Virtual screening combined with molecular docking for the !identification of new anti-adipogenic compounds.

Obesity is an important risk factor for diabetes, cardiovascular diseases, and cancer, reducing the quality of life and expectancy of millions of people. Consequently, obesity has turned into one of the most health public problems worldwide, which highlights the urgent need for new and safe treatments. Obesity is mainly related to excessive fat accumulation; therefore, proteins participating in white adipose tissue increase and dysfunction are considered pertinent and attractive targets for developing new methods that can help with body weight control. In this context, virtual screening of libraries containing a large number of molecules represents a valuable strategy for the identification of potential anti-adipogenic compounds with reduced costs and time production. Here, we review the scientific literature about the prediction of new ligands of specific proteins through molecular docking and virtual screening of chemical libraries, with the aim of proposing new potential anti-adipogenic molecules. First, we present the targets related to adipogenesis and adipocyte functions that were selected for the following studies: PPARγ, Crif1, SIRT1, ERβ, PC1, FTO, Mss51, and FABP4. Then, we describe the obtention of new ligands according to the characteristics of the virtual screening approach, i.e. a structure-based drug design (SBDD) or a ligand-based drug design (LBDD). Finally, the critical analysis of these computational strategies and the corresponding results points out the necessity of combining computational and