Date of Award
2007
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Chemistry
First Advisor
Dr. Jerome A. Darsey
Second Advisor
Dr. Cesar M. Compadre
Abstract
Cytochrome P450 3A4 (CYP3A4) plays a pivotal role in the metabolism of xenobiotics. Methylenedioxobenzene containing natural products have been shown to inhibit CYP3A4. Given that these compounds are widely distributed in nature there is a strong potential for drug interaction with many plants used for dietary or medicinal purposes. In this research we have developed two different computational models (Comparative Molecular Field Model and Artificial Neural Network Model) to assist in the identification of potentially strong inhibitors that could be further studied for potential inhibitory effects. These models were used to screen for the CYP3A4 inhibitory effects of 100 naturally occurring compounds. Of these berberine, methysticin, myristicin, sesamin and sesmolin were identified as the most likely the have strong inhibitory effects.
Recommended Citation
Thotakura, Sushma, "Computational Models to Predict the Inhibition of Cytochrome P450 3A4 by Selected Natural Compounds" (2007). Theses and Dissertations. 61.
https://research.ualr.edu/etd/61
