Challenges and Discoveries in Polypharmacology of Neurodegenerative Diseases

Background Neurological disorders are composed of several diseases that affect the central and peripheral nervous system; among these are neurodegenerative diseases, which lead to neuronal death. Many of these diseases have treatment for the disease and symptoms, leading patients to use several drugs that cause side effects. Introduction The search for new treatments has led to the investigation of multi-target drugs. Methods This review aimed to investigate in the literature the multi-target effect in neurological disorders through an in silico approach. Studies were reviewed on the diseases such as epilepsy, Alzheimer's disease, Amyotrophic Lateral Sclerosis (ALS), Huntington's disease, cerebral ischemia, and Parkinson's disease. Results As a result, the study emphasize the relevance of research by computational techniques such as quantitative structure-activity relationship (QSAR) prediction models, pharmacokinetic prediction models, molecular docking, and molecular dynamics, besides presenting possible drug candidates with multi-target activity. Conclusion It was possible to identify several targets with pharmacological activities. Some of these targets had diseases in common such as carbonic anhydrase, acetylcholinesterase, NMDA, and MAO being relevant for possible multi-target approaches.

Automated summary

This study investigated the multi-target effect in neurological disorders through computational techniques. The results suggest that computational methods can identify multiple pharmacologically active targets and propose possible drug candidates with multi-target activity.