Exploring QSARs for Binding Affinity of Azoles with CYP2B and CYP3A Enzymes Using GFA and G/PLS Techniques

Abstract

Eighteen azole compounds, including some commercial fungicides, reported by Daisuke Itokawa et al. have been subjected to quantitative structure-activity relationship (QSAR) analysis for their binding affinity with cytochrome enzymes CYP3A and CYP2B. The analyses were performed using electronic (Charge, FCharge, Apol, Dipole, HOMO, LUMO, and Sr), spatial (Radius of gyration, Jurs descriptors, Shadow indices, Area, PMI-mag, Density, Vm), different topological parameters (E-state index, kappa shape index, molecular connectivity index, subgraph cont, information content indices), and thermodynamic (Alog P, Alog P98, Molref) descriptors calculated using CERIUS2 version 10 software. Genetic function approximation and genetic partial least squares were used as chemometric tools for modeling. The derived binding affinity models are of high statistical quality (leave-one-out Q(2) ranging from 0.946 to 0.977). The selectivity models also satisfy the statistical significance (Q(2) ranging from 0.680 to 0.761). The models indicate that the binding affinity of these compounds is related to topological, steric, electronic, and spatial properties of the molecules. The spline-based genetic models indicate optimum range of different parameters. The models have also been validated by leave-25%-out cross-validation.