Advances in quantitative structure-activity relationship models of anti-Alzheimer's agents

被引:20
作者
Ambure, Pravin [1 ]
Roy, Kunal [1 ]
机构
[1] Jadavpur Univ, Dept Pharmaceut Technol, Drug Theoret & Cheminformat Lab, Kolkata 700032, India
关键词
Alzheimer's disease; cheminformatics; chemometrics; quantitative structure-activity relationship; GAMMA-SECRETASE INHIBITORS; NICOTINIC ACETYLCHOLINE-RECEPTOR; AMYLOID PRECURSOR PROTEIN; PREDICTIVE QSAR MODELS; MOLECULAR DOCKING; ACTIVITY CLIFFS; 3D QSAR; BUTYRYLCHOLINESTERASE INHIBITORS; NEURODEGENERATIVE DISEASES; CEREBROSPINAL-FLUID;
D O I
10.1517/17460441.2014.909404
中图分类号
R9 [药学];
学科分类号
100702 [药剂学];
摘要
Introduction: Alzheimer's disease (AD) is one of the lethal diseases, mainly affecting older people. The unclear root cause and involvement of various enzymes in the pathological conditions confirm the complexity of the disease. Quantitative structure-activity relationship (QSAR) techniques are of great significance in the design of drugs against AD. Areas covered: In the present review, the authors provide a basic background about AD and QSAR techniques. Furthermore, they review the various QSAR studies reported against various targets of AD. The information provided for each QSAR study includes chemical scaffold and target enzyme under study, applied QSAR technique and outcomes of the respective study. Expert opinion: In silico techniques like QSAR hold great potential in designing leads against a complex disease like AD. In combination with other in silico techniques, QSAR can provide more useful and rational insight to facilitate the discovery of novel compounds. Only few QSAR studies on imaging agents have been reported; hence, more QSAR studies are recommended to explore the biomarker or imaging agents for improving diagnosis. Again, for proper symptomatic treatment, multi-target drugs acting on more than one target are required. Hence, more multi-target QSAR studies are recommended in future to achieve this goal.
引用
收藏
页码:697 / 723
页数:27
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