EMERGING NEUROPROTECTIVE AND ANTI-INFLAMMATORY AGENTS: A REVIEW OF IN SILICO DESIGN AND PRECLINICAL DEVELOPMENT

Background: Neuroinflammation is an important pathophysiological factor in the etiology of multiple neurodegenerative conditions such as Alzheimer, Parkinson, and multiple sclerosis. Anti-inflammatory properties of novel neuroprotective agents are promising in the context of their development. In silico drug design has proven as a cost effective and time saving approach to finding potential lead compounds. Objective: The aim of the review is to critically analyze the current position of in silico methods to design neuroprotective compounds with anti-inflammatory properties followed by preclinical validation. Methods: PubMed, Scopus, and Web of Science databases were searched to identify the literature published in 2018-2024. The key words were in silico drug design, neuroprotection, anti-inflammatory, molecular docking and QSAR. Results: Recent computational drug design progress has enabled the identification of new scaffolds against neuroinflammation. Machine learning methods, molecular docking experiments, and QSAR simulation have played a significant role in forecasting neuroprotective potential of compounds. There are a number of favourable candidates which have demonstrated high activity in preclinical models. Conclusion: Convincing potentials in the design of suitable neuroprotective drugs have been evident in in silico drug design methods. To enable successful translation to clinical applications, it is necessary to integrate various methods of computation with strong preclinical validation.