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A multi-scale coevolutionary approach to predict interactions between protein domains

TitleA multi-scale coevolutionary approach to predict interactions between protein domains
Publication TypeJournal Article
Year of Publication2019
AuthorsCroce, G, Gueudré, T, Cuevas, MVirginia R, Keidel, V, Figliuzzi, M, Szurmant, H, Weigt, M
JournalPLOS Computational BiologyPLOS Computational Biology
Volume15
Issue10
Paginatione1006891 -
Date Published2019/10/21
Abstract

Author summary Interactions between proteins and their domains are at the basis of almost all biological processes. To complement labor intensive and error-prone experimental approaches to the genome-scale characterization of such interactions, we propose a computational approach based upon rapidly growing protein-sequence databases. To maintain interaction in the course of evolution, proteins and their domains are required to coevolve: evolutionary changes in the interaction partners appear correlated across several scales, from correlated presence-absence patterns of proteins across species, up to correlations in the amino-acid usage. Our approach combines these different scales within a common mathematical-statistical inference framework, which is inspired by the so-called direct coupling analysis. It is able to predict currently unknown, but biologically sensible interaction, and to identify cases of convergent evolution leading to alternative solutions for a common biological task. Thereby our work illustrates the potential of global statistical inference for the genome-scale coevolutionary analysis of interacting proteins and protein domains.

URLhttps://doi.org/10.1371/journal.pcbi.1006891