Background: The scientific community has supported from the medicinal flora of ancient as well as modern
times in extracting chemicals, which holds therapeutic potential. In many previous studies, it was discovered Amentoflavone
as an anti-viral agent and its presence as a bioactive constituent in many plants of different families Selaginellaceae, Euphorbiaceae,
and Calophyllaceae etc. Withania somnifera (Ashwagandha) is already considered significant anti-viral agent
in traditional medicine, and it is the main source of Somniferine-A, Withanolide-B.
Objective: In this study phytochemicals such as Withanolide-B, Somniferine-A, Stigmasterol, Amentoflavone, and Chavicine
were analyzed to screen protein inhibitors out of them; such proteins are involved in SARS-Cov-2's internalization and
interaction with human cytological domains. This will help in developing check point for SARS-Cov-2 internalization.
Material and methods: Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME,
MDWeb, Molsoft, ProTox-II, and LigPlot were deployed to examine the action of pharmacoactive agents against
SARS-Cov-2. The many tools deployed in the study were based on finest algorithms like Artificial neural networking, Machine
Learning, and Artificial intelligence.
Results: On the basis of binding energies less than equal to -8.5 kcal/mol. Amentoflavone, Stigmasterol, and Somniferine-A
were found to be most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and
competitively inhibit major proteins (SARS-Cov-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-Cov-2 RNA
binding protein) that are found to involved in its infection and pathogenesis. Simulation analysis provides more validity to the
selection of drug candidate Amentoflavone. ADMET properties were found to be in feasible range for putative drug candidates.
Conclusion: Computational analysis was successfully deployed in searching pharmacoactive phytochemicals Like Amentoflavone,
Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was
found to be efficient, as reduces monetary expenditures and time consumption, aftermath molecular wet-lab validations will
provide better approval for finalizing our selected drug model for controlling COVID-19 pandemic.