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

AbstractThe main aim of the paper was to determine bioactive compounds inPleione 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 pharmacol ogically 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, andN-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 ofP. maculata. The study depicts the first and novel ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - Category: Bioinformatics Source Type: research