Department of Pharmacology and Toxicology, College of Pharmacy, University of Hail, Hail, Saudi Arabia.
Eur Rev Med Pharmacol Sci. 2023 Apr;27(7):3150-3158. doi: 10.26355/eurrev_202304_31949.
The study aimed to evaluate the Withaferin-A against the drug target α-amylase, revealing its plausible mode of action and molecular-level interactions essential for this specific target inhibitory potential computational approach.
In this scenario, we used computational methods, including docking, molecular dynamics simulation, and model-building simulations, to elucidate the atomic-level details responsible for the inhibitory potential of Withaferin-A derived from W. somnifera. The studio visualizer software was used for the visualization of ligands, structures of the receptor, bond length, and rendering of the image. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics of phytochemicals were investigated. Crystal structure of protein receptors and ligands were generated. Semi-flexible docking was done using Autodock software. Docking was performed using the Lamarckian Genetic Algorithm (LGA). Molecular descriptors were evaluated, and the pharmacological properties of the phytochemicals were explored. Molecular dynamic simulations were analyzed at the atomic level. All the simulations were conducted under the same temperature, pressure, and volume circumstances over the simulated time scale.
Withaferin-A has shown a strong binding affinity towards α-amylase as demonstrated with -9.79 Kcal/mol with 66.61 estimated nanomolecular IC50 value for plausible anti-obesity activity. Molecular-level relationships and knowledge obtained from this study indicate solid interactions with TYR59, ASP197, and HIS299 residues which are of high importance for future works related to computational screening of target-specific α-amylase inhibitors. The results from the analysis have revealed potential molecular-level interactions useful for further designing/discovering novel α-amylase inhibitors.
The framework of the studied phytochemicals enables the rapid development of subsequent modifications that could result in more lead-like compounds with better inhibitory efficacy and selectivity for α-amylase.
本研究旨在评估 Withaferin-A 对药物靶标 α-淀粉酶的作用，揭示其作用模式和分子水平相互作用，这些对于理解其作为特定靶标抑制剂的潜力至关重要。
在这种情况下，我们使用计算方法，包括对接、分子动力学模拟和模型构建模拟，阐明了来自 W. somnifera 的 Withaferin-A 抑制潜力的原子水平细节。使用 Studio Visualizer 软件可视化配体、受体结构、键长和图像渲染。研究了植物化学物质的吸收、分布、代谢、排泄和毒性（ADMET）特征。生成了蛋白质受体和配体的晶体结构。使用 Autodock 软件进行半柔性对接。对接使用 Lamarckian 遗传算法（LGA）进行。评估了分子描述符，并探索了植物化学物质的药理学性质。在原子水平上分析了分子动力学模拟。所有模拟都是在相同的温度、压力和体积条件下，在模拟时间尺度上进行的。
Withaferin-A 对 α-淀粉酶表现出很强的结合亲和力，其结合自由能为-9.79 Kcal/mol，估计的纳米分子 IC50 值为 66.61，具有合理的抗肥胖活性。从这项研究中获得的分子水平关系和知识表明，它与 TYR59、ASP197 和 HIS299 残基之间存在牢固的相互作用，这些残基对未来与计算筛选特定靶标 α-淀粉酶抑制剂相关的工作非常重要。分析结果揭示了潜在的分子水平相互作用，这些相互作用对于进一步设计/发现新型 α-淀粉酶抑制剂非常有用。
所研究的植物化学物质的框架使后续的修饰能够快速发展，这可能会导致具有更好的抑制效果和对 α-淀粉酶的选择性的更具先导化合物特性的化合物的产生。
