Literature DB >> 34453465

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

Marc F Lensink1, Guillaume Brysbaert1, Théo Mauri1, Nurul Nadzirin2, Sameer Velankar2, Raphael A G Chaleil3, Tereza Clarence3, Paul A Bates3, Ren Kong4, Bin Liu4, Guangbo Yang4, Ming Liu4, Hang Shi4, Xufeng Lu4, Shan Chang4, Raj S Roy5, Farhan Quadir5, Jian Liu5, Jianlin Cheng5,6, Anna Antoniak7, Cezary Czaplewski7, Artur Giełdoń7, Mateusz Kogut7, Agnieszka G Lipska7, Adam Liwo7, Emilia A Lubecka8, Martyna Maszota-Zieleniak7, Adam K Sieradzan7, Rafał Ślusarz7, Patryk A Wesołowski7,9, Karolina Zięba7, Carlos A Del Carpio Muñoz10, Eiichiro Ichiishi11, Ameya Harmalkar12, Jeffrey J Gray12, Alexandre M J J Bonvin13, Francesco Ambrosetti13, Rodrigo Vargas Honorato13, Zuzana Jandova13, Brian Jiménez-García13, Panagiotis I Koukos13, Siri Van Keulen13, Charlotte W Van Noort13, Manon Réau13, Jorge Roel-Touris13, Sergei Kotelnikov14,15,16, Dzmitry Padhorny14,15, Kathryn A Porter17, Andrey Alekseenko14,15,18, Mikhail Ignatov14,15, Israel Desta17, Ryota Ashizawa14,15, Zhuyezi Sun17, Usman Ghani17, Nasser Hashemi17, Sandor Vajda17,19, Dima Kozakov14,15, Mireia Rosell20,21, Luis A Rodríguez-Lumbreras20,21, Juan Fernandez-Recio20,21, Agnieszka Karczynska22, Sergei Grudinin22, Yumeng Yan23, Hao Li23, Peicong Lin23, Sheng-You Huang23, Charles Christoffer24, Genki Terashi25, Jacob Verburgt25, Daipayan Sarkar25, Tunde Aderinwale24, Xiao Wang24, Daisuke Kihara24,25, Tsukasa Nakamura26, Yuya Hanazono27, Ragul Gowthaman28,29, Johnathan D Guest28,29, Rui Yin28,29, Ghazaleh Taherzadeh28,29, Brian G Pierce28,29, Didier Barradas-Bautista30, Zhen Cao30, Luigi Cavallo30, Romina Oliva31, Yuanfei Sun32, Shaowen Zhu32, Yang Shen32, Taeyong Park33, Hyeonuk Woo33, Jinsol Yang33, Sohee Kwon33, Jonghun Won33, Chaok Seok33, Yasuomi Kiyota34, Shinpei Kobayashi34, Yoshiki Harada34, Mayuko Takeda-Shitaka34, Petras J Kundrotas35, Amar Singh35, Ilya A Vakser35, Justas Dapkūnas36, Kliment Olechnovič36, Česlovas Venclovas36, Rui Duan37, Liming Qiu37, Xianjin Xu37, Shuang Zhang37, Xiaoqin Zou6,37,38,39, Shoshana J Wodak40.   

Abstract

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.
© 2021 Wiley Periodicals LLC.

Entities:  

Keywords:  CAPRI; CASP; blind prediction; docking; oligomeric state; protein assemblies; protein complexes; protein docking; protein-protein interaction; template-based modeling

Mesh:

Substances:

Year:  2021        PMID: 34453465      PMCID: PMC8616814          DOI: 10.1002/prot.26222

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  72 in total

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2.  Docking and scoring protein interactions: CAPRI 2009.

Authors:  Marc F Lensink; Shoshana J Wodak
Journal:  Proteins       Date:  2010-11-15

3.  Blind predictions of protein interfaces by docking calculations in CAPRI.

Authors:  Marc F Lensink; Shoshana J Wodak
Journal:  Proteins       Date:  2010-11-15

4.  The atomic structure of protein-protein recognition sites.

Authors:  L Lo Conte; C Chothia; J Janin
Journal:  J Mol Biol       Date:  1999-02-05       Impact factor: 5.469

5.  Statistical mechanics-based method to extract atomic distance-dependent potentials from protein structures.

Authors:  Sheng-You Huang; Xiaoqin Zou
Journal:  Proteins       Date:  2011-07-05

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Journal:  Nat Protoc       Date:  2017-01-12       Impact factor: 13.491

Review 7.  Template-based structure modeling of protein-protein interactions.

Authors:  Andras Szilagyi; Yang Zhang
Journal:  Curr Opin Struct Biol       Date:  2013-12-11       Impact factor: 6.809

8.  DockQ: A Quality Measure for Protein-Protein Docking Models.

Authors:  Sankar Basu; Björn Wallner
Journal:  PLoS One       Date:  2016-08-25       Impact factor: 3.240

9.  iScore: a novel graph kernel-based function for scoring protein-protein docking models.

Authors:  Cunliang Geng; Yong Jung; Nicolas Renaud; Vasant Honavar; Alexandre M J J Bonvin; Li C Xue
Journal:  Bioinformatics       Date:  2020-01-01       Impact factor: 6.937

10.  Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta.

Authors:  Sergey Ovchinnikov; David E Kim; Ray Yu-Ruei Wang; Yuan Liu; Frank DiMaio; David Baker
Journal:  Proteins       Date:  2016-02-24
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2.  Critical assessment of methods of protein structure prediction (CASP)-Round XIV.

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6.  Application of Homology Modeling by Enhanced Profile-Profile Alignment and Flexible-Fitting Simulation to Cryo-EM Based Structure Determination.

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7.  Studying Disease-Associated UBE3A Missense Variants Using Enhanced Sampling Molecular Simulations.

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8.  In silico optimization of RNA-protein interactions for CRISPR-Cas13-based antimicrobials.

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Journal:  Nat Commun       Date:  2022-03-10       Impact factor: 14.919

Review 10.  Modeling the Dynamics of Protein-Protein Interfaces, How and Why?

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Journal:  Molecules       Date:  2022-03-11       Impact factor: 4.411

  10 in total

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