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

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The main aim of the paper was to determine bioactive compounds in 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. 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 -decyl-alpha,-2-deoxyglycoside which are reported for the first time. Molecular docking using PatchDock illustrates GC-MS compounds Nor-diazepam,3-{-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 . The study depicts the first and novel report on various pharmaceutical important GC-MS bioactive compounds and molecular docking study on having potential against various intractable diseases.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13721-020-00276-1.