Xiaoqin Zou, Théo Mauri, Hang Shi, Shaowen Zhu, Justas Dapkūnas, Yuanfei Sun, Didier Barradas-Bautista, Raphael A. G. Chaleil, Ragul Gowthaman, Sohee Kwon, Xianjin Xu, Zuzana Jandova, Genki Terashi, Ryota Ashizawa, Petras J. Kundrotas, Shuang Zhang, Tunde Aderinwale, Jian Liu, Sandor Vajda, Paul A. Bates, Jianlin Cheng, Daisuke Kihara, Luis A. Rodríguez-Lumbreras, Carlos A. Del Carpio Muñoz, Liming Qiu, Guillaume Brysbaert, Jorge Roel-Touris, Česlovas Venclovas, Tereza Clarence, Rui Yin, Amar Singh, Patryk A. Wesołowski, Rafał Ślusarz, Adam Liwo, Guangbo Yang, Agnieszka S. Karczyńska, Yoshiki Harada, Sergei Kotelnikov, Yuya Hanazono, Charlotte W. van Noort, Marc F. Lensink, Jonghun Won, Adam K. Sieradzan, Israel Desta, Xufeng Lu, Charles Christoffer, Anna Antoniak, Taeyong Park, Sheng-You Huang, Tsukasa Nakamura, Brian G. Pierce, Usman Ghani, Yang Shen, Luigi Cavallo, Chaok Seok, Hao Li, Nurul Nadzirin, Ghazaleh Taherzadeh, Jacob Verburgt, Rodrigo V. Honorato, Artur Giełdoń, Jeffrey J. Gray, Dima Kozakov, Ming Liu, Shan Chang, Eiichiro Ichiishi, Manon Réau, Rui Duan, Francesco Ambrosetti, Johnathan D. Guest, Juan Fernández-Recio, Alexandre M. J. J. Bonvin, Ilya A. Vakser, Farhan Quadir, Yumeng Yan, Ren Kong, Sameer Velankar, Sergei Grudinin, Mateusz Kogut, Mikhail Ignatov, Yasuomi Kiyota, Hyeonuk Woo, Shoshana J. Wodak, Ameya Harmalkar, Shinpei Kobayashi, Panagiotis I. Koukos, Zhen Cao, Kliment Olechnovič, Cezary Czaplewski, Xiao Wang, Agnieszka G. Lipska, Kathryn A. Porter, Peicong Lin, Emilia A. Lubecka, Nasser Hashemi, Bin Liu, Mayuko Takeda-Shitaka, Karolina Zięba, Dzmitry Padhorny, Zhuyezi Sun, Daipayan Sarkar, Romina Oliva, Andrey Alekseenko, Siri Camee van Keulen, Mireia Rosell, Raj S. Roy, Brian Jiménez-García, Jinsol Yang, Martyna Maszota-Zieleniak, Cancer Research UK, Department of Energy and Climate Change (UK), European Commission, Institut National de Recherche en Informatique et en Automatique (France), Medical Research Council (UK), Japan Society for the Promotion of Science, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), National Institute of General Medical Sciences (US), National Institutes of Health (US), National Natural Science Foundation of China, National Science Foundation (US), Unité de Glycobiologie Structurale et Fonctionnelle (UGSF), Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Biomolecular Modelling Laboratory [London], The Francis Crick Institute [London], Jiangsu University of Technology [Changzhou], Department of Electrical Engineering and Computer Science [Columbia] (EECS), University of Missouri [Columbia] (Mizzou), University of Missouri System-University of Missouri System, Institute for Data Science and Informatics [Columbia], University of Gdańsk (UG), Faculty of Electronics, Telecommunications and Informatics [GUT Gdańsk] (ETI), Gdańsk University of Technology (GUT), Medical University of Gdańsk, Graduate School of Medical Sciences [Nagoya], Nagoya City University [Nagoya, Japan], International University of Health and Welfare Hospital (IUHW Hospital), Department of Chemical and Biomolecular Engineering [Baltimore], Johns Hopkins University (JHU), Bijvoet Center of Biomolecular Research [Utrecht], Utrecht University [Utrecht], Stony Brook University [SUNY] (SBU), State University of New York (SUNY), Innopolis University, Boston University [Boston] (BU), Russian Academy of Sciences [Moscow] (RAS), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Universidad de La Rioja (UR), Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Données, Apprentissage et Optimisation (DAO), Laboratoire Jean Kuntzmann (LJK), Université Grenoble Alpes (UGA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Huazhong University of Science and Technology [Wuhan] (HUST), Indiana University - Purdue University Indianapolis (IUPUI), Indiana University System, Graduate School of Information Sciences [Sendaï], Tohoku University [Sendai], National Institutes for Quantum and Radiological Science and Technology (QST), University of Maryland [Baltimore], King Abdullah University of Science and Technology (KAUST), University of Naples Federico II, Texas A&M University [Galveston], Seoul National University [Seoul] (SNU), Kitasato University, University of Kansas [Lawrence] (KU), Vilnius University [Vilnius], University of Missouri System, VIB-VUB Center for Structural Biology [Bruxelles], VIB [Belgium], Sub NMR Spectroscopy, Sub Overig UiLOTS, Sub Mathematics Education, NMR Spectroscopy, Université de Lille, CNRS, Unité de Glycobiologie Structurale et Fonctionnelle (UGSF) - UMR 8576, European Bioinformatics Institute [Hinxton] [EMBL-EBI], Department of Electrical Engineering and Computer Science [Columbia] [EECS], Faculty of Chemistry [Univ Gdańsk], Faculty of Electronics, Telecommunications and Informatics [GUT Gdańsk] [ETI], International University of Health and Welfare Hospital [IUHW Hospital], Johns Hopkins University [JHU], Stony Brook University [SUNY] [SBU], Department of Biomedical Engineering [Boston], Instituto de Ciencias de la Vid y el Vino [ICVV], Huazhong University of Science and Technology [Wuhan] [HUST], Indiana University - Purdue University Indianapolis [IUPUI], National Institutes for Quantum and Radiological Science and Technology [QST], King Abdullah University of Science and Technology [KAUST], Università degli Studi di Napoli 'Parthenope' = University of Naples [PARTHENOPE], Seoul National University [Seoul] [SNU], University of Kansas [Lawrence] [KU], University of Missouri [Columbia] [Mizzou], Unité de Glycobiologie Structurale et Fonctionnelle - UMR 8576 (UGSF), Université de Lille-Centre National de la Recherche Scientifique (CNRS), University of Naples Federico II = Università degli studi di Napoli Federico II, European Project: 675728,H2020,H2020-EINFRA-2015-1,BioExcel(2015), European Project: 823830,H2020-EU.1.4.1.3. Development, deployment and operation of ICT-based e-infrastructures, H2020-EU.1.4. EXCELLENT SCIENCE - Research Infrastructures ,BioExcel-2(2019), European Project: 777536,H2020-EU.1.4.1.3. Development, deployment and operation of ICT-based e-infrastructures, and H2020-EU.1.4. EXCELLENT SCIENCE - Research Infrastructures,EOSC-hub(2018)
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., Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC001003