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

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.