A multi-scale coevolutionary approach to predict interactions between protein domains.
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
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
10 2019
10 2019
Historique:
received:
19
02
2019
accepted:
27
09
2019
revised:
31
10
2019
pubmed:
22
10
2019
medline:
6
2
2020
entrez:
22
10
2019
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 31634362
doi: 10.1371/journal.pcbi.1006891
pii: PCOMPBIOL-D-19-00283
pmc: PMC6822775
doi:
Substances chimiques
Amino Acids
0
Proteins
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1006891Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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