In Silico ADMET and Docking Study of Selected Drug Used in Therapy of COVID-19
Authors
- Sagar Ashok Jadhav
- Payal Pandurang Chavan
- Supriya Suresh Shete
- Dipti Shantisagar Patil
- Saroj Dyandev Kolekar
- Godfrey Rudolph Mathews
- Dipak Babaso Bhingardeve
- Pravin Kondiba Pawar
Keywords
Docking, AUTO-DOCK VINA, PYMOL
Abstract
Docking is one of the most widely utilized technique used method in structure -based drug design because of its capability to predict the binding conformation of ligands to appropriate target. Ability of binding/ affinity towards the target i.e., bioactive peptides or specific receptor provides strong evidence of binding conformation pattern and affinity for further investigation. Aim- The present study was conducted for evaluation of current API’s potential used in COVID-19. Methods: In-silico molecular docking was performed using softwares such as SWISS ADME, MOLSOFT, MOLINSPIRATION, PYMOL, AUTO-DOCK VINA AND BIOVIA DS VISUALIZER. Results: The current research comprehend the drug likeliness character of selected API’s and their binding affinity with various targets selected by SWISS TARGET PREDICTION. Conclusion: The present investigation suggests that all the targets follow Lipinski rule of five except Remdesivir and Anakinra besides which it possesses enhanced binding affinity toward targets, the binding energy of the protein ligand interaction additionally confirms that the ligand fits into the dynamite pockets which proves to be evident for further in- vivo and in-vitro evaluations.
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How to Cite
Sagar Ashok Jadhav, Payal Pandurang Chavan, Supriya Suresh Shete, Dipti Shantisagar Patil, Saroj Dyandev Kolekar, Godfrey Rudolph
Mathews, Dipak Babaso Bhingardeve and Pravin Kondiba Pawar. In Silico ADMET and Docking Study of Selected Drug Used in Therapy of COVID-19.
J. Pharm. Technol. Res. Manag.. 2022, 10, 47-73
