title: Development of CYP3A4 inhibition models: comparisons of machine-learning techniques and molecular descriptors.
abstract: Computational models of cytochrome P450 3A4 inhibition were developed based on high-throughput screening data for 4470 proprietary compounds. Multiple models differentiating inhibitors (IC(50) <3 microM) and noninhibitors were generated using various machine-learning algorithms (recursive partitioning [RP], Bayesian classifier, logistic regression, k-nearest-neighbor, and support vector machine [SVM]) with structural fingerprints and topological indices. Nineteen models were evaluated by internal 10-fold cross-validation and also by an independent test set. Three most predictive models, Barnard Chemical Information (BCI)-fingerprint/SVM, MDL-keyset/SVM, and topological indices/RP, correctly classified 249, 248, and 236 compounds of 291 noninhibitors and 135, 137, and 147 compounds of 179 inhibitors in the validation set. Their overall accuracies were 82%, 82%, and 81%, respectively. Investigating applicability of the BCI/SVM model found a strong correlation between the predictive performance and the structural similarity to the training set. Using Tanimoto similarity index as a confidence measurement for the predictions, the limitation of the extrapolation was 0.7 in the case of the BCI/SVM model. Taking consensus of the 3 best models yielded a further improvement in predictive capability, kappa = 0.65 and accuracy = 83%. The consensus model could also be tuned to minimize either false positives or false negatives depending on the emphasis of the screening.
authors.affiliation: Pfizer Global Research and Development, Ann Arbor, Michigan, USA. rieko_arimoto@vrtx.com
authors.forename: Rieko
authors.initials: R
authors.lastname: Arimoto
authors.forename: Madhu-Ashni
authors.initials: MA
authors.lastname: Prasad
authors.forename: Eric M
authors.initials: EM
authors.lastname: Gifford
mesh_terms: D001185:Artificial Intelligence; D003198:Computer Simulation; D051544:Cytochrome P-450 CYP3A; D065607:Cytochrome P-450 Enzyme Inhibitors; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D004791:Enzyme Inhibitors / Q000737:chemistry* / Q000494:pharmacology; D006801:Humans; D008956:Models, Chemical; D008958:Models, Molecular; D015394:Molecular Structure
chemical_list: D065607:Cytochrome P-450 Enzyme Inhibitors; D004791:Enzyme Inhibitors; C104464:CYP3A protein, human; D051544:Cytochrome P-450 CYP3A; C510163:CYP3A4 protein, human