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, China 100050)
(2.Department of Pharmacy, Peking University First Hospital, Beijing, China 100034)

【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 ADORA2 A, 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 were partially uncovered using machine learning, network pharmacology, and molecular docking methods. This study provides important information for drug reposition in anti-AD therapy.

【Keywords】 Alzheimer’s disease; multi-target; virtual screening; global market drug; repositioning; molecular docking;

【DOI】

【Funds】 National Natural Science Foundation of China (81673480) Natural Science Foundation of Beijing (7192134) National Special Project of Data Sharing Platform of Population Health Science (NCMIAGD05-201809) Medical and Health Innovation Project of Chinese Academy of Medical Sciences (2016-I2M-3- 007) National Major Scientific and Technological Special Project for “Significant New Drugs Development” (2014ZX09507003-002)

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This Article

ISSN:0513-4870

CN: 11-2163/R

Vol 54, No. 07, Pages 1214-1224

July 2019

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Article Outline

Abstract

  • Materials and methods
  • Results
  • Discussion
  • References