Molecular insights into a mechanism of resveratrol action using hybrid computational docking/CoMFA and machine learning approach

Abstract

A phytoalexin, Resveratrol remains a legendary anticancer drug candidate in the archives of scientific literature. Although earlier wet-lab experiments rendering its multiple biological targets, for example, epidermal growth factors, Pro-apoptotic protein p53, sirtuins, and first apoptosis signal (Fas) receptor, Mouse double minute 2 (MDM2) ubiquitin-protein ligase, Estrogen receptor, Quinone reductase, etc. However, notwithstanding some notable successes, identification of an appropriate Resveratrol target(s) has remained a major challenge using physical methods, and hereby limiting its translation into an effective therapeutic(s). Thus, computational insights are much needed to establish proof-of-concept towards potential Resveratrol target(s) with minimum error rate, narrow down the search space, and to assess a more accurate Resveratrol signaling pathway/mechanism at the starting point. Herein, a brute-force technique combining computational receptor-, ligand-based virtual screening, and classification-based machine learning, reveals the precise mechanism of Resveratrol action. Overall, MDM2 ubiquitin-protein ligase (4OGN.pdb) and co-crystallized quinone reductases 2 (4QOH.pdb) were found two suitable drug targets in the case of Resveratrol derivatives. Indeed, carotenoid cleaving oxygenase together with later twos gave gigantic momentum in guiding the rational drug design of Resveratrol derivatives. These molecular modeling insights would be useful for Resveratrol lead optimization into a more precise science.

Communicated by Ramaswamy H. Sarma

Keywords:

• Breast cancer
• receptor-based docking
• ligand-based CoMFA/CoMSIA
• resveratrol derivatives
• MCF-7 cell line
• random forest

Acknowledgments

PG thanks to the MHRD, Govt. of India for postdoctoral funding. The authors are thankful to Prof. Sanjay Jasola Vice-Chancellor GEHU India for detailed comments that greatly improved the quality of the paper. Authors are also thankful to Department of Chemistry, IIT Roorkee for providing necessary facilities and constructive comments. Part of this work was performed using the Discovery Studio at UTU, India by the DBT, Govt. of India project support.

Disclosure statement

The authors declare no competing financial interest.

Additional information

Funding

Department of Biotechnology (DBT), Govt. of India (Grant No. BCIL/NER-BPMC/2013-541)