Abstract
In prostate cancer (PC), drugs targeting CYP17A1 have shown great success in regulating PC progression. However, successful drug molecules show adverse side effects and therapeutic resistance in PC. Therefore, we proposed to discover the potent phytochemical-based inhibitor against CYP17A1 using virtual screening. In this study, a phytochemicals library of ∼13800 molecules was selected to screen the best possible inhibitors against CYP17A1. A molecular modelling approach investigated detailed intermolecular interactions, their structural stability, and binding affinity. Further, in vitro and in vivo studies were performed to confirm the anticancer activity of identified potential inhibitor against CYP17A1. Friedelin from Cassia tora (CT) is identified as the best possible inhibitor from the screened library. MD simulation study reveals stable binding of Friedelin to conserved binding pocket of CYP17A1 with higher binding affinity than studied control, that is, Orteronel. Friedelin was tested on hormone-sensitive (22Rv1) and insensitive (DU145) cell lines and the IC50 value was found to be 72.025 and 81.766 µg/ml, respectively. CT extract showed a 25.28% IC50 value against 22Rv1, ∼92.6% increase in late Apoptosis/Necrosis, and three folds decrease in early apoptosis in treated cells compared to untreated cells. Further, animal studies show a marked decrease in prostate weight by 39.6% and prostate index by 36.5%, along with a reduction in serum PSA level by 71.7% and testosterone level by 92.4% compared to the testosterone group, which was further validated with histopathological studies. Thus, we propose Friedelin and CT extract as potential leads, which could be taken further for drug development in PC.
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Communicated by Ramaswamy H. Sarma
Acknowledgments
The authors thank UTU management and Director, CGBIBT, for their constant support and providing the necessary facilities to carry out the work. The authors also thank the Department of Biosciences, VNSGU, for providing the necessary computational resources to carry out the work.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Author contribution
BJ proposed the research objectives, designed the methodology, performed computational and experimental studies (in vitro and in vivo), and wrote the manuscript. VB analysed the computational data and wrote computational methodology and novel in silico findings in the manuscript. MV helped in performing animal studies. PP performed a statistical analysis of the collected data. RK monitored the progress, analysed the data and corrected the manuscript. RP provided computational resources to perform the molecular modelling study. BV monitored in vitro and in vivo experiments, analysed the results, and edited the manuscript.