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).
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Pisani, L., de Candia, M., Rullo, M., Altomare, C.D. (2023). Hansch-Type QSAR Models for the Rational Design of MAO Inhibitors: Basic Principles and Methodology. In: Binda, C. (eds) Monoamine Oxidase. Methods in Molecular Biology, vol 2558. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2643-6_16
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DOI: https://doi.org/10.1007/978-1-0716-2643-6_16
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