Computational Strategies to Identify New Drug Candidates against Neuroinflammation

Increasing application of computational approaches in these last decades has deeply modified the process of discovery and commercialization of new therapeutic entities. This is especially true in the field of neuroinflammation, in which both the peculiar anatomical localization and the presence of the blood-brain barrier make it mandatory to finely tune the candidates' physicochemical properties from the early stages of the discovery pipeline. The aim of this review is, therefore, to provide a general overview of neuroinflammation to the readers, together with the most common computational strategies that can be exploited to discover and design small molecules controlling neuroinflammation, especially those based on the knowledge of the three-dimensional structure of the biological targets of therapeutic interest. The techniques used to describe the molecular recognition mechanisms, such as molecular docking and molecular dynamics, will therefore be discussed, highlighting their advantages and limitations. Finally, we report several case studies in which computational methods have been applied to drug discovery for neuroinflammation, focusing on the research conducted in the last decade.