ArticleACS catalysis2020
Combinatorial Approach for Exploring Conformational Space and Activation Barriers in Computer-Aided Enzyme Design.
Article in ACS catalysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Decoding Enzymatic Dechlorination with Multiscale Modeling: Mechanistic Insights into Native Haloalkane Dehalogenase fromACS catalysis · 2025Article
- Biochemical and Computational Characterization of Haloalkane Dehalogenase Variants Designed by Generative AI: Accelerating the SJournal of the American Chemical Society · 2025Article
- Theoretical Improvements in Enzyme Efficiency Associated with Noisy Rate Constants and Increased Dissipation.Entropy (Basel, Switzerland) · 2024Article
- Computational design of highly efficient thermostable MHET hydrolases and dual enzyme system for PET recycling.Communications biology · 2023Article
- Enzyme Engineering Strategies for the Bioenhancement of L-Asparaginase Used as a Biopharmaceutical.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2023Review
- Transient water wires mediate selective proton transport in designed channel proteins.Nature chemistry · 2023Article
- Enhancing computational enzyme design by a maximum entropy strategy.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Redesigning Enzymes for Biocatalysis: Exploiting Structural Understanding for Improved Selectivity.Frontiers in molecular biosciences · 2022Review
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Authors and funding
3 authors.
Funding
Abstract
Computer-aided enzyme design is a field of great potential importance for biotechnological applications, medical advances, and a fundamental understanding of enzyme action. However, reaching a predictive ability in this direction is extremely challenging. It requires both the ability to predict quantitatively the activation barriers in cases where the structure and sequence are known and the ability to predict the effect of different mutations. In this work, we propose a protocol for predicting reasonable starting structures of mutants of proteins with known structures and for calculating the activation barriers of the generated mutants. Our approach also allows us to use the predicted structures of the generated mutant to predict structures and activation barriers for subsequent set of mutations. This protocol is used to examine the reliability of the
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