综合利用配体和基于结构的虚拟筛选、分子动力学、自由能计算和 ADME 预测来确定潜在的 PTP1B 抑制剂。

IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED
Molecular Diversity Pub Date : 2024-04-01 Epub Date: 2023-02-06 DOI:10.1007/s11030-023-10608-8
Bharti Devi, Sumukh Satyanarayana Vasishta, Bhanuranjan Das, Anurag T K Baidya, Rahul Salmon Rampa, Manoj Kumar Mahapatra, Rajnish Kumar
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引用次数: 0

摘要

蛋白酪氨酸磷酸酶(PTPs)是一类控制细胞活性和酪氨酸(Tyr)磷酸化蛋白去磷酸化的酶。PTP1B 的失调导致了许多疾病,包括糖尿病、阿尔茨海默病和肥胖症,使 PTP1B 成为治疗应用的合法靶点。由于 PTP1B 的活性位点口袋高度保守且带正电荷,因此针对这种酶的研究极具挑战性,这也促使研究人员寻找针对它的新型先导化合物。本研究采用基于配体和基于结构的虚拟筛选相结合的综合方法来寻找针对 PTP1B 的热门化合物。首先,我们进行了药效学建模,以从强效 PTP1B 抑制剂中找到共同特征,如两个氢键受体、一个芳香环和一个氢键供体。对符合共同药效学特征的化合物数据集进行筛选,以去除泛测定干扰子结构,并符合利宾斯基标准。然后,利用分子对接技术进一步确定化合物的优先次序,并挑选出具有良好结合亲和力的前五十个化合物进行吸收、分布、代谢和排泄(ADME)预测。溶解度、吸收和渗透性保持分数在 - 10 至 - 9.3 kcal/mol 之间的前五种化合物以及 Ertiprotafib 被提交进行全原子分子动力学(MD)研究。MD 研究和结合自由能计算结果表明,化合物 M4、M5 和 M8 与 PTP1B 酶的结合亲和力更好,ΔGtotal 分数分别为 - 24.25、- 31.47 和 - 33.81 kcal/mol,高于其他化合物,表明化合物 M8 可能是 PTP1B 抑制剂的合适先导化合物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated use of ligand and structure-based virtual screening, molecular dynamics, free energy calculation and ADME prediction for the identification of potential PTP1B inhibitors.

Protein tyrosine phosphatases (PTPs) are the group of enzymes that control both cellular activity and the dephosphorylation of tyrosine (Tyr)-phosphorylated proteins. Dysregulation of PTP1B has contributed to numerous diseases including Diabetes Mellitus, Alzheimer's disease, and obesity rendering PTP1B as a legitimate target for therapeutic applications. It is highly challenging to target this enzyme because of its highly conserved and positively charged active-site pocket motivating researchers to find novel lead compounds against it. The present work makes use of an integrated approach combining ligand-based and structure-based virtual screening to find hit compounds targeting PTP1B. Initially, pharmacophore modeling was performed to find common features like two hydrogen bond acceptors, an aromatic ring and one hydrogen bond donor from the potent PTP1B inhibitors. The dataset of compounds matching with the common pharmacophoric features was filtered to remove Pan-Assay Interference substructure and to match the Lipinski criteria. Then, compounds were further prioritized using molecular docking and top fifty compounds with good binding affinity were selected for absorption, distribution, metabolism, and excretion (ADME) predictions. The top five compounds with high solubility, absorption and permeability holding score of - 10 to - 9.3 kcal/mol along with Ertiprotafib were submitted to all-atom molecular dynamic (MD) studies. The MD studies and binding free energy calculations showed that compound M4, M5 and M8 were having better binding affinity for PTP1B enzyme with ∆Gtotal score of - 24.25, - 31.47 and - 33.81 kcal/mol respectively than other compounds indicating that compound M8 could be a suitable lead compound as PTP1B inhibitor.

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来源期刊
Molecular Diversity
Molecular Diversity 化学-化学综合
CiteScore
7.30
自引率
7.90%
发文量
219
审稿时长
2.7 months
期刊介绍: Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including: combinatorial chemistry and parallel synthesis; small molecule libraries; microwave synthesis; flow synthesis; fluorous synthesis; diversity oriented synthesis (DOS); nanoreactors; click chemistry; multiplex technologies; fragment- and ligand-based design; structure/function/SAR; computational chemistry and molecular design; chemoinformatics; screening techniques and screening interfaces; analytical and purification methods; robotics, automation and miniaturization; targeted libraries; display libraries; peptides and peptoids; proteins; oligonucleotides; carbohydrates; natural diversity; new methods of library formulation and deconvolution; directed evolution, origin of life and recombination; search techniques, landscapes, random chemistry and more;
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