ArticleProceedings of the National Academy of Sciences of the United States of America2011
Direct-coupling analysis of residue coevolution captures native contacts across many protein families.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 750 papers.
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750 citing papers in PubMed.
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- Review
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- Toward reliable machine learning models for neural circuit inference: A diagnostic study of CNNs on spike trains.PLoS computational biology · 2026Article
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- Decoding cryptic defluorinases through a latent generative sequence landscape.Chemical science · 2026Article
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- Artificial intelligence and automation in enzyme engineering: evolution, advances, and future perspectives.Bioresources and bioprocessing · 2026Review
- Beyond native sequence recovery: Improved modeling of the sequence-energy landscape of protein structures.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Epistasis and co-adaptation in bacterial genome evolution.Nature reviews. Genetics · 2026Review
- Small Structural Variations, Large Functional Consequences: Comparative Analysis Reveals Structural Control of Ubiquitylation Site Selection by BRCA1/BARD1.bioRxiv : the preprint server for biology · 2026Article
- Evolutionary and molecular characteristics of high-Shannon entropy codons in VP1 of Coxsackievirus A6.The Journal of general virology · 2026Article
- Probe-based identification of metal-binding sites using deep learning representations.Nature communications · 2026Article
690 more citing papers are in PubMed but not listed here.
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10 authors.
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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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