Aims and Objective: In this study, a novel quantitative structure activity relationship
(QSAR) model has been developed for inhibitors of human 5-alpha reductase type II, which are
used to treat benign prostate hypertrophy (BPH).
Methods: The dataset consisted of 113 compounds-mainly nonsteroidal-with known inhibitory
concentration. Then 3D structures of compounds were optimized and molecular structure descriptors
were calculated. The stepwise multiple linear regression was used to select descriptors
encoding the inhibitory activity of the compounds. Multiple linear regression (MLR) was used to
build up the linear QSAR model.
Results: The results obtained revealed that the descriptors which best describe the activity were
atom type electropological state, carbon type, radial distribution function (RDF), barysz matrix
and molecular linear free energy relation. The suggested model could achieve satisfied square correlation
coefficient of R2 = 0.72, higher than of many previous studies, indicating its superiority.
Rigid validation criteria were met using external data with Q2 ˃ 0.5 and R2 = 0.75, reflecting the
predictive power of the model.
Conclusion: The QSAR model was applied for screening botanical components of herbal preparations
used to treat BPH, and could predict the activity of some, among others, making reasonable
attribution to the proposed effect of these preparations. Gamma tocopherol was found to be an active
inhibitor, in consistence with many previous studies, anticipating the power of this model in
the prediction of new candidate molecules and suggesting further investigations.