Regression Modeling for the Prediction of Hydrogen Atom Transfer Barriers in Cytochrome P450 from Semi‐empirically Derived Descriptors
Author:
Affiliation:
1. Department of Chemistry University of California, Davis One Shields Avenue Davis CA-95616 USA
Publisher
Wiley
Subject
Materials Science (miscellaneous)
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/cmtd.202100108
Reference60 articles.
1. Mechanism of Oxidation Reactions Catalyzed by Cytochrome P450 Enzymes
2. Cytochrome P450 Compound I: Capture, Characterization, and C-H Bond Activation Kinetics
3. Cytochrome P450—The Wonderful Nanomachine Revealed through Dynamic Simulations of the Catalytic Cycle
4. Gauging the Relative Oxidative Powers of Compound I, Ferric-Hydroperoxide, and the Ferric-Hydrogen Peroxide Species of Cytochrome P450 Toward C−H Hydroxylation of a Radical Clock Substrate
5. Hydrocarbon Hydroxylation by Cytochrome P450 Enzymes
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1. C–H bond dissociation enthalpy prediction with machine learning reinforced semi-empirical quantum mechanical calculations;Chemistry Letters;2024-01-31
2. Repurposing quantum chemical descriptor datasets for on-the-fly generation of informative reaction representations: application to hydrogen atom transfer reactions;Digital Discovery;2024
3. Semi-empirical and machine learning-based prediction of site of metabolisms mediated by aldehyde oxidase;Chemical Physics Letters;2023-12
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