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Title: Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

Journal Article · · Proteins
DOI: https://doi.org/10.1002/prot.26222 · OSTI ID:1976380
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  1. University of Lille, Lille (France). et al.; OSTI
  2. CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology University of Lille Lille France
  3. Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory European Bioinformatics Institute (EMBL‐EBI) Cambridge UK
  4. Biomolecular Modelling Laboratory The Francis Crick Institute London UK
  5. Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering Jiangsu University of Technology Changzhou China
  6. Department of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USA
  7. Department of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USA; Institute for Data Science and Informatics University of Missouri Columbia Missouri USA
  8. Faculty of Chemistry University of Gdansk Gdansk Poland
  9. Faculty of Electronics, Telecommunications and Informatics Gdansk University of Technology Gdansk Poland
  10. Faculty of Chemistry University of Gdansk Gdansk Poland; Intercollegiate Faculty of Biotechnology University of Gdansk and Medical University of Gdansk Gdansk Poland
  11. Graduate School of Medical Sciences Nagoya City University Nagoya Japan
  12. International University of Health and Welfare Hospital (IUHW Hospital) Nasushiobara City Japan
  13. Chemical and Biomolecular Engineering Johns Hopkins University Baltimore Maryland USA
  14. Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science Utrecht University Utrecht The Netherlands
  15. Department of Applied Mathematics and Statistics Stony Brook University Stony Brook New York USA; Laufer Center for Physical and Quantitative Biology Stony Brook University Stony Brook New York USA; Innopolis University Russia
  16. Department of Applied Mathematics and Statistics Stony Brook University Stony Brook New York USA; Laufer Center for Physical and Quantitative Biology Stony Brook University Stony Brook New York USA
  17. Department of Biomedical Engineering Boston University Boston Massachusetts USA
  18. Department of Applied Mathematics and Statistics Stony Brook University Stony Brook New York USA; Laufer Center for Physical and Quantitative Biology Stony Brook University Stony Brook New York USA; Institute of Computer‐Aided Design of the Russian Academy of Sciences Moscow Russia
  19. Department of Biomedical Engineering Boston University Boston Massachusetts USA; Department of Chemistry Boston University Boston Massachusetts USA
  20. Instituto de Ciencias de la Vid y del Vino (ICVV) CSIC – Universidad de la Rioja – Gobierno de La Rioja Logrono Spain; Barcelona Supercomputing Center (BSC) Barcelona Spain
  21. Université Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK Grenoble France
  22. School of Physics Huazhong University of Science and Technology Wuhan China
  23. Department of Computer Science Purdue University West Lafayette Indiana USA
  24. Department of Biological Sciences Purdue University West Lafayette Indiana USA
  25. Department of Computer Science Purdue University West Lafayette Indiana USA; Department of Biological Sciences Purdue University West Lafayette Indiana USA
  26. Graduate School of Information Sciences Tohoku University Sendai Miyagi Japan
  27. Institute for Quantum Life Science, National Institutes for Quantum and Radiological Science and Technology Tokai Ibaraki Japan
  28. University of Maryland Institute for Bioscience and Biotechnology Research Rockville Maryland USA; Department of Cell Biology and Molecular Genetics University of Maryland Maryland USA
  29. King Abdullah University of Science and Technology Thuwal Saudi Arabia
  30. University of Naples “Parthenope” Napoli Italy
  31. Department of Electrical and Computer Engineering Texas A&M University Texas USA
  32. Department of Chemistry Seoul National University Seoul Republic of Korea
  33. School of Pharmacy Kitasato University Minato‐ku Tokyo Japan
  34. Computational Biology Program and Department of Molecular Biosciences University of Kansas Lawrence Kansas USA
  35. Institute of Biotechnology, Life Sciences Center Vilnius University Vilnius Lithuania
  36. Dalton Cardiovascular Research Center University of Missouri Columbia Missouri USA
  37. Institute for Data Science and Informatics University of Missouri Columbia Missouri USA; Dalton Cardiovascular Research Center University of Missouri Columbia Missouri USA; Department of Physics and Astronomy University of Missouri Columbia Missouri USA; Department of Biochemistry University of Missouri Columbia Missouri USA
  38. Center for Structural Biology VIB‐VUB Brussels Belgium
+ Show Author Affiliations

Here we present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.

Research Organization:
Donald Danforth Plant Science Center, St. Louis, MO (United States); Georgia Institute of Technology, Atlanta, GA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Contributing Organization:
CASP Collaboration Teams
Grant/Contract Number:
SC0020400; SC0021303
OSTI ID:
1976380
Journal Information:
Proteins, Journal Name: Proteins Journal Issue: 12 Vol. 89; ISSN 0887-3585
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (1)

Application of Homology Modeling by Enhanced Profile–Profile Alignment and Flexible-Fitting Simulation to Cryo-EM Based Structure Determination journal February 2022

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Related Subjects

protein complexes
59 BASIC BIOLOGICAL SCIENCES
CAPRI
CASP
blind prediction
docking
oligomeric state
protein assemblies
protein docking
protein-protein interaction
template-based modeling