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Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions

Proteins Structure Function and Bioinformatics2013Vol. 81(11), pp. 1980–1987

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Rocco Moretti, Sarel J. Fleishman, Rudi Agius, Mieczyslaw Torchala, Paul A. Bates, Panagiotis L. Kastritis, João Rodrigues, Mikaël Trellet, Alexandre M. J. J. Bonvin, Meng Cui, Marianne Rooman, Dimitri Gillis, Yves Dehouck, Iain H. Moal, Miguel Romero‐Durana, Laura Pérez‐Cano, Chiara Pallara, Brian Jiménez‐García, Juan Fernández‐Recio, Samuel Coulbourn Flores, Michael S. Pacella, Krishna Praneeth Kilambi, Jeffrey J. Gray, Petr Popov, Sergei Grudinin, Juan Esquivel‐Rodríguez, Daisuke Kihara, Nan Zhao, Dmitry Korkin, Xiaolei Zhu, Omar Demerdash, Julie C. Mitchell, Eiji Kanamori, Yuko Tsuchiya, Haruki Nakamura, Hasup Lee, Hahnbeom Park, Chaok Seok, Jamica Sarmiento, Shide Liang, Shunsuke Teraguchi, Daron M. Standley, Hiromitsu Shimoyama, Genki Terashi, Mayuko Takeda‐Shitaka, Mitsuo Iwadate, Hideaki Umeyama, Dmitri Beglov, David Hall, Dima Kozakov, Sándor Vajda, Brian G. Pierce, Howook Hwang, Thom Vreven, Zhiping Weng, Yangyu Huang, Haotian Li, Xiufeng Yang, Xiaofeng Ji, Shiyong Liu, Yi Xiao, Martin Zacharias, Sanbo Qin, Huan‐Xiang Zhou, Sheng‐You Huang, Xiaoqin Zou, Sameer Velankar, Joël Janin, Shoshana J. Wodak, David Baker

Abstract

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.

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Abstract

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