ArticleBiopolymers2023
Chasing long-range evolutionary couplings in the AlphaFold era.
Article in Biopolymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Nanobodies: From Discovery to AI-Driven Design.Biology · 2025Review
- An augmented transformer model trained on protein family specific variant data leads to improved prediction of variants of uncertain significance.Human genetics · 2025Article
- Advances of deep Neural Networks (DNNs) in the development of peptide drugs.Future medicinal chemistry · 2025Review
- Evolutionary analysis of ZAP and its cofactors identifies intrinsically disordered regions as central elements in host-pathogen interactions.Computational and structural biotechnology journal · 2024Article
- Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies.Structural dynamics (Melville, N.Y.) · 2024Article
- Exploring the Alternative Conformation of a Known Protein Structure Based on Contact Map Prediction.Journal of chemical information and modeling · 2024Article
- Representing structures of the multiple conformational states of proteins.Current opinion in structural biology · 2023Review
- Systematic identification of conditionally folded intrinsically disordered regions by AlphaFold2.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Chasing long-range evolutionary couplings in the AlphaFold era.Biopolymers · 2023Article
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1 author.
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Abstract
Coevolution between protein residues is normally interpreted as direct contact. However, the evolutionary record of a protein sequence contains rich information that may include long-range functional couplings, couplings that report on homo-oligomeric states or even conformational changes. Due to the complexity of the sequence space and the lack of structural information on various members of a protein family, it has been difficult to effectively mine the additional information encoded in a multiple sequence alignment (MSA). Here, taking advantage of the recent release of the AlphaFold (AF) database we attempt to identify coevolutionary couplings that cannot be explained simply by spatial proximity. We propose a simple computational method that performs direct coupling analysis on a MSA and searches for couplings that are not satisfied in any of the AF models of members of the identified protein family. Application of this method on 2012 protein families suggests that ~12% of the total identified coevolving residue pairs are spatially distant and more likely to be disordered than their contacting counterparts. We expect that this analysis will help improve the quality of coevolutionary distance restraints used for structure determination and will be useful in identifying potentially functional/allosteric cross-talk between distant residues.
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