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Novel and Predictive QSAR Model for Steroidal and Nonsteroidal 5α- Reductase Type II Inhibitors

Author(s):

Huda Mando, Ahmad Hassan and Sajjad Gharaghani*   Pages 1 - 16 ( 16 )

Abstract:


In this study, 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). 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. 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. 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 active inhibitor, in consistence with many previous studies, anticipating the power of this model in prediction of new candidate molecules and suggesting further investigations.

Keywords:

QSAR, 5α-Reductase, BHP, inhibitor, prostate

Affiliation:

Department of Pharmaceutical chemistry and quality control of medicaments, Faculty of Pharmacy, Damascus University, Damascus, Department of Pharmaceutical chemistry and quality control of medicaments, Faculty of Pharmacy, Damascus University, Damascus, Department of Bioinformatics, Laboratory of Bioinformatics and Drug Design, Institute of Biochemistry and Biophysics, University of Tehran, Tehran



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