Estimation of drug-likeness properties of GC–MS separated bioactive compounds in rare medicinal Pleione maculata using molecular docking technique and SwissADME in silico tools

29Citations
Citations of this article
96Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The main aim of the paper was to determine bioactive compounds in Pleione maculata extracts using gas chromatographic technique and to investigate their drug-likeness potential using molecular docking algorithm and ADME studies on the recent intractable disease, for example, SARS-CoV-2. Pleione maculata sample was prepared for GC–MS analysis. The peak components were identified based on the NIST Library. Molecular docking was performed using PatchDock, and energy refinement was carried out using the FireDock algorithm followed by drug-likeness analysis using the SwissADME tool. The mass spectrum revealed various pharmacologically important compounds and novel compounds 8-oxatetracyclo{5.2.1.1(2,6). 1(4,10)}dodecane, 7-tert-butyl-1,9,9-trimeth, docosane, 2,4-dimethyl, kryptogenin 2,4-dinitrophenyl hydrazine, and N-decyl-alpha,D-2-deoxyglycoside which are reported for the first time. Molecular docking using PatchDock illustrates GC–MS compounds Nor-diazepam,3-{N-hydroxymethyl}aminocarbonyloxy a good docking and high binding affinity with atomic contact energy -10.95 kcal/mol against SARS-CoV-2 spike protein S2 subunit. ADME analysis predicts Nor-diazepam,3-{N-hydroxymethyl}aminocarbonyloxy and andrographolide showed very high drug-likeness parameters with no metabolism disturbances. The random control antiviral drug arabidiol revealed a lower binding affinity and lower solubility compared to bioactive compounds of P. maculata. The study depicts the first and novel report on various pharmaceutical important GC–MS bioactive compounds and molecular docking study on Pleione maculata having potential against various intractable diseases.

Cite

CITATION STYLE

APA

Sympli, H. D. (2021). Estimation of drug-likeness properties of GC–MS separated bioactive compounds in rare medicinal Pleione maculata using molecular docking technique and SwissADME in silico tools. Network Modeling Analysis in Health Informatics and Bioinformatics, 10(1). https://doi.org/10.1007/s13721-020-00276-1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free