Decoding the Knacks of Ellagitannin Lead Compounds to Treat Nonalcoholic Fatty Liver Disease using Computer-aided Drug Designing.

Hina Shahid, Muhammad Ibrahim, Wadi B Alonazi, Zhanyou Chi
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Abstract

Background: The prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing globally, impacting individuals in Western nations and rapid growing in Asian countries due to sedentary lifestyles; thus, NAFLD has emerged as a significant worldwide health concern. Presently, lifestyle changes represent the primary approach to managing NAFLD.

Methods: This research aimed to identify the potential drug targets for treating NAFLD through comprehensive in silico computational analysis. These include the prediction of the three-dimensional structure of the protein, the prediction of inhibitors by PubChem and ZINC, molecular docking by Autodcok, pharmacophore modeling, molecular dynamics simulation by the OPLS_2005 force field, and the orthorhombic box solvent model Intermolecular Interaction Potential 3 Points Transferable to the selected compound. The toxicity of the lead compounds was analyzed through AdmetSAR software.

Results: The protein associated with the PNPLA3 gene, whose overall three-dimensional structure was 95% accurate, were retrieved following inhibitor selection via PubChem and ZINC. Among the selected inhibitors and docked compounds with ID 10033935 (ellagitannin) showed a minimum E-Score of -17.266. In docking and pharmacophore modeling the compound ellagitannin shows promise as a potential drug candidate. Moreover, the molecular dynamics and structural stability of the protein-ligand complex were evaluated with several metrics such as as root mean square fluctuation and root mean square deviation and resulted in the stability not only of PNPLA3-10033935 (ellagitannin) but also of compound PNPLA3-71448940 and PNPLA3-5748394 complexed proteins at 400 ns with very slight variation.

Conclusion: Overall, ellagitannin was identified as the best druggable target with the best therapeutics profile. The findings of our study can pave the way for the development of a new drug against NALFD.

利用计算机辅助药物设计解码鞣花丹宁先导化合物治疗非酒精性脂肪肝的诀窍。
背景:非酒精性脂肪肝(NAFLD)的发病率在全球范围内不断上升,对西方国家的人造成了影响,而在亚洲国家,由于久坐不动的生活方式,非酒精性脂肪肝的发病率也在迅速上升;因此,非酒精性脂肪肝已成为一个重大的全球健康问题。目前,改变生活方式是控制非酒精性脂肪肝的主要方法:本研究旨在通过全面的硅计算分析,确定治疗非酒精性脂肪肝的潜在药物靶点。这些分析包括预测蛋白质的三维结构、利用 PubChem 和 ZINC 预测抑制剂、利用 Autodcok 进行分子对接、药理学建模、利用 OPLS_2005 力场进行分子动力学模拟,以及将正交箱溶剂模型 Intermolecular Interaction Potential 3 Points 转移到所选化合物。通过 AdmetSAR 软件分析了先导化合物的毒性:通过 PubChem 和 ZINC 筛选出与 PNPLA3 基因相关的蛋白质,其整体三维结构的准确率为 95%。在筛选出的抑制剂和对接化合物中,ID 10033935(鞣花丹宁)的最小 E-Score 为 -17.266。在对接和药效学建模中,鞣花丹宁有望成为一种潜在的候选药物。此外,通过均方根波动和均方根偏差等指标对蛋白质配体复合物的分子动力学和结构稳定性进行了评估,结果表明,不仅 PNPLA3-10033935(鞣花丹宁)具有稳定性,而且化合物 PNPLA3-71448940 和 PNPLA3-5748394 复合物蛋白质在 400 ns 时也具有稳定性,且变化非常小:总之,鞣花丹宁被确定为具有最佳治疗特征的最佳药物靶点。结论:总体而言,鞣花丹宁被鉴定为具有最佳治疗特征的最佳药物靶点。我们的研究结果可为开发抗NALFD的新药铺平道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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