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计算机辅助药物设计在治疗阿尔兹海默症中的应用
蒋迎迎
学位类型硕士
导师高洪伟
2018-05-21
学位授予单位中国科学院大学
学位授予地点北京
学位专业药物化学
关键词阿尔兹海默症 乙酰胆碱酯酶 丁酰胆碱酯酶 分子对接 药效团模型
摘要

计算机辅助药物设计(CADD)一直是新药研发的重要方法,因为它节省了大量资金,并且实现了一些在实验中无法完成的事情。在这项研究中,我们的目的是应用CADD技术探索出高活性、高选择性的阿尔茨海默症抑制剂。阿尔兹海默症(Alzheimer's Disease, AD)是一种常发于老年人群的中枢神经系统退行性慢性疾病,其临床主要表现为智力衰退、进行性记忆减退、语言能力下降、认知障碍甚至意识丧失,严重危胁着患者的身体健康。目前,AD还不能被完全治愈,其发病机制相当复杂,病因还不十分清楚,临床上也缺乏能够有效延缓疾病进程和减少神经元死亡的药物。现在胆碱能假说在AD的发病机制过程中受到了广泛的关注,该学说认为引起AD疾病的关键因素是乙酰胆碱的缺失。在人体中可以水解乙酰胆碱的酶主要有2种,即乙酰胆碱酯酶(AChE),亦称为真性胆碱酯酶,和丁酰胆碱酯酶(BChE),亦称为假性胆碱酯酶。研究表明,在胆碱能突触间,胆碱酯酶 (ChE) 是生物神经传导中的关键性的酶,该酶可以终止神经递质对突触后膜的兴奋作用,从而保证神经信号在生物体内的正常传递。目前,单靶点药物很难取得理想的治疗效果,设计具有多靶点作用的药物可能是对抗AD的有效策略,所以同时抑制AChE和BChE是更加理想的AD治疗方案。结合多靶点药物设计理念,旨在通过CADD技术寻找治疗AD的双胆碱酯酶抑制剂,为此我们做了三部分的内容。第一部分,以新疆的天然产物棉花花提取物黄酮类化合物为起点,寻找实验中一系列对乙酰胆碱酯酶(AChE)单靶点起抑制作用的黄酮类化合物。首先创建训练集和测试集,利用Discovery Studio软件构建和评价具有活性预测能力的药效团(Hypogen)模型,最好的药效团模型包含2个氢键受体、3个疏水中心。然后应用最好的药效团模型从中草药数据库(TCMD)中筛选出与药效团模型相匹配的化合物,选择预测活性 < 2μM的化合物与AChE蛋白分子做对接,得出10个打分最好的候选药物分子,然后利用De Novo Evolution calculation的方法对筛选出的化合物进行分子优化改造,最终得到10个抗AD的候选药物分子。第二部分,基于药效团药物设计的方法从数据库中选并设计对丁酰胆碱酯酶(BChE)有抑制作用的候选药物分子。用通过测试集,cost值和Fischer图表法验证的最佳药效团模型筛选数据库。然后使用Lipinski’s rule of five原则和ADMET性质(25摄氏度下水溶解度、血脑屏障通透性、血细胞素P450 2D6抑制性、肝毒性、人类肠道吸收性、血浆蛋白结合率)对化合物进行预测,将筛选出的化合物与BChE蛋白对接,选出打分高的分子进行分子优化改造,从而得到候选药物分子。第三部分,计算机辅助药物设计方法筛选对双胆碱酯酶(乙酰胆碱酯酶和丁酰胆碱酯酶)有抑制作用的候选药物分子。我们使用已经验证过的AChE和BChE药效团模型来虚拟筛选数据库,本研究采用分层虚拟筛选方案,筛选ZINC数据库中有潜力的分子。经过Lipinski’s rule of five原则和ADMET性质的过滤之后,将所得的7个化合物分别与AChE和BChE蛋白进行对接,经过分析得出1个最具有潜力的化合物,总而言之,考虑到AD复杂的病因,多靶向策略将成为开发高效低毒甚至逆转病程的抗AD药物的有效途径。

其他摘要

Computer aided drug design (CADD) has been an important method in the new drugs discovery, because it saved a great deal of money and it accomplished something that could not be done in experiment. In this study, we aimed to explore highly active and selective Alzheimer's disease inhibitors using CADD techniques and methods.Alzheimer's disease (AD), is a severe neurodegenerative disease of the central nervous system in the elderly, and its clinical manifestations are progressive remembrance loss, mental decline, language skill declining, cognitive impairment or even loss of consciousness. It is a seriously threat to the physical health of AD patients. At present, AD cannot be completely cured, because the specifical cause of disease is not clear and the pathogenesis is very complex. There is a lack of drugs that can decrease the death of neurons and delay the progression of disease in clinical use.Now, the cholinergic hypothesis has received extensive attention among the pathogenesis of AD. The theory holds that the loss of neurotransmitter acetylcholine in the brain of Alzheimer's patients is the key cause of AD disease. In human body, there are 2 enzymes that can hydrolyze acetylcholine, namely acetylcholinesterase (AChE), also known as true cholinesterase, and butylyl cholinesterase (BChE), also known as pseudo cholinesterase. Studies have shown that in the process of biological nerve conduction, cholinesterase (ChE), a key enzyme, can terminate the excitatory effect of neurotransmitters on the postsynaptic membrane to ensure the normal transmission of neural signals in the organism. At present, single-target is difficult to obtain the ideal treatment effect as the pathogenesis of AD. The design and development of drugs with multiple targets may be an effective strategy against AD, so inhibition of AChE and BChE at the same time is a more ideal for AD treatment.Combined with the concept of multi target drug design, our team aims to find a double cholinesterase inhibitor for the treatment of AD by CADD technology. For this purpose, we have made three parts.In the first part, based on Flavonoids from Xinjiang natural product cotton flower extract, we searched for a series of flavonoid compounds that can inhibit the single target of acetylcholinesterase (AChE) in the experiment, and then set up training set and test set using these compounds. The pharmacophore (Hypogen) with activity prediction ability was constructed and validated by Discovery Studio software, the best pharmacophore model obtained with 2 hydrogen bond receptors and 3 hydrophobic centers. The compounds that match the best pharmacophore model were screened out from the Traditional Chinese Medicine Database (TCMD). Then we docked the compounds with the predicted activity < 2 μM into the protein active site in this study, and 10 best candidate drug molecules were obtained. De Novo Evolution designed the top 10 derivatives, and three potential AChE inhibitor candidates were obtained eventually.In the second part, we screened and designed candidate drug molecules that inhibit butyrylcholinesterase (BChE) based on pharmacophore drug design method. The best pharmacophore validated by test set, cost value and Fischer chart method was used to screen databases. Then we selected compounds by Lipinski's rule of five principle and ADMET properties (aqueous solubility, Blood-brain barrier penetration, cytochrome P450 2D6 inhibition, hepatotoxicity, human intestinal absorption, and plasma protein binding rate). The screened compounds were docked with the BChE protein, and then selected high scored molecular to Molecular optimization and transformation, resulting in candidate drug molecules.In the third part, computer-aided drug design methods are selected to screen candidate drug molecules that inhibit the two cholinesterase (AChE and BChE). We used the validated AChE and BChE pharmacophore models to virtual screen the database. In this study, a layered virtual screening scheme was used to screen potential molecules from ZINC database. After Lipinski's rule of five principle and the ADMET filtration, the screened seven compounds were docked to AChE and BChE proteins, respectively. After analysis, one of the most promising compounds was obtained. In summary, considering the complex etiology of AD, multi target strategy may be an effective way to develop anti-AD drugs with high efficacy, low toxicity and even reversal of the disease course

页数100
文献类型学位论文
条目标识符http://ir.xjipc.cas.cn/handle/365002/5438
专题资源化学研究室
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蒋迎迎. 计算机辅助药物设计在治疗阿尔兹海默症中的应用[D]. 北京. 中国科学院大学,2018.
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