A multi-scale coevolutionary approach to predict interactions between protein domains.
Details
Serval ID
serval:BIB_9F0D5311B690
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A multi-scale coevolutionary approach to predict interactions between protein domains.
Journal
PLoS computational biology
ISSN
1553-7358 (Electronic)
ISSN-L
1553-734X
Publication state
Published
Issued date
10/2019
Peer-reviewed
Oui
Volume
15
Number
10
Pages
e1006891
Language
english
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Publication Status: epublish
Abstract
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.
Keywords
Algorithms, Amino Acids/metabolism, Animals, Biophysical Phenomena, Computational Biology/methods, Evolution, Molecular, Humans, Models, Statistical, Phylogeny, Protein Binding/physiology, Protein Domains/physiology, Protein Interaction Domains and Motifs/physiology, Protein Interaction Mapping/methods, Proteins/chemistry
Pubmed
Web of science
Open Access
Yes
Create date
21/09/2023 13:32
Last modification date
25/05/2024 6:14