title: Sequence co-evolution gives 3D contacts and structures of protein complexes.
abstract: 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.
authors.affiliation: Department of Systems Biology, Harvard University, Boston, United States.
authors.forename: Thomas A
authors.identifier: http://orcid.org/0000-0002-7476-9539
authors.initials: TA
authors.lastname: Hopf
authors.affiliation: Department of Systems Biology, Harvard University, Boston, United States.
authors.forename: Charlotta P I
authors.identifier: http://orcid.org/0000-0002-6689-6423
authors.initials: CP
authors.lastname: Schärfe
authors.affiliation: Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, Netherlands.
authors.forename: João P G L M
authors.initials: JP
authors.lastname: Rodrigues
authors.affiliation: Department of Systems Biology, Harvard University, Boston, United States.
authors.forename: Anna G
authors.initials: AG
authors.lastname: Green
authors.affiliation: Applied Bioinformatics, Quantitative Biology Center, University of Tübingen, Tübingen, Germany.
authors.forename: Oliver
authors.initials: O
authors.lastname: Kohlbacher
authors.affiliation: Computational Biology Center, Memorial Sloan Kettering Cancer Center, New York, United States.
authors.forename: Chris
authors.initials: C
authors.lastname: Sander
authors.affiliation: Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, Netherlands.
authors.forename: Alexandre M J J
authors.identifier: http://orcid.org/0000-0001-7369-1322
authors.initials: AM
authors.lastname: Bonvin
authors.affiliation: Department of Systems Biology, Harvard University, Boston, United States.
authors.forename: Debora S
authors.identifier: http://orcid.org/0000-0001-9388-2281
authors.initials: DS
authors.lastname: Marks
mesh_terms: D030562:Databases, Protein; D004926:Escherichia coli / Q000235:genetics* / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D019143:Evolution, Molecular; D015870:Gene Expression; D053263:Gene Regulatory Networks; D016680:Genome, Bacterial; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D025941:Protein Interaction Mapping
chemical_list: D029968:Escherichia coli Proteins
keywords: E. coli; co-evolution; evolutionary biology; genomics; interactions; protein