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通过药效团驱动鉴定N-甲基-D-受体拮抗剂作为有效的神经保护剂,并通过研究进行验证。

Pharmacophore-driven identification of N-methyl-D-receptor antagonists as potent neuroprotective agents validated using studies.

作者信息

Sharma Mukta, Mittal Anupama, Singh Aarti, Jainarayanan Ashwin K, Sharma Swapnil, Paliwal Sarvesh

机构信息

Department of Pharmacy, Banasthali Vidyapith, Banasthali, Rajasthan, India.

Indian Institute of Science Education and Research, Mohali, Punjab, India.

出版信息

Biol Methods Protoc. 2020 Jul 14;5(1):bpaa013. doi: 10.1093/biomethods/bpaa013. eCollection 2020.

Abstract

Alzheimer's disease (AD), apparently the most widespread reason behind dementia, is delineated by a continuous cognitive weakening in the aged. During its progression, N-methyl-D-aspartate receptor (NMDAR) antagonists are known to play a pivotal part in the mechanisms of learning and memory. Since there is an unmet medical need for the treatment of AD, we aim to identify possible chemical compounds targeted toward N-methyl-D-aspartate receptors. Three-dimensional models are developed to unveil some of the essential characteristics of the N-methyl-D-aspartate receptors by using a collection of already discovered N-methyl-D-aspartate receptor inhibitors. This is followed by virtual screening, which results in novel chemical compounds having the potential to inhibit N-methyl-D-aspartate receptors. Molecular docking studies and analysis promulgated two lead compounds with a high LibDock score. The compounds are shortlisted based on high estimated activity, fit values, LibDock score, no violation of Lipinski's, and availability for procuring. Finally, the shortlisted compounds are tested by employing studies, which we further propose as potential NMDA inhibitors for treating AD.

摘要

阿尔茨海默病(AD)显然是痴呆症最普遍的病因,其特征是老年人持续的认知衰退。在其发展过程中,N-甲基-D-天冬氨酸受体(NMDAR)拮抗剂在学习和记忆机制中起着关键作用。由于AD的治疗存在未满足的医疗需求,我们旨在鉴定针对N-甲基-D-天冬氨酸受体的潜在化合物。通过使用一系列已发现的N-甲基-D-天冬氨酸受体抑制剂,开发三维模型以揭示N-甲基-D-天冬氨酸受体的一些基本特征。随后进行虚拟筛选,得到具有抑制N-甲基-D-天冬氨酸受体潜力的新型化合物。分子对接研究和分析公布了两种具有高LibDock评分的先导化合物。这些化合物基于高估计活性、拟合值、LibDock评分、不违反Lipinski规则以及可获得性而入围。最后,通过实验对入围化合物进行测试,我们进一步提出这些化合物作为治疗AD的潜在NMDA抑制剂。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a271/7474860/4d89082f420d/bpaa013f1.jpg

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