Editing Folding@home (section)

== Examples of application in biomedical research ==
Protein misfolding can result in a [[proteopathy|variety of diseases]] including Alzheimer's disease, [[cancer]], [[Creutzfeldt–Jakob disease]], [[cystic fibrosis]], Huntington's disease, [[sickle-cell anemia]], and [[type&nbsp;II diabetes]].<ref name="10.1002/iub.117"/><ref name="Protein Misfolding Diseases"/><ref name="diseases FAQ"/> Cellular infection by viruses such as [[HIV]] and [[influenza]] also involve folding events on [[cell membrane]]s.<ref name="978-0-340-66316-5"/> 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.<ref name="10.1038/nature02265"/> The combination of computational molecular modeling and experimental analysis has the possibility to fundamentally shape the future of molecular medicine and the [[drug design|rational design of therapeutics]],<ref name="10.1016/j.cbpa.2008.02.011"/> such as expediting and lowering the costs of [[drug discovery]].<ref name="10.1093/bib/bbp023"/> 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.<ref name="Press FAQ"/>

The simulations run on Folding@home are used in conjunction with laboratory experiments,<ref name="10.1016/j.sbi.2010.10.006"/> 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 [[ribosome|ribosomal]] exit tunnel, to help scientists better understand how natural confinement and crowding might influence the folding process.<ref name="forum: 7808/7809 to FAH"/><ref name="10.1073/pnas.0608256104"/> Furthermore, scientists typically employ chemical [[denaturation (biochemistry)|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 [[Protein&nbsp;L]], and predicted its collapse rate in strong agreement with experimental results.<ref name="10.1021/ja908369h"/>

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.<ref name="typepad: Simbios"/><ref name="papers for free"/> The Pande lab has collaborated with other molecular dynamics systems such as the [[Blue Gene]] supercomputer,<ref name="10.1038/sj.embor.7400108"/> and they share Folding@home's key software with other researchers, so that the algorithms which benefited Folding@home may aid other scientific areas.<ref name="typepad: Simbios"/> 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 cluster]]s or [[supercomputer]]s.<ref name="Pronk et al, 2011" /><ref name="Copernicus download"/> Summaries of all scientific findings from Folding@home are posted on the Folding@home website after publication.<ref name="papers"/>

=== Alzheimer's disease ===
{{Multiple image|footer= 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.|image1= Amyloid 01big1.jpg|image2= Amyloid 02big1.jpg|image3= Amyloid 03big1.jpg}}

[[Alzheimer's disease]] is an incurable [[neurodegeneration|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 [[proteopathy|protein misfolding disease]]. Alzheimer's is associated with toxic [[protein aggregation|aggregations]] of the [[amyloid beta]] (Aβ) [[peptide]], caused by Aβ misfolding and clumping together with other Aβ peptides. These Aβ aggregates then grow into significantly larger [[senile plaques]], a pathological marker of Alzheimer's disease.<ref name="10.2119/2007-00100.Irvine"/><ref name="10.1001/archneurol.2007.56"/><ref name="10.1074/jbc.R800036200"/> 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 Aβ aggregation are highly demanding computationally due to their size and complexity.<ref name="10.1063/1.3010881"/><ref name="10.1371/journal.pone.0021776"/>

Preventing Aβ aggregation is a promising method to developing therapeutic drugs for Alzheimer's disease, according to Naeem and Fazili in a [[literature review]] article.<ref name="10.1007/s12013-011-9200-x"/> In 2008, Folding@home simulated the dynamics of Aβ 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 Aβ 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.<ref name="10.1038/cr.2010.57"/> 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.<ref name="10.1063/1.3010881"/>

In December 2008, Folding@home found several small drug candidates which appear to inhibit the toxicity of Aβ aggregates.<ref name="typepad: possible alz. drug"/> In 2010, in close cooperation with the Center for Protein Folding Machinery, these drug leads began to be tested on [[biological tissue]].<ref name="diseases FAQ"/> In 2011, Folding@home completed simulations of several [[mutation]]s of Aβ 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 Aβ [[oligomer]]s.<ref name="10.1371/journal.pone.0021776"/><ref name="10.1021/jm201332p"/> Later that year, Folding@home began simulations of various Aβ fragments to determine how various natural enzymes affect the structure and folding of Aβ.<ref name="forum: 6871"/><ref name="description: 6571"/>

=== Huntington's disease ===
[[Huntington's disease]] is a neurodegenerative [[genetic disorder]] that is associated with protein misfolding and aggregation. [[Polyglutamine tract|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.<ref name="10.1016/S0140-6736(07)60111-1"/> As with other aggregates, there is difficulty in experimentally determining its structure.<ref name="10.1016/j.jmb.2009.01.032"/> 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.<ref name="diseases FAQ"/> The N17 fragment of the huntingtin protein accelerates this aggregation, and while there have been several mechanisms proposed, its exact role in this process remains largely unknown.<ref name="10.1038/nchembio.279"/> Folding@home has simulated this and other fragments to clarify their roles in the disease.<ref name="forum: 8021 in beta"/> Since 2008, its drug design methods for Alzheimer's disease have been applied to Huntington's.<ref name="diseases FAQ"/>

=== Cancer ===
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.<ref name="10.1126/science.1905840"/> In 2004, Folding@home was used to perform the first molecular dynamics study of the refolding of p53's [[protein dimer]] in an [[water model|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.<ref name="10.1016/j.jmb.2004.10.083"/> This was the first [[peer review]]ed publication on cancer from a distributed computing project.<ref name="FAH publishes cancer results"/> 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.<ref name="10.1016/j.jmb.2005.12.083"/>

Folding@home is also used to study [[chaperone (protein)|protein chaperones]],<ref name="diseases FAQ"/> [[heat shock protein]]s which play essential roles in cell survival by assisting with the folding of other proteins in the [[Macromolecular crowding|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.<ref name="10.1016/j.biopha.2011.04.025"/> 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.<ref name="typepad: nanomedicine ce"/> 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 (gene)|engrailed]] [[homeodomain]]: a large protein which may be involved in many diseases, including cancer.<ref name="typepad: protomol b4"/><ref name="description: 180"/> In 2011, Folding@home began simulations of the dynamics of the small [[Trefoil knot fold|knottin]] protein EETI, which can identify [[carcinoma]]s in [[medical imaging|imaging scan]]s by binding to [[cell surface receptor|surface receptor]]s of cancer cells.<ref name="forum: 7600 in beta"/><ref name="description: 7600"/>

[[Interleukin 2]] (IL-2) is a protein that helps [[T cell]]s 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.<ref name="scientists boost IL-2 potency"/><ref name="10.1038/nature10975"/>

=== Osteogenesis imperfecta ===
[[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]],<ref name="10.1016/S0140-6736(04)16051-0"/> which fulfills a variety of structural roles and is the most abundant protein in [[mammal]]s.<ref name="978-0-387-73905-2"/> The mutation causes a deformation in [[Collagen helix|collagen's triple helix structure]], which if not naturally destroyed, leads to abnormal and weakened bone tissue.<ref name="10.1016/j.bpj.2009.04.059"/> 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.<ref name="10.1002/jcc.20301"/> 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.<ref name="diseases FAQ"/>

=== Viruses ===
Folding@home is assisting in research towards preventing some [[virus]]es, such as [[influenza]] and [[HIV]], from recognizing and entering [[Cell (biology)|biological cells]].<ref name="diseases FAQ"/> 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.<ref name="forum: 10125"/> Folding@home has also been used to study [[membrane fusion]], an essential event for [[viral entry|viral infection]] and a wide range of biological functions. This fusion involves [[conformational change]]s of viral fusion proteins and [[protein docking]],<ref name="978-0-340-66316-5"/> but the exact molecular mechanisms behind fusion remain largely unknown.<ref name="10.1039/c0cs00115e"/> 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.<ref name="10.1038/cr.2010.57"/> 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.<ref name="Peter Kasson"/> In 2006, scientists applied Markov state models and the Folding@home network to discover two pathways for fusion and gain other mechanistic insights.<ref name="10.1038/cr.2010.57"/>

Following detailed simulations from Folding@home of small cells known as [[vesicle (biology)|vesicles]], in 2007, the Pande lab introduced a new computing method to measure the [[topology]] of its structural changes during fusion.<ref name="10.1093/bioinformatics/btm250"/> In 2009, researchers used Folding@home to study mutations of [[Hemagglutinin (influenza)|influenza hemagglutinin]], a protein that attaches a virus to its [[Host (biology)|host]] cell and assists with viral entry. Mutations to hemagglutinin affect [[binding affinity|how well the protein binds]] to a host's [[cell surface receptor]] molecules, which determines how [[infectivity|infective]] the virus strain is to the host organism. Knowledge of the effects of hemagglutinin mutations assists in the development of [[antiviral drug]]s.<ref name="10.1021/ja904557w"/><ref name="19209725, 2811693"/> As of 2012, Folding@home continues to simulate the folding and interactions of hemagglutinin, complementing experimental studies at the [[University of Virginia]].<ref name="diseases FAQ"/><ref name="typepad: kasson update"/>

In March 2020, Folding@home launched a program to assist researchers around the world who are working on finding a cure and learning more about the [[COVID-19 pandemic|coronavirus pandemic]]. The initial wave of projects simulate potentially druggable protein targets from SARS-CoV-2 virus, and the related SARS-CoV virus, about which there is significantly more data available.<ref name="tomshw-fah">{{cite web |last1=Broekhuijsen |first1=Niels |title=Help Cure Coronavirus with Your PC's Leftover Processing Power |url=https://www.tomshardware.com/news/folding-fight-coronavirus |website=Tom's Hardware |access-date=March 12, 2020 |date=March 3, 2020}}</ref><ref name="fah-newspost">{{cite web |last1=Bowman |first1=Greg |title=Folding@home takes up the fight against COVID-19 / 2019-nCoV |url=https://foldingathome.org/2020/02/27/foldinghome-takes-up-the-fight-against-covid-19-2019-ncov/ |website=Folding@home |access-date=March 12, 2020 |date=February 27, 2020}}</ref><ref>{{Cite web | url=https://www.hpcwire.com/2020/03/16/foldinghome-turns-its-massive-crowdsourced-computer-network-against-covid-19/ |title = Folding@home Turns Its Massive Crowdsourced Computer Network Against COVID-19|date = March 16, 2020}}</ref>

=== Drug design ===
[[Drug]]s function by [[ligand binding|binding]] to [[binding site|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 [[binding affinity|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 calculation]]s. Folding@home's computing performance allows researchers to use both methods, and evaluate their efficiency and reliability.<ref name="Press FAQ"/><ref name="typepad: drug design methods"/><ref name="10.1063/1.2221680"/> Computer-assisted drug design has the potential to expedite and lower the costs of drug discovery.<ref name="10.1093/bib/bbp023"/> In 2010, Folding@home used MSMs and free energy calculations to predict the native state of the [[villin]] protein to within 1.8 [[angstrom]] (Å) [[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]].<ref name="10.1038/cr.2010.57"/> 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]].<ref name="description: 10721"/><ref name="typepad: drug targets"/>

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 site]]s 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 [[Analysis of algorithms|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]].<ref name="typepad: drug targets"/><ref name="10.1073/pnas.1209309109"/>

Approximately half of all known [[antibiotic]]s interfere with the workings of a bacteria's [[ribosome]], a large and complex biochemical machine that performs [[protein biosynthesis]] by [[translation (biology)|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 (money)|grant]] to study and design new antibiotics.<ref name="diseases FAQ"/> In 2008, they used Folding@home to study the interior of this tunnel and how specific molecules may affect it.<ref name="10.1073/pnas.0801795105"/> The full structure of the ribosome was determined only as of 2011, and Folding@home has also simulated [[ribosomal protein]]s, as many of their functions remain largely unknown.<ref name="description: 5765"/>