ArticleProtein science : a publication of the Protein Society2016
How mutational epistasis impairs predictability in protein evolution and design.
Article in Protein science : a publication of the Protein Society, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers.
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104 citing papers in PubMed.
- The fitness landscape of a form II rubisco in a photosynthetic bacterium guides engineering of oxygen tolerance.Science advances · 2026Article
- Epistasis: Just say no!The Journal of biological chemistry · 2026Review
- Rank-guided learning accelerates automated enzyme engineering.Nature communications · 2026Article
- Engineering selective amyloid precursor protein inhibitors by machine learning and deep mutational scanning.Protein science : a publication of the Protein Society · 2026Article
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- Harnessing Nature's Algorithm: From Test Tubes to Autonomous In Vivo Evolution.Biotechnology journal · 2026Review
- Biophysical trade-offs in antibody evolution are resolved by conformation-mediated epistasis.bioRxiv : the preprint server for biology · 2026Article
- Structural and evolutionary constraints of organophosphate resistance in dipteran carboxylesterases.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Inferring context-specific site variation with evotuned protein language models.NAR genomics and bioinformatics · 2026Article
- Functional bottlenecks can emerge from non-epistatic underlying traits.PLoS computational biology · 2026Article
- Factors controlling protein evolvability-at the molecular scale.European biophysics journal : EBJ · 2026Article
- Dynamic signature of activity-stability tradeoff in lactamase evolution.Nature communications · 2026Article
- Advances in Machine Learning Models for Predicting Enzyme Kinetic Parameters.Journal of chemical information and modeling · 2026Review
- Graph attention with structural features improves the generalizability of identifying functional sequences at a protein interface.bioRxiv : the preprint server for biology · 2025Article
- Phosphate ions modulate enzyme activity and epistatic effects in two clavulanic acid-resistant β-lactamase mutants.Protein science : a publication of the Protein Society · 2025Article
- Effect of Mutations on the Evolution of Extended Spectrum β-lactamases (ESBL).The protein journal · 2025Review
- Distal mutations enhance catalysis in designed enzymes by facilitating substrate binding and product release.Nature communications · 2025Article
- Comprehensive profiling of activity and specificity of RNA-guided transposons reveals opportunities to engineer improved variants.Nucleic acids research · 2025Article
- Machine learning-guided evolution of pyrrolysyl-tRNA synthetase for improved incorporation efficiency of diverse noncanonical amino acids.Nature communications · 2025Article
- A Cyanobacterial Screening Platform for Rubisco Mutant Variants.ACS synthetic biology · 2025Article
44 more citing papers are in PubMed but not listed here.
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2 authors.
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Abstract
There has been much debate about the extent to which mutational epistasis, that is, the dependence of the outcome of a mutation on the genetic background, constrains evolutionary trajectories. The degree of unpredictability introduced by epistasis, due to the non-additivity of functional effects, strongly hinders the strategies developed in protein design and engineering. While many studies have addressed this issue through systematic characterization of evolutionary trajectories within individual enzymes, the field lacks a consensus view on this matter. In this work, we performed a comprehensive analysis of epistasis by analyzing the mutational effects from nine adaptive trajectories toward new enzymatic functions. We quantified epistasis by comparing the effect of mutations occurring between two genetic backgrounds: the starting enzyme (for example, wild type) and the intermediate variant on which the mutation occurred during the trajectory. We found that most trajectories exhibit positive epistasis, in which the mutational effect is more beneficial when it occurs later in the evolutionary trajectory. Approximately half (49%) of functional mutations were neutral or negative on the wild-type background, but became beneficial at a later stage in the trajectory, indicating that these functional mutations were not predictable from the initial starting point. While some cases of strong epistasis were associated with direct interaction between residues, many others were caused by long-range indirect interactions between mutations. Our work highlights the prevalence of epistasis in enzyme adaptive evolution, in particular positive epistasis, and suggests the necessity of incorporating mutational epistasis in protein engineering and design to create highly efficient catalysts.
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