Virtual Screening Studies for Discovery of Novel Inhibitors of Inflammatory Process Targets

Abstract

Inflammation has been very evident in infectious diseases, but in recent times research has increasingly shown that a range of non-infectious diseases may present with inflammatory conditions. This fact becomes important as new anti-inflammatory drugs emerge with different targets for treatment of diseases. Virtual screening (VS) involves applying computational methods to discover new ligands for biological structures from the formation of large libraries composed of a large number of compounds. This review aims to report several studies employing a variety of VS: ligand-based and structure-based VS are being used more frequently in combination to decrease the probability of choosing false positive candidates. There are also studies that use only one approach. Docking is widely employed as structure-based VS methodology, however pharmacophore models based on the structure are becoming more prevalent. Molecular dynamics simulations, despite their computational cost, are still utilized to validate docking scores and analyze the stability of the complex ligand-structure. It is important to note that several studies employed several drug-like rules to screen structures, as well, decoys and PAINS to validate the models. Natural product databases, despite the lower number of the compounds compared to other databases that are available, are commonly referred to as a source of drug-like molecules. There is a literal explosion of software being released for a variety of purposes and several of them are free tools and/or web tools. Overall, VS studies are nowadays a normal part of medicinal chemistry to determine novel potential inhibitors for targets of inflammatory diseases.