ArticlePLoS computational biology2020
Direct coupling analysis of epistasis in allosteric materials.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Evolutionary pathways in epistatic mechanical networks.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Article
- Decoding allosteric landscapes: computational methodologies for enzyme modulation and drug discovery.RSC chemical biology · 2025Review
- Impact of phylogeny on the inference of functional sectors from protein sequence data.PLoS computational biology · 2024Article
- Evolution shapes interaction patterns for epistasis and specific protein binding in a two-component signaling system.Communications chemistry · 2024Article
- Undersampling and the inference of coevolution in proteins.Cell systems · 2023Article
- Impact of phylogeny on structural contact inference from protein sequence data.Journal of the Royal Society, Interface · 2023Article
- A Model for Allosteric Communication in Drug Transport by the AcrAB-TolC Tripartite Efflux Pump.Antibiotics (Basel, Switzerland) · 2022Article
- Episodic evolution of coadapted sets of amino acid sites in mitochondrial proteins.PLoS genetics · 2021Article
- Mechanics of Allostery: Contrasting the Induced Fit and Population Shift Scenarios.Biophysical journal · 2019Article
- Revealing evolutionary constraints on proteins through sequence analysis.PLoS computational biology · 2019Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In allosteric proteins, the binding of a ligand modifies function at a distant active site. Such allosteric pathways can be used as target for drug design, generating considerable interest in inferring them from sequence alignment data. Currently, different methods lead to conflicting results, in particular on the existence of long-range evolutionary couplings between distant amino-acids mediating allostery. Here we propose a resolution of this conundrum, by studying epistasis and its inference in models where an allosteric material is evolved in silico to perform a mechanical task. We find in our model the four types of epistasis (Synergistic, Sign, Antagonistic, Saturation), which can be both short or long-range and have a simple mechanical interpretation. We perform a Direct Coupling Analysis (DCA) and find that DCA predicts well the cost of point mutations but is a rather poor generative model. Strikingly, it can predict short-range epistasis but fails to capture long-range epistasis, in consistence with empirical findings. We propose that such failure is generic when function requires subparts to work in concert. We illustrate this idea with a simple model, which suggests that other methods may be better suited to capture long-range effects.
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