Sequence co-evolution gives 3D contacts and structures of protein complexes

Protein-protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein...

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Bibliographic Details
Published in:eLife 2014-09, Vol.3
Main Authors: Hopf, Thomas A, Schärfe, Charlotta P I, Rodrigues, João P G L M, Green, Anna G, Kohlbacher, Oliver, Sander, Chris, Bonvin, Alexandre M J J, Marks, Debora S
Format: Article
Language:English
Subjects:
Bioinformatics
Biology
co-evolution
Databases, Protein
E coli
Escherichia coli - genetics
Escherichia coli - metabolism
Escherichia coli Proteins - chemistry
Escherichia coli Proteins - genetics
Escherichia coli Proteins - metabolism
Evolution
Evolution, Molecular
Gene Expression
Gene Regulatory Networks
Genome, Bacterial
Genomes
Genomics and Evolutionary Biology
interaction
Kinases
Models, Molecular
protein
Protein Binding
Protein Conformation
Protein interaction
Protein Interaction Mapping
Protein sources
Protein structure
Proteins
Software
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Summary:Protein-protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein-protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein-protein interaction networks and used for interaction predictions at residue resolution.
ISSN:2050-084X
2050-084X
DOI:10.7554/elife.03430