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

TitleCommunity-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions.
Publication TypeJournal Article
Year of Publication2013
AuthorsMoretti, R., S. J. Fleishman, R. Agius, M. Torchala, P. A. Bates, P. L. Kastritis, J. P. G. L. M. Rodrigues, M. Trellet, A. M. J. J. Bonvin, M. Cui, M. Rooman, D. Gillis, Y. Dehouck, I. Moal, M. Romero-Durana, L. Pérez-Cano, C. Pallara, B. Jimenez, J. Fernández-Recio, S. Flores, M. Pacella, K. Praneeth Kilambi, J. J. Gray, P. Popov, S. Grudinin, J. Esquivel-Rodríguez, D. Kihara, N. Zhao, D. Korkin, X. Zhu, O. N. A. Demerdash, J. C. Mitchell, E. Kanamori, Y. Tsuchiya, H. Nakamura, H. Lee, H. Park, C. Seok, J. Sarmiento, S. Liang, S. Teraguchi, D. M. Standley, H. Shimoyama, G. Terashi, M. Takeda-Shitaka, M. Iwadate, H. Umeyama, D. Beglov, D. R. Hall, D. Kozakov, S. Vajda, B. G. Pierce, H. Hwang, T. Vreven, Z. Weng, Y. Huang, H. Li, X. Yang, X. Ji, S. Liu, Y. Xiao, M. Zacharias, S. Qin, H-X. Zhou, S-Y. Huang, X. Zou, S. Velankar, J. Janin, S. J. Wodak, and D. Baker
Date Published2013 Nov
KeywordsAlgorithms, Databases, Protein, Mutation, Protein Binding, Protein Interaction Mapping

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.

Alternate JournalProteins
PubMed ID23843247
PubMed Central IDPMC4143140
Grant List10748 / / Cancer Research UK / United Kingdom
R01 GM061867 / GM / NIGMS NIH HHS / United States
R01 GM064700 / GM / NIGMS NIH HHS / United States
R01 GM078221 / GM / NIGMS NIH HHS / United States
/ / Canadian Institutes of Health Research / Canada
/ / Howard Hughes Medical Institute / United States
Research group: