Recent advances in computational approaches for designing potential anti-alzheimer’s agents

Abstract

Alzheimer’s disease (AD) is the leading cause of dementia in old people worldwide and one of the leading causes of death in developed countries. The current poor understanding of AD mechanisms makes it difficult to develop novel drugs that could be used to treat effectively this disease. Different enzymes are known to be crucial in the biochemical pathways involved in the development of AD and therefore can be considered as potential targets to design efficient drugs. Among them, three enzymes stand out: acetylcholinesterase (AChE), β-amyloid cleaving enzyme 1 (BACE1), and glycogen synthase kinase-3 (GSK-3). Chemoinformatics and molecular modeling methodologies have been used for decades for the selection and optimization of new compounds with therapeutic properties in different areas. The initial works in computational drug discovery (CDD) were only considered as promising theoretical studies. However, currently, these in silico methodologies are part of the normal drug discovery process, and they are usually implemented in the search of novel drugs or for the optimization of therapeutic activity (or pharmacokinetic properties) of chemical series. In particular, the search for drugs in the field of neurodegenerative disorders is very active, though unfortunately no cure exists nowadays for AD. In this review, we will present the advances on the use of computational techniques in the search for novel small molecules as effective therapeutic agents against AD. We will describe recent computational studies to find or design new anti-AD compounds applying different computational approaches, mainly quantitative structure-activity relationship (QSAR), molecular docking, pharmacophore development, and molecular dynamics simulations. Taking into account that there is a huge amount of literature on the field, we have chosen to focus on studies published in the last few years related to the main AD targets (AChE, BACE1, and GSK-3). We will conclude by providing a perspective on the future of this field.