Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences

TL;DR

This study demonstrates that correlations from structural contacts and phylogeny synergistically improve protein partner inference from sequences, with phylogeny providing crucial signals especially when contact information is limited.

Contribution

The paper introduces a minimal model to analyze how structural and phylogenetic correlations jointly enhance protein partner inference, highlighting the constructive combination of these signals.

Findings

Correlations from structure and phylogeny combine constructively for better inference.

Phylogeny can compensate for limited structural contact information.

Non-contact site pairs contribute positively to inference performance.

Abstract

Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families. Does successful inference mainly rely on correlations from structural contacts or from phylogeny, or both? Do these two types of signal combine constructively or hinder each other? To address these questions, we generate and analyze synthetic data produced using a minimal model that allows us to control the amounts of structural constraints and phylogeny. We show that correlations from these two sources combine constructively to increase the performance of partner inference by DCA or MI. Furthermore, signal from phylogeny can rescue partner inference when signal from contacts becomes less informative, including in the realistic case where inter-protein contacts are restricted to a small subset of sites. We also demonstrate that DCA-inferred couplings between non-contact pairs of sites improve partner inference in the presence of strong phylogeny, while deteriorating it otherwise. Moreover, restricting to non-contact pairs of sites preserves inference performance in the presence of strong phylogeny. In a natural data set, as well as in realistic synthetic data based on it, we find that non-contact pairs of sites contribute positively to partner inference performance, and that restricting to them preserves performance, evidencing an important role of phylogeny.