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

• Published in: PLoS computational biology 2019-10, Vol.15 (10), p.e1006891-e1006891
• Main Authors: Croce, Giancarlo, Gueudré, Thomas, Ruiz Cuevas, Maria Virginia, Keidel, Victoria, Figliuzzi, Matteo, Szurmant, Hendrik, Weigt, Martin
• Format: Article
• Language: English
• Subjects: Acids; Algorithms; Amino acids; Amino Acids - metabolism; Animals; Biology and Life Sciences; Biophysical Phenomena; Coevolution; Computational Biology - methods; Computer and Information Sciences; Computer applications; Convergent evolution; Correlation; Couplings; Criminal investigation; E coli; Evolution (Biology); Evolution, Molecular; Genomes; Genomics; Health sciences; Humans; Life Sciences; Mathematical models; Methods; Models, Statistical; Multiscale analysis; Osteopathic medicine; Phylogenetics; Phylogeny; Physical Sciences; Predictions; Protein Binding - physiology; Protein Domains - physiology; Protein families; Protein Interaction Domains and Motifs - physiology; Protein Interaction Mapping - methods; Proteins; Proteins - chemistry; Research and Analysis Methods; Statistical analysis; Statistical models
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1006891

Interacting proteins and protein domains coevolve on multiple scales, from their correlated presence across species, to correlations in amino-acid usage. Genomic databases provide rapidly growing data for variability in genomic protein content and in protein sequences, calling for computational predictions of unknown interactions. We first introduce the concept of direct phyletic couplings, based on global statistical models of phylogenetic profiles. They strongly increase the accuracy of predicting pairs of related protein domains beyond simpler correlation-based approaches like phylogenetic profiling (80% vs. 30-50% positives out of the 1000 highest-scoring pairs). Combined with the direct coupling analysis of inter-protein residue-residue coevolution, we provide multi-scale evidence for direct but unknown interaction between protein families. An in-depth discussion shows these to be biologically sensible and directly experimentally testable. Negative phyletic couplings highlight alternative solutions for the same functionality, including documented cases of convergent evolution. Thereby our work proves the strong potential of global statistical modeling approaches to genome-wide coevolutionary analysis, far beyond the established use for individual protein complexes and domain-domain interactions.