Phytoconstituents of traditional Himalayan Herbs as potential inhibitors of Human Papillomavirus (HPV-18) for cervical cancer treatment: An In silico Approach.

PloS one 2022

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Human papillomavirus (HPV) induced cervical cancer is becoming a major cause of mortality in women. The present research aimed to identify the natural inhibitors of HPV-18 E1 protein (1R9W) from Himalayan herbs with lesser toxicity and higher potency. In this study, one hundred nineteen phytoconstituents of twenty important traditional medicinal plants of Northwest Himalayas were selected for molecular docking with the target protein 1R9W of HPV-18 E1 Molecular docking was performed by AutoDock vina software. ADME/T screening of the bioactive phytoconstituents was done by SwissADME, admetSAR, and Protox II. A couple of best protein-ligand complexes were selected for 100 ns MD simulation. Molecular docking results revealed that among all the selected phytoconstituents only thirty-five phytoconstituents showed the binding affinity similar or more than the standard anti-cancer drugs viz. imiquimod (-6.1 kJ/mol) and podofilox (-6.9 kJ/mol). Among all the selected thirty-five phytoconstituents, eriodictyol-7-glucuronide, stigmasterol, clicoemodin and thalirugidine showed the best interactions with a docking score of -9.1, -8.7, -8.4, and -8.4 kJ/mol. Based on the ADME screening, only two phytoconstituents namely stigmasterol and clicoemodin selected as the best inhibitor of HPV protein. MD simulation study also revealed that stigmasterol and clicoemodin were stable inside the binding pocket of 1R9W, Stigmasterol and clicoemodin can be used as a potential investigational drug to cure HPV infections.

Citation

Deeksha Salaria, Rajan Rolta, Jyoti Mehta, Oladoja Awofisayo, Olatomide A Fadare, Baljinder Kaur, Balvir Kumar, Renato Araujo da Costa, Shikha Rangra Chandel, Neha Kaushik, Eun Ha Choi, Nagendra Kumar Kaushik. Phytoconstituents of traditional Himalayan Herbs as potential inhibitors of Human Papillomavirus (HPV-18) for cervical cancer treatment: An In silico Approach. PloS one. 2022;17(3):e0265420