A novel in-silico approach for QSAR studies of anabolic and androgenic activities in the 17β-hydroxy-5α-androstane steroid family

Predictive Quantitative Structure-Activity Relationship (QSAR) models of anabolic and androgenic activities for the 17β-hydroxy-5α-androstane steroid family were obtained by means of multi-linear regression using quantum and physicochemical molecular descriptors and a genetic algorithm for the selection of the best set of descriptors. The model allows the identification, selection and future design of new steroid molecules with increased anabolic activity. Molecular descriptors included in reported models allow the structural interpretation of the biological process, evidencing the main role of the shape of molecules, hydrophobicity and electronic properties. The model for the anabolic/androgenic ratio (expressed by the weight of the levator ani muscle and ventral prostate in mice) predicts that: a) 2-cyano-17-α-methyl-17- β-acetoxy-5α-androst-2-ene is the most potent anabolic steroid in the group and b) the testosterone-3-cyclopentenyl-enoleter is the less potent one. The approach described in this paper is an alternative for the discovery and optimization of leading anabolic compounds.