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用于预测新型恶二唑衍生物作为多功能抗阿尔茨海默病药物活性的稳健且具有预测性的3D-QSAR模型。

Robust and predictive 3D-QSAR models for predicting the activities of novel oxadiazole derivatives as multifunctional anti-Alzheimer agents.

作者信息

Sun Yekai, Zhang Zirou, Wen Menghao, Wang Fangfang, Li Xiuling, Yang Wei, Zhou Bo

机构信息

School of Life Science, Linyi University Linyi 276000 China

National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital 518112 Shenzhen China.

出版信息

RSC Adv. 2024 Sep 23;14(41):30230-30244. doi: 10.1039/d4ra05342g. eCollection 2024 Sep 18.

DOI:10.1039/d4ra05342g
PMID:39315029
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11418590/
Abstract

In recent years, Alzheimer disease (AD) as a neurodegenerative disorder has been increasing annually with the aging of the global population, therefore, development of novel anti-AD drugs is imperative. Studies have proven that glycogen synthase kinase-3β (GSK-3β) is a pivotal factor in the development of AD. Therefore, GSK-3β inhibitors would provide powerful means to treat the disorders, such as AD. To in-depth study the structure-activity relationship of a series of oxadiazole derivatives as multifunctional anti-Alzheimer agents, computational three dimensional quantitative structure-activity relationship (3D-QSAR) studies, molecular docking and molecular dynamics were conducted. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were conducted to build up the 3D-QSAR models, and exhibited significant results ( = 0.692, = 0.6885/CoMFA, = 0.696, = 0.6887/CoMSIA). The accuracy of the 3D-QSAR models was validated by external validation and applicability domain analysis. The derived contour maps provided structural information for designing novel compounds to improve the inhibitory activities. Additionally, molecular docking and molecular dynamics were also employed to investigate the bonding interactions and stability of this series of inhibitors in the active site of GSK-3β, and the results revealed that the importance of residues Ile62, Asn64 Val70, Tyr128, Val129 and Leu182 for ligand binding to the receptor GSK-3β. All the results would be of great help for the discovery of new GSK-3β agents that can solve the problem of AD.

摘要

近年来,随着全球人口老龄化,作为一种神经退行性疾病的阿尔茨海默病(AD)的发病率逐年上升,因此,开发新型抗AD药物势在必行。研究证明,糖原合酶激酶-3β(GSK-3β)是AD发病过程中的关键因素。因此,GSK-3β抑制剂将为治疗AD等疾病提供有力手段。为了深入研究一系列恶二唑衍生物作为多功能抗阿尔茨海默病药物的构效关系,进行了计算三维定量构效关系(3D-QSAR)研究、分子对接和分子动力学研究。采用比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)方法建立3D-QSAR模型,并取得了显著结果(CoMFA:r2 = 0.692,q2 = 0.6885;CoMSIA:r2 = 0.696,q2 = 0.6887)。通过外部验证和适用域分析验证了3D-QSAR模型的准确性。导出的等高线图为设计新型化合物以提高抑制活性提供了结构信息。此外,还采用分子对接和分子动力学研究了该系列抑制剂在GSK-3β活性位点的结合相互作用和稳定性,结果揭示了Ile62、Asn64、Val70、Tyr128、Val129和Leu182残基对于配体与受体GSK-3β结合的重要性。所有这些结果将对发现能够解决AD问题的新型GSK-3β药物有很大帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b249/11418590/261bcd17b69e/d4ra05342g-f8.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b249/11418590/261bcd17b69e/d4ra05342g-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b249/11418590/401d47ef7972/d4ra05342g-f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b249/11418590/261bcd17b69e/d4ra05342g-f8.jpg

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