Preprint Article Version 1 NOT YET PEER-REVIEWED

Human Caveolin-1 a Potent Inhibitor for Prostate Cancer Therapy: A Computational Approach

  1. Centre for Computational Biology and Bioinformatics, Amity Institute of Biotechnology, Amity University (Noida Campus), Noida-201301, India
  2. Department of Biotechnology, TERI University, 10 Institutional Area, Vasant kunj, New Delhi-110070, India
  3. Department of Biosciences, Jamia Millia Islamia (A Central University), New Delhi-110025, India
  4. Research & Scientific Studies Unit, College of Nursing & Allied Health Sciences, Jazan University, Jazan-45142, Saudi Arabia
  5. Department of Biotechnology, Sharda University, Greater Noida-201306, India
Version 1 : Received: 7 October 2016 / Approved: 7 October 2016 / Online: 7 October 2016 (12:09:06 CEST)

How to cite: Khanam, U.; Somvanshi, P.; Haque, S.; Malik, B.; Rathi, B. Human Caveolin-1 a Potent Inhibitor for Prostate Cancer Therapy: A Computational Approach. Preprints 2016, 2016100016 (doi: 10.20944/preprints201610.0016.v1). Khanam, U.; Somvanshi, P.; Haque, S.; Malik, B.; Rathi, B. Human Caveolin-1 a Potent Inhibitor for Prostate Cancer Therapy: A Computational Approach. Preprints 2016, 2016100016 (doi: 10.20944/preprints201610.0016.v1).

Abstract

Caveolin-1 (Cav-1) is 22 kDa caveolae protein, acts as a scaffold within caveolar membranes. It interacts with alpha subunits of G-protein and thereby regulates their activity. Earlier studies reported elevated or up-regulated levels of caveolin-1 in the serum of prostate cancer patients. Secreted Cav-1 promotes angiogenesis, cell proliferation and anti-apoptotic activities in prostate cancer patients. Cav-1 upregulation is mainly related to prostate cancer metastasis. Keeping above facts in view, the present study was designed to explore Cav-1 as a target for prostate cancer therapy using computational approach. Molecular docking, structural base molecular modelling and molecular dynamics simulations were performed to investigate Cav-1 inhibitors. A predictive model was generated and validated to establish a stable structure. ZINC database of biogenic compounds was used for induced fit docking (IFD) and high throughput virtual screening. The H-bond interactions of the compounds with active site residues of Cav-1 were estimated by IFD and 100 ns long molecular dynamic simulations. The reported compounds showed significant binding and thus can be considered as potent therapeutic inhibitors of Cav-1. This study provides a valuable insight into biochemical interactions of Cav-1 for therapeutic applications and warrants for experimental validation of the predicted ‘active(s)’.

Subject Areas

molecular dynamics simulation; virtual screening; molecular docking; prostate cancer; caveolin-1

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