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

Abstract

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.

Keywords::

• Alzheimer’s disease
• cheminformatics
• chemometrics
• quantitative structure–activity relationship

Declaration of interest

The authors were supported by the Department of Biotechnology (DBT), Government of India, New Delhi for the financial assistance. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Notes

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