years after that. Therefore, the Mossad directors personal pledge that Iran will never have a nuclear bomb is about as coherent and impressive as a personal pledge by his Iranian counterpart that Israel will never have a nuclear bomb.

Moreover, the Mossad is undoubtedly an efficient assassination enterprise, and assassinations are very good for the ego, morale and the enthusiastic media. But they dont produce any real benefits. The Mossad also has a successful dirty tricks department that knows how to plant viruses in electric razors, disrupt the timetables of cable cars and even cause centrifuges to spin out of control. This department, too, is good at tactical annoyances but fails to produce any strategic benefits.

By contrast, the Mossad and its ilk around the world have been consistent failures for many years at anything connected to actual intelligence and strategic analysis. As proof, consider the collapse of the Soviet bloc, the fall of the Berlin Wall, the Yom Kippur War, the first intifada, the Iraq war, the attack on the Twin Towers, the war in Afghanistan and more and more and more resounding, embarrassing strategic failures that have escaped my gaze. But the top-secret operations are all really terrific.

Therefore, the Mossad director should try to enhance the functioning of his modesty gland and practice lowering his nose in front of a mirror. That might help him later on.

In his defense, I will say one thing only. His remarks were so arrogant, conceited, aggressive and inflated that together they create a frighteningly accurate reflection of Israel in 2021 arrogant, conceited, aggressive and inflated. And for that, he has my thanks.

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What was the Mossad director thinking? - Haaretz

The grandmother hypothesis: How humankind owes its success to matriarchs – EL PAS in English

Posted on December 25, 2021 by Prof Baldwin

The worlds great civilizations were forged contrary to family instinct. The Chinese created an objective system to select civil servants who would put the states interests above those of their families; the Christian world prohibited marriage among its clergy with similar intent and the Ottomans set up an administrative elite made up of foreign slaves who could not pass on the privileges they acquired during their lives to their children. All of this was designed to limit the impulse to put family interests above general ones.

However, these measures had limited success. There were archbishops who fathered children and the Ottoman Janissaries eventually reversed the prohibition on passing power to offspring. Family always wins out, perhaps because the famiy instinct is so ingrained in human nature.

Children hold incredible potential, but for it to be developed they require a prolonged and intensive care that frequently their parents are unable to meet. We are dependent for many years after birth and it is likely that this has encouraged some typical traits in the species. Recently, the journal of the Proceedings of the National Academy of Sciences of the United States of America (PNAS) published a study carried out by Harvard University researchers that suggested that active grandparenting favored humans maintaining physical fitness long after their prime reproductive years and that also explained why exercise is so beneficial in later life. This role of grandparents as the pillars of parenting could be the reason why women, contrary to what occurs in practically every other animal species, can live for decades after losing their reproductive ability.

The success of species at large is reproductive, but ours achieved success with an increase in non-reproductive time

The grandmother hypothesis was developed through the study of older female members of the Hadza people of northern Tanzania. Kristen Hawkes, of the University of Utah, observed that these women were extremely active in gathering food that they then shared with their daughters. This generosity was conducive to them being given more grandchildren. Years later, an analysis of pre-industrial societies in Canada and Finland reached similar conclusions. At the beginning of the 17th century in Quebec, ecclesiastical records made it possible to determine that women who lived in the same parish as their mothers on average had 1.75 more children than their sisters who lived further away. In Finland, the results showed a similar tendency, as long as the grandmother was not over the age of 75.

Natural selection would have favored longevity in species made up of dependent individuals, says Mara Martinn Torres, director of the Spanish National Center for Research on Human Evolution (Cenieh). Fragile human babies and their huge brains would have had more chance of survival and development thanks to their grandmothers and in turn their efforts would have given our species the reward of a much longer and healthier life span than that of our close relatives, such as chimpanzees. These animals, which remain fertile their whole lives, suffer serious physical decline in their 30s and rarely make it to 40.

The paleoanthropologist Marina Lozano notes that it is estimated this essential function in grandmothers began with Homo erectus, a species that emerged around 1.8 million years ago. It is the first species of our genus to have a similar structure and life cycle to ours, with a more dilated growth in which lactation and childhood are separated and we have another stage, adolescence, says Lozano, of the Catalan Institute of Human Paleoecology and Social Evolution.

It is probable that grandmotherly help began with human species that predated our own, but it seems that around 50,000 years ago cultural transformations occurred that intensified the phenomenon. According to calculations by Central Michigan University researcher Rachel Caspari, based on the fossilized teeth of 768 individuals who lived over the past three million years, among Homo sapiens during the Upper Paleolithic, the number of individuals surviving until an age when they could become grandparents was greatly increased. In that period, for every 10 Neanderthals who died between the ages of 15 and 30, only four lived longer. Among Homo sapiens, that number rose to 20.

Sapiens had already been on the planet for tens of thousands of years, but around 60,000 years ago something happened that increased their capabilities. There is a palpable cultural sophistication; it is the age when hybridization with Neanderthals took place and it also when there was a migration out of Africa that coincided with migrations within the continent, says Antonio Rosas, director of the Paleoanthropology Department at the National Museum of Natural Sciences in Madrid. This period was unique, something was happening and it is clear that it was changing social and cultural organization, something that would also change the value of grandparenting.

This capacity for cultural adaptation increased life expectancy among Homo sapiens, leading to larger numbers of grandparents in the population. Women are born with a number of egg cells that are distributed during their fertile years. On increasing life expectancy, there may have been a change that also increased the number of egg cells to maintain fertility for longer, but the presence of grandmothers without their own children to look after offered other advantages. Human females are among the few animal species that cannot reproduce until the end of their lives. The others are cetaceans with teeth, such as pilot whales, beluga whales, narwhals and orcas, which also have large brains.

During that period of reinforcing cultural and biological transformation, greater life expectancy would have been a driving force for the species, which after many millennia of survival was on its way to an unprecedented global expansion. Increased life expectancy allows for an overlapping of generations that makes it possible to accumulate exceptional wealth. The Australopiths never knew their grandparents. Being able to bring together three generations in one home is a hive of knowledge that other species do not have. Humans do not have to start from zero with every generation. That completely alters the value of older people, says Martinn Torres.

These societies, in which grandparents gained more and more importance, were responsible for artistic creations such as the cave paintings at Altamira in Spain and Lascaux in France. They were able to improve their hunting techniques and survived and prospered during the Ice Age in Europe, during which the Neanderthals disappeared. This peculiar species, that had been so fragile for so long, achieved its success in an almost paradoxical way, says Martinn Torres. The success of species at large is reproductive, but ours achieved success with an increase in non-reproductive time.

The developmental needs of the brain, the organ where intelligence resides, but above all the social skills of humans, changed other traits of human biology that at the same time reinforced cultural changes that transformed the planet. The childcare input of grandparents was one of the traits that defined human singularity. As on other occasions, the strength of the species was to be found among some of its weakest members.

English version by Rob Train.

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The grandmother hypothesis: How humankind owes its success to matriarchs - EL PAS in English

Longevity and Anti-Senescence Therapy Market 2021 Size, Status and Global Outlook Acorda Therapeutics, Calico Life Sciences, Human Longevity Inc.,…

Posted on June 28, 2021 by Prof Baldwin

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Longevity and Anti-Senescence Therapy Market 2021 Size, Status and Global Outlook Acorda Therapeutics, Calico Life Sciences, Human Longevity Inc.,...

Why ‘Sunny’ is the greatest sitcom of all time – The Bona Venture

Posted on December 12, 2021 by Prof Baldwin

BY TUCKER REILLY, MANAGING EDITOR

Last week, the FX sitcom Its Always Sunny in Philadelphia premiered its 15th season, officially marking it as the longest running live-action sitcom in US history. The secret to the series longevity lies in its strong cast of characters, clever dialogue and constant boundary-pushing humor, which has allowed Sunny to garner an ever-increasing cult audience over nearly two decades. Additionally, the show has continued to produce quality content throughout its entire run, not suffering from the late season fatigue of many other sitcoms. With its unique comedic genius and historical precedent, Its Always Sunny should be considered the greatest American sitcom of all time.

Like many sitcoms, Sunny is based on a simple premise: five friends run a bar in Philadelphia, concocting schemes and settling scores with the local population. Unlike its thematic predecessor Cheers however, Sunny endeavors from the start to prove that its core cast are the absolute worst people imaginable. In the second season alone, our core five make a fake terrorist threat video, get addicted to crack cocaine, solicit bribes from local politicians and start a deadly Vietnamese gambling ring in the basement, among other crimes. The genius of Sunny lies in this darkness, in showing the viewer each characters rock bottom, then revealing that rock bottom is actually a cliff. Often the world around them acts as a universal straight man to the gangs antics, although Sunny does occasionally relish in finding someone even crazier than its own characters.

One of the defining features of Sunnys longevity is the shows acceptance of change, in contrast to the sitcom norm of status quo. When Dennis (Glenn Howerton) and Dee (Kaitlin Olson) get addicted to crack cocaine or suffer heart attacks (on separate occasions), they remain encumbered with these problems, although the culmination of their sins make each but a single aspect of chaos within the overall storm. Frank Reynolds (Danny DeVito) enters the series as a disciplined, business-savvy father figure to the group, who gradually devolves into a near-animalistic train wreck of a human being over time. Characters have children, gain and lose dramatic amounts of weight, suffer permanent afflictions and occasionally die. Sunny understands that its characters are not a mere collection of gimmicks, however, and molds its comedy around the irreplaceable actors themselves.

Its Always Sunny is an inherently character-driven comedy that mercilessly lambasts and pities its characters in equal measure. Many episodes of the show function like car wrecks, locking viewers into the sordid spectacle, while acknowledging the human flaws at each characters center. And more often than not, there is something profound there: we are not these people, yet we understand where their fears, desires and insecurities come from before they are turned up to 11. We want to see them win or better themselves but crave the inevitable implosion of their despicable actions. The snowball rolls on, keeping us firmly stuck within an ever-expanding web of degeneracy.

It is also important to emphasize the exceptional talent brought to Its Always Sunny by the cast and writing staff, who happen to be one in the same. The series core group of Rob McElhenney (the shows creator), Charlie Day, Kaitlin Olson, Glenn Howerton and Danny DeVito have built larger-than-life characters around their own strengths and eccentricities, sharply refined over time. The casts familiarity, mixed with Sunnys trademark rapid-fire dialogue, have allowed them to make nearly every scenario comedically valuable, while pushing the boundaries of the show to new heights. A key factor in this development has been creative freedom: due to the shows relatively low profile on FX, McElhenney and co. have been allowed to stretch the series into strange new directions largely without restriction. While some creative decisions such as the shows ironic use of blackface have been poorly received, Sunny has never lacked nuance in its satire. Its Always Sunny is a unique and terrible creation developed by a singular set of people, consistently sustaining itself for over 15 years (even though we all know seasons five through nine are the best, of course). It deserves, without a doubt, a seat at the table as the greatest American sitcom of all time.

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Why 'Sunny' is the greatest sitcom of all time - The Bona Venture

Where Is the Endgame in Chess Experts’ Visual Memory Abilities? – University of Texas at Dallas

Posted on June 28, 2021 by Prof Baldwin

Chess experts are known for their remarkable ability to recall configurations of chess pieces on a board. For decades, neurological experts have investigated how this memory functions and whether it can be applied to information beyond the gameboard.

To further probe this topic, researchers from The University of Texas at Dallas Center for Vital Longevity (CVL) turned to the UTDallas chess team. Since the chess programs inception in 1996, 24 Grandmasters and International Masters have played for the UTDallas team, which has competed in the Presidents Cup known as the Final Four of College Chess in 17 of the last 21 seasons.

Dr. Chandramallika Basak

The researchers tested 14 chess team members, along with 15 chess novices, on rapid-fire processing of visuospatial information in working memory.

Their findings, published June 14 in Memory and Cognition, help pinpoint the strengths and limitations of the subjects recall framework and how that framework can be applied to human cognition in general.

Prior studies have shown that chess experts advantage in visual memory is limited to chess pieces on chess boards, said corresponding author Dr. Chandramallika Basak, associate professor of psychology in the School of Behavioral and Brain Sciences. We wanted to see whether the expertise generalizes beyond chess pieces to unfamiliar, new stimuli, and where does this expertise break down for immediate memory.

Chess masters visual short-term memory for arrangements that can occur in chess has been of particular interest to cognitive scientists, said Basak, director of the Lifespan Neuroscience and Cognition Laboratory.

Its almost like chess experts have snapshots of these positions they demonstrate remarkable visuospatial working memory, given that the information is presented for less than half a second, she said. But is it driven by the visual aspects or spatial aspects of what they saw? Or a combination of both?

Evan T. Smith, a UTDallas cognition and neuroscience doctoral student, is the papers lead author. He described the difference between working and long-term memory as analogous to the gap between whats on top of your desk and whats filed away in a cabinet.

Evan T. Smith

The existing theory is that chess players have so thoroughly memorized and categorized board configurations that their long-term memory for this information functions like working memory, he said.

The researchers collaborated with Jim Stallings, director of the UTDallas chess program, to bring test subjects on board from the team.

Dr. Basaks study varies from other chess studies done with youngsters, Stallings said. This study goes directly to chess expertise and working memory. I look forward to sharing the results with the chess community.

The control group included UTDallas students of similar age and education level to the chess players who had never formally learned how to play chess.

In each test, participants saw a two-dimensional chessboard with a number of pieces displayed for three-tenths of a second. After a one-second pause, they saw a second chessboard and had to decide if there had been a change.

The tests were conducted with standard chess pieces and with novel, unfamiliar symbols. Basak said that this switch helped to determine if the chess players memory abilities were domain specific to chess or domain general to a wider range of objects.

One series of tests asks about changes in location; the second asks if the objects the pieces themselves have changed, Basak said. A third test incorporates changes in location or changes in object, or both, or no change at all. Finally, the grid of the board is removed.

The researchers found that while both chess experts and novices performed better with chess stimuli than with the unfamiliar symbols, the experts, for the most part, outperformed the control group for both chess stimuli and for the new objects particularly when detecting positional changes.

Section A of this figure from the Memory and Cognition article shows how each trial works: An initial configuration appears for three-tenths of a second, followed by a one-second pause. The three different trial types then could change an objects identity, location, or both. Section B shows the chess stimuli and novel stimuli used. Section C shows a trial with the grid removed.

When changing the identity of the objects, however, but not location, the chess players advantage was limited to the chess pieces. They performed no better than the control group at remembering when the identity of the novel symbols changed.

You would expect that this advantage that chess players have is related to a familiarity with the chess pieces or the chess players expectation of what they are about to see, Basak said. But results from our study say otherwise. It seems like the chess players can rapidly process a chessboard-like layout in a very holistic manner, like the brain does with faces. The next step in our research may be to do a functional MRI study to see if the face-processing regions of the brain are also used for chess.

The experiments also were split into tests using fewer than four pieces which is within the normal limits of an average persons focus of attention and five to eight pieces. With the larger number of pieces, long-term memory should come into play. The chess experts performed better than the controls in the tests with more pieces.

We observed an eight-item working-memory capacity for chess experts, Basak said. We assume that ties back to the idea that chess players are viewing the board and the set of positions as a single object, as they would recognize a face.

The grid-versus-no-grid portion of the study something that Basak said has not been examined before produced some of the more striking results.

The grid is the linchpin that supports the scaffolding of this memory structure, Smith said.

Basak added: Any expertise-related advantage disappeared in the absence of the chessboard display. It appears to be essential, acting as a road map, a familiar framework to aid the memory.

Collectively, the results indicate that visuospatial memory advantages associated with chess expertise extend beyond chess stimuli in certain circumstances, particularly to position changes with between five to eight items. But the grid appears to be necessary for experts to leverage these advantages.

We cannot generalize our findings beyond what we tested, so we cannot claim, based on our data, that chess experts will be better at studying for school, Basak said. But their advantage does go beyond chess pieces, provided the grid remains. We believe this indicates that experts are automatically encoding spatial-relational information.

Other contributors to the research were Dr. Daniel Krawczyk, UT Dallas professor of psychology, holder of the Debbie and Jim Francis Chair in Behavioral and Brain Sciences, deputy director of the Center for BrainHealth and associate professor of psychiatry at UT Southwestern Medical Center; and Dr. James Bartlett, a distinguished scholar in cognitive neuroscience and cognitive psychology and a longtime UTDallas faculty member who played a key role in the beginning of the project. Bartlett died in 2019.

Jim Bartlett played a big role in designing the experiments and in bringing Jim Stallings and the chess team on board, Basak said. He was a mentor, friend and valued collaborator, and we dedicate this publication in honor of his memory.

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Where Is the Endgame in Chess Experts' Visual Memory Abilities? - University of Texas at Dallas

Watson professor named ASME fellow for three decades of electronics packaging innovations | Binghamton News – Binghamton University

Posted on November 11, 2021 by Prof Baldwin

Moores Law packing twice as many transistors on the silicon every 18 months has driven our technological revolution over the past 50 years. The processing power that once took entire buildings of computer banks now fits into the palm of your hand, giving smartphones access to all the knowledge of the internet.

In the past few years, though, as semiconductor manufacturers are making circuits measured in single nanometers, Moores Law appears to be coming to an end. (For scale, 1 nanometer is a billionth of a meter, smaller than a strand of human DNA.)

To accommodate consumer expectations for even smaller and powerful devices, researchers are increasingly looking to electronics packaging a term that encompasses everything apart from the chips themselves. The field always has been important to ensure the proper functioning and longevity of devices, but now it is more critical than ever.

Professor SB Park a faculty member in the Thomas J. Watson College of Engineering and Applied Sciences Department of Mechanical Engineering has researched electronics packaging for nearly 30 years. As the director of Binghamton Universitys Integrated Electronics Engineering Center (IEEC), he and his team have made key discoveries that improve how everyday devices work.

In appreciation for his groundbreaking research and contributions, the American Society of Mechanical Engineers (ASME) recently named Park a fellow of the organization, which includes more than 90,000 members in 135 countries worldwide. Only about 3% of members become fellows.

ASMEs fellow grade is the highest elected grade of membership within ASME, said ASME President Mahantesh Hiremath. It recognizes exceptional engineering achievements and contributions to the engineering profession.

Park said he is honored by the recognition and hopes that it brings more attention to the research being done at Watson College.

It is a meaningful recognition, and also a way of promoting my ideas and my Universitys division to the wider world, he said. To be promoted to fellow, you have to proactively reach out to the technical communities by organizing conferences and symposiums, and by promoting a certain technology or bringing more attention to a certain field.

Park earned his BS and MS from Seoul National University in his native Korea, and his PhD at Purdue University. Before coming to Binghamton in 2002, he worked on electronics packaging for seven years at IBM Corp.s Microelectronics Division, but he originally had a very different career path in mind.

When they approached me and offered the job as a packaging engineer, I knew what IBM was but because I was an aerospace engineer, I didnt have any clue why they would need me. Is IBM packaging chocolate cake or something? he thought.

In fact, they were doing something very similar, trying to protect electronics from drop shock and packing more into each device without ruining the electronics by the heat generated internally. I studied fracture and failure in aircraft, and they recognized that my background and expertise could effectively contribute to solving the problems they faced.

Although he works in academia now, Park believes the experience and knowledge he acquired during his time in industry has been vital to the success of IEEC, his colleagues and students. Many others on his IEEC team have similar experiences working at tech firms.

About 70% of my research groups projects are associated with industry, and we have weekly meetings with the sponsoring companies, he said. All of my graduate students are directly connected with industry on a weekly basis. It is not just theoretical engineering it is real engineering as they work toward their dissertations. They know the industry languages and what the hot topics are at their companies, which could be their future employers.

To explain the challenges that electronics packaging faces, Park makes an analogy to an automobile: When you build a car with a powerful engine, such as a 500-horsepower engine, you need stronger axles to handle that strain, a top-notch steering system that keeps you on the road and excellent brakes that will stop the car before a collision. Similarly, as silicon chips get smaller and powerful, the accessories that help it to maintain its level of performance must also shrink and be resilient.

Much like an urban area with a growing population occupying a finite amount of space, one way to make everything fit is to start thinking three-dimensionally, but stacking components faces one big problem: How to dissipate the heat buildup?

Heat is the biggest threat for any electronics, Park said. When creating a three-dimensional design, how do we take the heat out? For the topmost component, we can use conventional methods, but what about the middle ones? Its going to be well cooked in the middle!

Finding solutions for future generations of electronics is a daunting mandate to fulfill, but Park is always looking ahead and eager for what comes next.

Every day, the research is fun, and that is making me busy with joy, he said. Im really grateful to be having this opportunity in my life.

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