Title:Computational Strategies to Identify New Drug Candidates against
Neuroinflammation
Volume: 29
Issue: 27
关键词:
神经炎症，药物设计，分子建模，分子对接，分子动力学，BBB渗透。
摘要: 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.
