Detecting Amino Acid Coevolution with Bayesian Graphical Models

Abstract

The comparative study of homologous proteins can provide abundant information about the functional and structural constraints on protein evolution. For example, an amino acid substitution that is deleterious may become permissive in the presence of another substitution at a second site of the protein. A popular approach for detecting coevolving residues is by looking for correlated substitution events on branches of the molecular phylogeny relating the protein-coding sequences. Here we describe a machine learning method (Bayesian graphical models) implemented in the open-source phylogenetic software package HyPhy, http://hyphy.org , for extracting a network of coevolving residues from a sequence alignment.

Keywords: Bayesian graphical model; HyPhy; amino acid coevolution; epistasis; hepatitis C virus.