TY - JOUR
T1 - An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12
AU - Scientific Reports
AU - Keasar, Chen
AU - McGuffin, Liam J.
AU - Wallner, Björn
AU - Chopra, Gaurav
AU - Adhikari, Badri
AU - Bhattacharya, Debswapna
AU - Blake, Lauren
AU - Bortot, Leandro Oliveira
AU - Cao, Renzhi
AU - Dhanasekaran, B. K.
AU - Dimas, Itzhel
AU - Faccioli, Rodrigo Antonio
AU - Faraggi, Eshel
AU - Ganzynkowicz, Robert
AU - Ghosh, Sambit
AU - Ghosh, Soma
AU - Giełdoń, Artur
AU - Golon, Lukasz
AU - He, Yi
AU - Heo, Lim
AU - Hou, Jie
AU - Khan, Main
AU - Khatib, Firas
AU - Khoury, George A.
AU - Kieslich, Chris
AU - Kim, David E.
AU - Krupa, Pawel
AU - Lee, Gyu Rie
AU - Li, Hongbo
AU - Li, Jilong
AU - Lipska, Agnieszka
AU - Liwo, Adam
AU - Maghrabi, Ali Hassan A.
AU - Mirdita, Milot
AU - Mirzaei, Shokoufeh
AU - Mozolewska, Magdalena A.
AU - Onel, Melis
AU - Ovchinnikov, Sergey
AU - Shah, Anand
AU - Shah, Utkarsh
AU - Sidi, Tomer
AU - Sieradzan, Adam K.
AU - Ślusarz, Magdalena
AU - Ślusarz, Rafal
AU - Smadbeck, James
AU - Tamamis, Phanourios
AU - Trieber, Nicholas
AU - Wirecki, Tomasz
AU - Yin, Yanping
AU - Zhang, Yang
N1 - Funding Information:
The authors would like to acknowledge the collaboration of hundreds of thousands of citizen scientists who contributed millions of decoys through the Foldit game. This research used significant resources of the National Energy Research Scientific Computing Center (NERSC), which is supported by the Office of Science of the U.S. Department of Energy under Contract number DE-AC02-05CH11231. L. Blake, I.D., and S.M. were supported in part by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Science Undergraduate Laboratory Internship (SULI) program and Visiting Faculty Program (VFP). C. Keasar and T.S. are grateful for support by grant no. 2009432 from the United States-Israel Binational Science Foundation (BSF) and grant no. 1122/14 from the Israel Science Foundation (ISF). D.B., J.L. and J.C. were supported by the National Institute of General Medical Sciences (R01GM093123). G.C. acknowledges the support of Purdue University start-up funds, Ralph W. and Grace M. Showalter Trust Award, and Jim and Diann Robbers Cancer Research Grant for New Investigators Award. Y.Z. is supported in part by the National Institute of General Medical Sciences (GM083107 and GM116960). Delbem lab is grateful for the support by Brazilian agencies: FAPESP, CAPES and CNPq. Y.H., Y.Y. and H.S. were funded by NIH Grant GM-14312 and NSF Grant MCB-10-19767. M. Levitt acknowledges the National Institutes of Medicine grant GM11574901 and is the Robert W. and Vivian K. Cahill Professor of Cancer Research. B.W. is supported by the Swedish Research Council (2012-5270 and 2016-05369) and Swedish e-Science Research Center. C. Czaplewski, A. Liwo, M. Mozolewska, P. Krupa were supported by grant UMO-2013/10/M/ST4/00640 from the Polish National Science Center. SVGrp acknowledges the computing facilities at MBU and SERC of IISc. Sambit Ghosh is supported by the IISc Mathematical Initiative Assistantship and SV is thankful to The National Academy of Sciences, India for Senior Scientist Fellowship. H.L. and D.X. were partially supported by National Institutes of Health grant R01-GM100701. C.A.F. acknowledges support from the National Institutes of Health (R01GM052032) and the National Science Foundation. G.A.K. is grateful for support by a National Science Foundation Graduate Research Fellowship under grant No. DGE-1148900. The authors gratefully acknowledge that the calculations reported in this paper were performed at the TIGRESS high performance computing center at Princeton University which is supported by the Princeton Institute for Computational Science and Engineering (PICSciE) and the Princeton University Office of Information Technology. J.B. acknowledges the support of the UK Engineering and Physical Sciences Research Council under grants EP/M020576/1 and EP/N031962/1. C.S., G.R.L., and L.H. acknowledge National Research Foundation of Korea, No. 2016R1A2A1A05005485. S.N.C. and the WeFold community are very grateful to NERSC and especially Shreyas Cholia and Francesca Verdier for their HPC support. SNC would like to thank Prof. Eric Chi for his advice on comparing the performance of the pipelines. We like to thank the Rosetta@home volunteers for providing the computing resources for Rosetta decoys.
Publisher Copyright:
© 2018 The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.
AB - Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.
UR - http://www.scopus.com/inward/record.url?scp=85049381808&partnerID=8YFLogxK
U2 - 10.1038/s41598-018-26812-8
DO - 10.1038/s41598-018-26812-8
M3 - Article
AN - SCOPUS:85049381808
SN - 2045-2322
VL - 8
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 9939
ER -