Monte Carlo optimization method based QSAR modeling of postmortem redistribution of structurally diverse drugs

Abstract

Post-mortem redistribution (PMR) involves a multifaceted process that renders the analytical results of drug concentrations inaccurate for the interpretation of forensic toxicologists. The present study's aim was to assess whether quantitative structure–activity relationship (QSAR) methodology may prove to be an effective tool for the estimation of the capability of drug redistribution across tissue barriers during the post-mortem period on the grounds of their conformation – Independent molecular descriptors. With this in mind, the Monte Carlo optimization method was administered to a set of 76 drugs with a diverse structure, randomly split into three training and test sets. Literature was consulted for the purpose of expressing the PMR data with the central : peripheral concentration ratio (C : P ratio). The best developed QSAR model (r² = 0.8505, q² = 0.8374, s = 0.333, MAE = 0.253, F = 313 for the training set; r² = 0.8551, q² = 0.8128, s = 0.297, MAE = 0.237, F = 100 for the test set) was established for 59 (75%) out of the 77 drugs. The developed QSAR model showed considerable applicability and illustrated the contribution of the molecular fragments in the PMR process. Owing to the great complexity of the PMR process, subsequent QSAR studies need to focus on structurally related drugs in order to develop more specific models, which might serve as alternative tools for the evaluation of PMR in different chemical classes.