ArticleElectronic structure (Bristol, England)2022
Convergence in determining enzyme functional descriptors across Kemp eliminase variants.
Article in Electronic structure (Bristol, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- SubTuner leverages physics-based modeling to complement AI in enzyme engineering toward non-native substrates.Chem catalysis · 2025Article
- Substrate Positioning Dynamics Involves a Non-Electrostatic Component to Mediate Catalysis.The journal of physical chemistry letters · 2023Article
- Mutexa: A Computational Ecosystem for Intelligent Protein Engineering.Journal of chemical theory and computation · 2023Review
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4 authors.
Funding
Abstract
Molecular simulations have been extensively employed to accelerate biocatalytic discoveries. Enzyme functional descriptors derived from molecular simulations have been leveraged to guide the search for beneficial enzyme mutants. However, the ideal active-site region size for computing the descriptors over multiple enzyme variants remains untested. Here, we conducted convergence tests for dynamics-derived and electrostatic descriptors on 18 Kemp eliminase variants across six active-site regions with various boundary distances to the substrate. The tested descriptors include the root-mean-square deviation of the active-site region, the solvent accessible surface area ratio between the substrate and active site, and the projection of the electric field (EF) on the breaking C-H bond. All descriptors were evaluated using molecular mechanics methods. To understand the effects of electronic structure, the EF was also evaluated using quantum mechanics/molecular mechanics methods. The descriptor values were computed for 18 Kemp eliminase variants. Spearman correlation matrices were used to determine the region size condition under which further expansion of the region boundary does not substantially change the ranking of descriptor values. We observed that protein dynamics-derived descriptors, including RMSD
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