Kumar Navneet, Gahlawat Anuj, Kumar Rajaram Naresh, Singh Yash Pal, Modi Gyan, Garg Prabha
Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), S.A.S. Nagar, Mohali, Punjab, India.
Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (Banaras Hindu University), Varanasi, Uttar Pradesh, India.
J Biomol Struct Dyn. 2022 Apr;40(7):2878-2892. doi: 10.1080/07391102.2020.1844054. Epub 2020 Nov 10.
Alzheimer's disease (AD) is one of the most familiar multifactorial and complex neurodegenerative disorders characterized by loss of cholinergic neurons in the brain. The various attempts for drug development to treat AD have been hampered by largely unsuccessful clinical trials in the last two decades. Developing a new drug from scratch takes enormous amounts of time, effort and money, mainly due to several barriers in the therapeutic drug development process. Drug repurposing strategy resuscitates this slow drug discovery process by finding new uses and clinical indications for existing drugs. This study is focused on the cholinergic hypothesis, a well-established target of the clinically available drugs in the market for the treatment of AD. The computational virtual screening (VS) led to the identification of thiazolidinedione (TZD, antidiabetic) and aminoquinoline (antimalarial) class of drugs as acetylcholinesterase (AChE) inhibitors. Intriguingly, rosiglitazone (RGZ) and hydroxychloroquine (HCQ) were found to be mild-to-moderate inhibitors of AChE (human acetylcholinesterase) in our enzyme inhibition studies which are complementary to our computational studies. On the basis of our computational and experimental studies, it can be suggested that the beneficial effect of RGZ and HCQ in AD patients reported in the literature may partly be due to their AChE inhibitory property. The VS also led to the identification of antifungal drugs miconazole and oxiconazole as potential AChE inhibitors. The molecular dynamics (MD) simulation of the potential hits belonging to TZD, aminoquinoline and azoles class were also carried out. The MD simulations studies revealed detailed computational insights related to molecular interactions and protein-ligand stability for selected hits.
阿尔茨海默病(AD)是最常见的多因素复杂神经退行性疾病之一,其特征是大脑中胆碱能神经元丧失。在过去二十年中,治疗AD的药物开发的各种尝试因临床试验大多未成功而受阻。从头开发一种新药需要大量的时间、精力和金钱,主要是由于治疗药物开发过程中的几个障碍。药物重新利用策略通过为现有药物寻找新用途和临床适应症,使这个缓慢的药物发现过程得以复苏。本研究聚焦于胆碱能假说,这是市场上治疗AD的临床可用药物的一个成熟靶点。计算虚拟筛选(VS)导致鉴定出噻唑烷二酮(TZD,抗糖尿病药物)和氨基喹啉(抗疟疾药物)类药物为乙酰胆碱酯酶(AChE)抑制剂。有趣的是,在我们的酶抑制研究中发现罗格列酮(RGZ)和羟氯喹(HCQ)是AChE(人乙酰胆碱酯酶)的轻度至中度抑制剂,这与我们的计算研究相辅相成。基于我们的计算和实验研究,可以认为文献中报道的RGZ和HCQ对AD患者的有益作用可能部分归因于它们的AChE抑制特性。虚拟筛选还导致鉴定出抗真菌药物咪康唑和奥昔康唑为潜在的AChE抑制剂。还对属于TZD、氨基喹啉和唑类的潜在命中物进行了分子动力学(MD)模拟。MD模拟研究揭示了与选定命中物的分子相互作用和蛋白质-配体稳定性相关的详细计算见解。