Abstract
BackgroundAlthough there are successful examples of the discovery of new PPARγ agonists, it has recently been of great interest to identify new PPARγ partial agonists that do not present the adverse side effects caused by PPARγ full agonists. Consequently, the goal of this work was to design, apply and validate a virtual screening workflow to identify novel PPARγ partial agonists among natural products.Methodology/Principal FindingsWe have developed a virtual screening procedure based on structure-based pharmacophore construction, protein-ligand docking and electrostatic/shape similarity to discover novel scaffolds of PPARγ partial agonists. From an initial set of 89,165 natural products and natural product derivatives, 135 compounds were identified as potential PPARγ partial agonists with good ADME properties. Ten compounds that represent ten new chemical scaffolds for PPARγ partial agonists were selected for in vitro biological testing, but two of them were not assayed due to solubility problems. Five out of the remaining eight compounds were confirmed as PPARγ partial agonists: they bind to PPARγ, do not or only moderately stimulate the transactivation activity of PPARγ, do not induce adipogenesis of preadipocyte cells and stimulate the insulin-induced glucose uptake of adipocytes.Conclusions/SignificanceWe have demonstrated that our virtual screening protocol was successful in identifying novel scaffolds for PPARγ partial agonists.
Highlights
Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptor superfamily that regulate the gene expression of proteins involved in energy, glucose and lipid metabolism, adipocyte proliferation and differentiation and insulin sensitivity [1]
This is the only virtual screening (VS) step for which the active set was composed of PPARc full agonists and the inactive set was decoys and PPARc partial agonists; the statistics for this VS step were calculated using these considerations
We have shown that a VS workflow based on two structurebased 3D pharmacophores, protein-ligand docking and electrostatic/shape similarity analysis is able to discover novel scaffolds for PPARc partial agonists
Summary
Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptor superfamily that regulate the gene expression of proteins involved in energy, glucose and lipid metabolism, adipocyte proliferation and differentiation and insulin sensitivity [1]. Partial agonists activate PPARc by an H12-independent mechanism [12,13], and the key interactions between partial agonists and the ligand-binding domain (LBD) of PPARc are different than those of the full agonists [9] (i.e., partial agonists do not bind to PPARc by the net of hydrogen bonds used by full agonists). A new mechanism by which partial and full PPARc agonists act to improve insulin sensitivity independent of receptor agonism has been suggested This mechanism consists of blocking the phosphorylation of PPARc at Ser 273 [16] and may explain how partial agonists can exhibit similar or higher antidiabetic effects than those of full agonists. The goal of this work was to design, apply and validate a virtual screening workflow to identify novel PPARc partial agonists among natural products
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