Accounting for epistatic interactions improves the functional analysis of protein structures

Abstract

Motivation: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure.Methods and Results: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions.Conclusions: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction.Contact: lichtarge@bcm.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Elucidation of G-protein and β-arrestin functional selectivity at the dopamine D2 receptor

“…Evolutionary Trace-Guided Mutagenesis of D 2 R. The ET method identifies amino acids that determine the function of a protein and map its functional sites when a structure is available (15,16). ET algorithms exploit protein orthologs and paralogs to correlate sequence variations with phylogenetic divergences and determine whether substitutions at a particular residue are likely to produce a functional change in the protein (17).…”

“…ET algorithms exploit protein orthologs and paralogs to correlate sequence variations with phylogenetic divergences and determine whether substitutions at a particular residue are likely to produce a functional change in the protein (17). The predictive power of ET is further enhanced when specific crystal structures (18) and more sophisticated models of the evolution of structure and function can be applied (16,19). Here a combination of these approaches (cocrystals of receptors and signaling molecules as well as more sophisticated algorithms; Fig.…”

“…These sequences were gathered from GPCRDB, aligned, and filtered for the 195 gapless seven transmembrane helix residues. We used the updated pair interaction ET algorithm (piET) (16), which achieves greater accuracy by taking into account the residue contacts seen in a structure, here the crystal structure of rhodopsin in complex with the C terminus peptide of the endogenous G protein (27). The residues targeted for mutation were selected based on their evolutionarily importance (top 5%) and proximity to the C terminus peptide (within 12 Angstroms, the residues in DRY and NPXXY motifs being ignored).…”

Determinants of Endogenous Ligand Specificity Divergence among Metabotropic Glutamate Receptors

“…Evolutionary trace analysis was performed with rvET and piET algorithms (10,11). The rvET algorithm measures the importance of a residue based on its variation pattern in the context of the phylogenetic tree.…”

A formal perturbation equation between genotype and phenotype determines the Evolutionary Action of protein-coding variations on fitness

“…To measure the evolutionary fitness gradient @f/@r i , we rank the importance of every sequence position with the Evolutionary Trace (ET) method (Lichtarge et al 1996;Mihalek et al 2004;Wilkins et al 2013). By definition, a gradient is the ratio of the sensitivity of a function with respect to its coordinates.…”