Hansch-Type QSAR Models for the Rational Design of MAO Inhibitors: Basic Principles and Methodology

Abstract

Hansch-type regression analysis enables the derivation of quantitative structure-activity relationship (QSAR) equations correlating bioactivity data with physicochemical parameters accounting for hydrophobicity, electronic properties, and steric effects of molecules or functional groups (substituents). Two datasets of MAO A and B inhibitors were enrolled in prototypical workflows employing multiparametric stepwise regression analysis, which includes linear and nonlinear (generally quadratic) terms. The optimal choice of variables (and/or combinations thereof) along with statistical validation yielded two robust equations describing MAO B potency and B/A selectivity, which included three and one parameter(s), respectively, and explained more than 80% of y-variance (r²) with low standard deviation (s) and good statistical significance (F, Fisher value).

Keywords: Drug design; Hansch-type QSAR; Linear free-energy relationship; MAO inhibitors; Multiple regression analysis.