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

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 wer...

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Published in:Proteins, structure, function, and bioinformatics Vol. 89; no. 12; pp. 1800 - 1823
Main Authors: Mauri, Théo, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphael A. G., Bates, Paul A., Kong, Ren, Liu, Bin, Yang, Guangbo, Liu, Ming, Shi, Hang, Lu, Xufeng, Chang, Shan, Roy, Raj S., Quadir, Farhan, Antoniak, Anna, Czaplewski, Cezary, Giełdoń, Artur, Kogut, Mateusz, Lipska, Agnieszka G., Liwo, Adam, Maszota‐Zieleniak, Martyna, Sieradzan, Adam K., Ślusarz, Rafał, Wesołowski, Patryk A., Zięba, Karolina, Del Carpio Muñoz, Carlos A., Ichiishi, Eiichiro, Harmalkar, Ameya, Gray, Jeffrey J., Ambrosetti, Francesco, Vargas Honorato, Rodrigo, Jandova, Zuzana, Jiménez‐García, Brian, Koukos, Panagiotis I., Van Keulen, Siri, Van Noort, Charlotte W., Réau, Manon, Roel‐Touris, Jorge, Kotelnikov, Sergei, Padhorny, Dzmitry, Porter, Kathryn A., Alekseenko, Andrey, Ignatov, Mikhail, Desta, Israel, Ashizawa, Ryota, Sun, Zhuyezi, Ghani, Usman, Hashemi, Nasser, Vajda, Sandor, Kozakov, Dima, Rosell, Mireia, Rodríguez‐Lumbreras, Luis A., Fernandez‐Recio, Juan, Karczynska, Agnieszka, Grudinin, Sergei, Yan, Yumeng, Li, Hao, Lin, Peicong, Huang, Sheng‐You, Christoffer, Charles, Terashi, Genki, Verburgt, Jacob, Sarkar, Daipayan, Aderinwale, Tunde, Wang, Xiao, Kihara, Daisuke, Nakamura, Tsukasa, Hanazono, Yuya, Gowthaman, Ragul, Guest, Johnathan D., Yin, Rui, Taherzadeh, Ghazaleh, Pierce, Brian G., Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Sun, Yuanfei, Zhu, Shaowen, Shen, Yang, Park, Taeyong, Woo, Hyeonuk, Yang, Jinsol, Kwon, Sohee, Won, Jonghun, Seok, Chaok, Kiyota, Yasuomi, Kobayashi, Shinpei, Harada, Yoshiki, Takeda‐Shitaka, Mayuko, Kundrotas, Petras J., Vakser, Ilya A., Dapkūnas, Justas, Olechnovič, Kliment, Venclovas, Česlovas, Duan, Rui, Qiu, Liming, Xu, Xianjin, Zhang, Shuang, Zou, Xiaoqin, Wodak, Shoshana J.
Format: Journal Article
Language:English
Published: Hoboken, USA John Wiley & Sons, Inc 01.12.2021
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Subjects:
Accuracy
Assemblies
Assembly
Binding Sites
blind prediction
CAPRI
CASP
Computational Biology - methods
Dimers
docking
Interfaces
Life Sciences
Models, Molecular
Molecular Docking Simulation
oligomeric state
Oligomers
Performance prediction
Predictions
protein assemblies
protein complexes
protein docking
Protein Interaction Domains and Motifs
protein-protein interaction
Proteins
Proteins - chemistry
Proteins - metabolism
Sequence Analysis, Protein
Software
template-based modeling
Trimers
docking
oligomeric state
protein assemblies
CASP
blind prediction
protein docking
CAPRI
protein-protein interaction
protein complexes
template-based modeling
ISSN:0887-3585, 1097-0134, 1097-0134
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Description
Summary: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.
Bibliography:Funding information
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
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USDOE Office of Science (SC)
SC0020400; SC0021303
ISSN:0887-3585
1097-0134
1097-0134
DOI:10.1002/prot.26222