Quantitative Structure–Activity Relationship Studies for the Binding Affinities of Imidazobenzodiazepines for the α6 Benzodiazepine Receptor Isoform Utilizing Optimized Blockwise Variable Combination by Particle Swarm Optimization for Partial Least Squares Modeling

Abstract

Binding affinities of a series of substituted imidazobenzodiazepines for the a6 Benzodiazepine Receptor (BzR) isoform are investigated by the Optimized Blockwise Variable Combination (OBVC) by Particle Swarm Optimization (PSO) based on Partial Least Squares (PLS) modeling. The QSAR analysis result showed that MolRef, AlogP, MR CM**-3 , Rotatable bonds (Rotlbonds), Hydrogen Bond Acceptors (Hbond acceptor), five Jurs descriptors, two Shadow indices descriptors and principal moment of inertia are the most important descriptors among all the investigated descriptors. One can change the molar refractivity, the polar interactions between molecules, the shape of the molecules, the principal moments of inertia about the principal axes of a molecule, the hydrophobic character of the molecule, the number of Rotlbonds and Hbond acceptors of the compounds to adjust the binding affinities of imidazobenzodiazepine for the a6 BzR isoform. The Quantitative Structure -Activity Relationship (QSAR) analysis result was also compared with MLR, PLS, and hierarchical PLS algorithms. It has been demonstrated that OBVC by PSO for PLS modeling shows satisfactory performance in the QSAR analysis.