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Computational models for cytochrome P450: a predictive electronic model for aromatic oxidation and hydrogen atom
Jeffrey P Jones1, Michael Mysinger, Kenneth Ray Korzekwa
1Department of Chemistry, Washington State University, Pullman, WA 99164, USA. jpj@wsu.edu
Drug Metabolism and Disposition: the Biological Fate of Chemicals
|December 18, 2001
Summary
This study develops a combined computational model for cytochrome P450 enzymes, predicting oxidation rates for aromatic and aliphatic hydroxylation. The model accurately correlates electronic properties with reaction speeds, enhancing predictive capabilities.
Area of Science:
- Biochemistry
- Computational Chemistry
- Enzymology
Background:
- Electronic characteristics influence substrate oxidation rates in cytochrome P450 enzymes.
- Radical stability correlates with oxidation tendencies (e.g., N-dealkylation > O-dealkylation).
Purpose of the Study:
- To develop a combined computational model for predicting both aromatic and aliphatic hydroxylation rates.
- To extend previous aliphatic hydroxylation models to include aromatic oxidation.
Main Methods:
- Utilized experimental data and semiempirical molecular orbital calculations.
- Predicted activation energies for aromatic and aliphatic hydroxylation reactions.
Main Results:
- Developed a combined model accounting for 83% of the variance in oxidation rates for 20 compounds.
- Achieved an error of approximately 0.7 kcal/mol in predictions.
- Successfully integrated aromatic hydroxylation into a predictive model.
Conclusions:
- A unified computational model can effectively predict cytochrome P450 oxidation rates.
- Electronic models provide valuable correlations for enzyme kinetics.
- The combined model enhances the prediction of key drug metabolism pathways.