In Silico ADMET and Docking Study of Selected Drug Used in Therapy of COVID-19

Simple item page
dc.contributor.authorSagar Ashok Jadhav
dc.contributor.authorPayal Pandurang Chavan
dc.contributor.authorSupriya Suresh Shete
dc.contributor.authorDipti Shantisagar Patil
dc.contributor.authorSaroj Dyandev Kolekar
dc.contributor.authorGodfrey Rudolph Mathews
dc.contributor.authorDipak Babaso Bhingardeve
dc.contributor.authorPravin Kondiba Pawar
dc.date.accessioned2025-12-19T06:31:50Z
dc.date.available2025-12-19T06:31:50Z
dc.date.issued2022-05-07
dc.description.abstractDocking 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.
dc.identifier.issn2321-2217
dc.identifier.issn2321-2225
dc.identifier.otherhttps://doi.org/10.15415/jptrm.2022.101006
dc.identifier.urihttps://demodspace.chitkara.edu.in/handle/123456789/263
dc.language.isoen
dc.publisherChitkara University Publications
dc.subjectDocking
dc.subjectAUTO-DOCK VINA
dc.subjectPYMOL
dc.titleIn Silico ADMET and Docking Study of Selected Drug Used in Therapy of COVID-19
dc.typeArticle

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
JPTRM Volume 10 Issue 1 006.pdf
Size:
6.2 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description:
Download

Collections

JPTRM Vol. 10 No. 1 (May 2022)