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Cited by 1,434Protein Structure and DynamicsMachine Learning in BioinformaticsEnzyme Structure and Function

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

Direct-coupling analysis of residue coevolution captures native contacts across many protein families

Open access
Morcos, Faruck, Pagnani, Andrea, Lunt, Bryan, Bertolino, Arianna, Marks, Debora S., Sander, Chris, Zecchina, Riccardo, Onuchic, José N., Hwa, Terence, Weigt, Martin·2011·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.1111471108PMC PMC3241805
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Abstract

The similarity in the three-dimensional structures of homologous proteins imposes strong constraints on their sequence variability. It has long been suggested that the resulting correlations among amino acid compositions at different sequence positions can be exploited to infer spatial contacts within the tertiary protein structure. Crucial to this inference is the ability to disentangle direct and indirect correlations, as accomplished by the recently introduced direct-coupling analysis (DCA). Here we develop a computationally efficient implementation of DCA, which allows us to evaluate the accuracy of contact prediction by DCA for a large number of protein domains, based purely on sequence information. DCA is shown to yield a large number of correctly predicted contacts, recapitulating the global structure of the contact map for the majority of the protein domains examined. Furthermore, our analysis captures clear signals beyond intradomain residue contacts, arising, e.g., from alternative protein conformations, ligand-mediated residue couplings, and interdomain interactions in protein oligomers. Our findings suggest that contacts predicted by DCA can be used as a reliable guide to facilitate computational predictions of alternative protein conformations, protein complex formation, and even the de novo prediction of protein domain structures, contingent on the existence of a large number of homologous sequences which are being rapidly made available due to advances in genome sequencing.

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Research works printed but not linked: 6

  1. 10.1093/nar/gkp848 · DOI
  2. 10.1093/nar/gkp848 · DOI
  3. 10.1073/pnas.0805923106 · DOI · Paper page
  4. 10.1016/S1097-2765(03)00148-5 · DOI
  5. 10.1101/gad.1125603 · DOI
  6. 10.1002/j.1460-2075.1990.tb07409.x · DOI

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Metadata

Authors
Morcos, F., Pagnani, A., Lunt, B., Bertolino, A., Marks, D. S., Sander, C., Zecchina, R., Onuchic, J. N., Hwa, T., & Weigt, M.
Affiliations
  • University of California San Diego (US)
  • Politecnico di Torino (IT)
  • Institute for Scientific Interchange (IT)
  • Harvard University (US)
  • Memorial Sloan Kettering Cancer Center (US)
  • Center for Theoretical Biological Physics, University of California at San Diego, La Jolla, CA 92093-0374;
  • Biologie Computationnelle, Quantitative et Synthétique (FR)
ORCID
Venue
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Published
2011-11-21
Volume
108
Issue
49
Pages
E1293-301
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.1111471108
PMC
PMC3241805
OpenAlex
W2008545402
Cited by
1,434
References
55
Citations by year
2026: 93 · 2025: 99 · 2024: 102 · 2023: 112 · 2022: 145 · 2021: 142 · 2020: 107 · 2019: 134 · 2018: 105 · 2017: 101 · 2016: 82 · 2015: 73 · 2014: 65 · 2013: 48 · 2012: 23
FWCI
18.07
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • HAL (submittedVersion)
  • PORTO@Iris (submittedVersion)
  • PORTO Publications Open Repository TOrino (Politecnico di Torino) (submittedVersion)
  • arXiv (Cornell University)
Funders
National Institute of General Medical Sciences (R01GM106303)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
Keywords
direct coupling analysis, residue coevolution, protein contact prediction, native contacts, protein domains, homologous sequences, domain-domain interactions, protein oligomers, protein complex formation, de novo protein structure prediction, contact maps
MeSH terms
Algorithms, Amino Acids, Binding Sites, Models, Molecular, Protein Binding, Protein Conformation, Proteins, Reproducibility of Results, Computational Biology, Protein Interaction Mapping, Protein Multimerization

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