药学学报, 2019, 54(7): 1214-1224
引用本文:
张宝月, 庞晓丛, 贾皓, 王喆, 刘艾林, 杜冠华. 基于全球上市药物数据的抗阿尔茨海默病重定位新药发现[J]. 药学学报, 2019, 54(7): 1214-1224.
ZHANG Bao-yue, PANG Xiao-cong, JIA Hao, WANG Zhe, LIU Ai-lin, DU Guan-hua. Repositioning drug discovery for Alzheimer's disease based on global marketed drug data[J]. Acta Pharmaceutica Sinica, 2019, 54(7): 1214-1224.

基于全球上市药物数据的抗阿尔茨海默病重定位新药发现
张宝月1, 庞晓丛1,2, 贾皓1, 王喆1, 刘艾林1, 杜冠华1
1. 中国医学科学院、北京协和医学院药物研究所, 北京 100050;
2. 北京大学第一医院药剂科, 北京 100034
摘要:
阿尔茨海默病(Alzheimer's disease,AD)是一种严重威胁老年人健康的神经系统退行性疾病,目前尚未发现能够根治或者延缓疾病进程的药物。寻找可以同时作用于多个AD相关靶点的多靶点定向配体(MTDL)是当前抗AD新药发现的重要策略。为了从上市药物中寻找潜在的多靶点抗AD药物,本文利用实验室前期基于机器学习算法建立的抗AD多靶点药物预测平台,对全球上市药物数据库进行了预测和挖掘,从中挑选出13个至少作用于1个抗AD药物靶点,且可以通过多种作用对抗AD的上市药物,利用Cytoscape构建化合物——靶点网络;并针对上市药物阿戈美拉汀及其预测的多靶点蛋白进行分子对接以验证预测结果,蛋白靶点包括ADORA2A、ACHE、BACE1、PTGS2、MAOB、SIGMAR1、ESR1,阿戈美拉汀均能与以上靶点产生相互作用。本文应用机器学习算法、网络药理学方法及分子对接方法,初步揭示了上市药物数据库中抗AD作用的潜在药物,为上市药物抗AD作用重定位提供了重要信息。
关键词:    阿尔茨海默病      多靶点      虚拟筛选      全球上市药物      药物重定位      分子对接     
Repositioning drug discovery for Alzheimer's disease based on global marketed drug data
ZHANG Bao-yue1, PANG Xiao-cong1,2, JIA Hao1, WANG Zhe1, LIU Ai-lin1, DU Guan-hua1
1. Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China;
2. Department of Pharmacy, Peking University First Hospital, Beijing 100034, China
Abstract:
Alzheimer's disease (AD) is a neurodegenerative disease that seriously threatens the life of the elderly and there is no effective therapy to treat or delay the onset of this disease. Due to the multifactorial etiology of this disease, the multi-target-directed ligand (MTDL) approach is an innovative and promising method in search for new drugs against AD. In order to find potential multi-target anti-AD drugs through reposition of current drugs, the database of global drugs on market were mined by an anti-AD multi-target prediction platform established in our laboratory. As a result, inositol nicotinate, cyproheptadine, curcumin, rosiglitazone, demecarium, oxybenzone, agomelatine, codeine, imipramine, dyclonine, melatonin, perospirone, and bufexamac were predicted to act on at least one anti-AD drug target yet act against AD through various mechanisms. The compound-target network was built using the Cytoscape. The prediction was validated by molecular docking between agomelatine and its multiple targets, including ADORA2A, ACHE, BACE1, PTGS2, MAOB, SIGMAR1 and ESR1. Agomelatine was shown to be able to act on all the targets above. In conclusion, the potential drugs for anti-AD therapy in the database for global drugs on market was partially uncovered using machine learning, network pharmacology, and molecular docking methods. This study provides important information for drug reposition in anti-AD therapy.
Key words:    Alzheimer's disease    multi-target    virtual screening    global market drug    repositioning    molecular docking   
收稿日期: 2019-03-08
DOI: 10.16438/j.0513-4870.2019-0165
基金项目: 国家自然科学基金资助项目(81673480);北京市自然科学基金资助项目(7192134);国家人口健康科学数据共享平台资源专项课题(NCMI-AGD05-201809);协和创新工程(2016-I2M-3-007);"重大新药创制"国家科技重大专项资助项目(2014ZX09507003-002).
通讯作者: 刘艾林,Tel/Fax:86-10-83150885,E-mail:liuailin@imm.ac.cn;杜冠华,Tel/Fax:86-10-63165184,E-mail:dugh@imm.ac.cn
Email: liuailin@imm.ac.cn;dugh@imm.ac.cn
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