Aggarwal Sanchita, Raghav Neera, Dahiya Heena, Mor Nitika
Department of Chemistry, Baba Mastnath University, Asthal Bohar, Rohtak 124021, India.
Department of Chemistry, Panjab University, Chandigarh 160014, India.
Comput Biol Chem. 2025 Oct;118:108488. doi: 10.1016/j.compbiolchem.2025.108488. Epub 2025 Apr 26.
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.
计算研究在药物开发中至关重要，特别是在筛选潜在的先导化合物方面。在本研究中，精心制备并分析了一个由37种源自印度人参的化合物组成的库。评估过程包括应用Lipinski规则，随后进行ADMET预测，以评估直接影响药物药理学性质的因素。以阿司匹林作为标准参考药物，对这些化合物的药代动力学和药效学进行了全面比较。在37种化合物中，Withasomniferol C被发现是最有效的药物候选物，并通过针对组织蛋白酶B、牛血清白蛋白和胰蛋白酶（特别是参与炎症的酶）的分子对接研究进行了进一步评估。与阿司匹林相比，Withasomniferol C被发现是这些酶的有效抑制剂。本研究还报告了基于分子轨道性质评估热稳定性和化学反应性的密度泛函理论（DFT）计算。分子动力学模拟表明，如均方根波动（RMSF）分析所示，Withasomniferol C在结合位点附近诱导局部灵活性，而如均方根偏差（RMSD）和回转半径（RoG）研究所示，对整体蛋白质结构的影响最小。
