ArticleProceedings of the National Academy of Sciences of the United States of America2022
Enhancing computational enzyme design by a maximum entropy strategy.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Evaluating Mechanical-Embedding ML/MM for Predicting Mutation Effects in Chorismate Mutase Catalysis.Journal of chemical theory and computation · 2026Article
- Generative AI for controllable protein sequence design: A survey.npj drug discovery · 2026Review
- Chemical neighborhood exploration for substrate discovery in biocatalysis.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Semi-rational design of the N-terminal of Chondroitinase ABC to improve the catalytic activity.World journal of microbiology & biotechnology · 2026Article
- Generative Artificial Intelligence-Empowered Virtual Evolution of Enzyme with the VERnet Model.ACS catalysis · 2026Article
- What Determines the Directionality of Kinesins? Studying the Anomalous Directionality of Nonclaret Disjunctional Motor Mutants.Journal of the American Chemical Society · 2026Article
- Exploring evolutionary trajectories of drug resistance.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Amino acid substitutions at rheostat positions in the NaProtein science : a publication of the Protein Society · 2025Article
- Identification and understanding of allostery hotspots in proteins: Integration of deep mutational scanning and multi-faceted computational analyses.Journal of molecular biology · 2025Review
- Approaches for regulating enzyme activities: Recent advances in experiment and computation.Current opinion in structural biology · 2025Review
- Decoding Enzymatic Dechlorination with Multiscale Modeling: Mechanistic Insights into Native Haloalkane Dehalogenase fromACS catalysis · 2025Article
- Dissecting the effects of single amino acid substitutions in SARS-CoV-2 Mpro.Protein science : a publication of the Protein Society · 2025Article
- Machine learning in molecular biophysics: Protein allostery, multi-level free energy simulations, and lipid phase transitions.Biophysics reviews · 2025Review
- Engineering Dehalogenase Enzymes Using Variational Autoencoder-Generated Latent Spaces and Microfluidics.JACS Au · 2025Article
- Biochemical and Computational Characterization of Haloalkane Dehalogenase Variants Designed by Generative AI: Accelerating the SJournal of the American Chemical Society · 2025Article
- Rheostatic contributions to protein stability can obscure a position's functional role.Protein science : a publication of the Protein Society · 2024Article
- Biosynthetic production of anticoagulant heparin polysaccharides through metabolic and sulfotransferases engineering strategies.Nature communications · 2024Article
- Engineering Proteins Using Statistical Models of Coevolutionary Sequence Information.Cold Spring Harbor perspectives in biology · 2024Review
- Rheostats, toggles, and neutrals, Oh my! A new framework for understanding how amino acid changes modulate protein function.The Journal of biological chemistry · 2024Review
- Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering.ACS central science · 2024Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Although computational enzyme design is of great importance, the advances utilizing physics-based approaches have been slow, and further progress is urgently needed. One promising direction is using machine learning, but such strategies have not been established as effective tools for predicting the catalytic power of enzymes. Here, we show that the statistical energy inferred from homologous sequences with the maximum entropy (MaxEnt) principle significantly correlates with enzyme catalysis and stability at the active site region and the more distant region, respectively. This finding decodes enzyme architecture and offers a connection between enzyme evolution and the physical chemistry of enzyme catalysis, and it deepens our understanding of the stability-activity trade-off hypothesis for enzymes. Overall, the strong correlations found here provide a powerful way of guiding enzyme design.
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