A virtual screening of Withaniasomnifera compounds using ADMET predictions, molecular docking, MD simulation and DFT calculations: Withasomniferol C an effective drug and potent inhibitor of anti-inflammatory targets.

Computational studies are pivotal in drug development, particularly for screening potential lead compounds. In this study, a library of 37 compounds derived from Withaniasomnifera was meticulously prepared and analyzed. The evaluation process involved applying Lipinski's Rule, followed by ADMET predictions to assess factors that directly influence the pharmacological properties of a drug. The pharmacokinetics and pharmacodynamics of these compounds were thoroughly compared, with aspirin serving as the standard reference drug.Among 37 compounds, Withasomniferol C was found to be the most effective candidate as a drug which was further evaluated by molecular docking studies against cathepsin B, BSA, and trypsin enzymes especially involved in the inflammation. Withasomniferol C was found to be a potent inhibitor of these enzymes as compared to aspirin. This study also reports the density functional theory (DFT) calculations to evaluate the thermal stability and chemical reactivity based on molecular orbital properties. The MD simulations reveal that Withasomniferol C induces localized flexibility near the binding site, as indicated by RMSF analysis, while having minimal impact on the overall protein structure, as shown by RMSD and RoG studies.