Using Drugs as Molecular Probes: A Computational Chemical Biology Approach in Neurodegenerative Diseases

作     者：Emon, Mohammad Asif Emran Khan Kodamullil, Alpha Tom Karki, Reagon Younesi, Erfan Hofmann-Apitius, Martin 

作者机构：Fraunhofer Inst Algorithms & Sci Comp SCAI Dept Bioinformat D-53754 St Augustin Germany Univ Bonn Bonn Aachen Int Ctr IT Bonn Germany 

出 版 物：《JOURNAL OF ALZHEIMERS DISEASE》 (阿耳茨海默氏病杂志)

年 卷 期：2017年第56卷第2期

页      面：677-686页

核心收录：

学科分类：1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

基　　金：EU/EFPIA Innovative Medicines Initiative Joint Undertaking under AETIONOMY European Union's Seventh Framework Programme (FP7) 

主　　题：Alzheimer disease amyotrophic lateral sclerosis biological expression language disease-drug modeling drug repositioning neurodegenerative diseases 

摘      要：Neurodegenerative diseases including Alzheimer s disease are complex to tackle because of the complexity of the brain, both in structure and function. Such complexity is reflected by the involvement of various brain regions and multiple pathways in the etiology of neurodegenerative diseases that render single drug target approaches ineffective. Particularly in the area of neurodegeneration, attention has been drawn to repurposing existing drugs with proven efficacy and safety profiles. However, there is a lack of systematic analysis of the brain chemical space to predict the feasibility of repurposing strategies. Using a mechanism-based, drug-target interaction modeling approach, we have identified promising drug candidates for repositioning. Mechanistic cause-and-effect models consolidate relevant prior knowledge on drugs, targets, and pathways from the scientific literature and integrate insights derived from experimental data. We demonstrate the power of this approach by predicting two repositioning candidates for Alzheimer s disease and one for amyotrophic lateral sclerosis.