Design Of Anti-diabetic Lead Compounds Based On PPARs Targetand CADD Technology

Objective: PPARα and PPARγ are the most widely studied peroxisome proliferator-activated receptor(PPAR)subtypes due to their important roles in regulating glucose,lipids and cholesterol metabolism.The thiazolidinedione class antidiabetic agents are restricted in clinic because of the side effects such as edema,weight gain and heart failure.By combining the lowering serum triglyceride levels benefit of PPARα agonists with the glycemic advantages of the PPARγ agonists,the dual PPARα/γ agonistscan both improve the metabolic effects and minimize the side effects.PPARγ antagonists can bind reversibly with high affinity but do not induce transactivation of the receptor,yet they act as insulin sensitizers and reduce the side effects.In this paper,PPARα/γ dual agonists and PPARγ antagonists were designed and screened by means of computer-aided drug design in order to avoid the side effects of the thiazolidinediones and lay the foundation for the development of novel antidiabetic drugs.Methods: 1.By means of virtual screening,Glide SP(standard precision),ADMET prediction and molecular dynamics(MD)simulations techniques using Schr?dinger suite 2009 software,one compound with stable binding to PPARα/γ,good pharmacokinetic properties,and low toxicity were gained from Asinex database.2.We use the Discovery Studio 4.0 software to perform molecular docking and 3D-QSAR studies on 55 PPARγ antagonists,then carry out structural modifications to obtain molecules with higher activity values and docking scores than the original compound,which can be further optimized to become new PPARγ antagonists.3.Starting from the approved PPARα/γ dual agonist Saroglitazar as the lead compound,using core hopping,CDOCKER,ADMET prediction and molecular dynamics simulation,PPARα/γ dually active compounds were gained.4.We construct a pharmacophore model based on PPARα/γ receptor-ligand complexes using Discovery Studio 4.0 software,and perform virtual screening,CDOCKER,ADMET prediction,and molecular dynamics simulation to screen CHEMBL database.Finally,we get PPARα/γ dual agonists.Results: 1.We obtain compound ASN 15761007 through screening of Asinex database.The docking pattern,docking score,ADMET prediction and molecular dynamics results of compound ASN 15761007 were better than original ligands.2.By molecular docking,3D-QSAR,and structural optimizationof the known PPARγ antagonists,four new PPARγ antagonists were obtained.3.Using Saroglitazar as the lead compound,the α-O substituted phenylpropanoic acid scaffold of Saroglitazar was replaced by L-tyrosine,which was then further modified to obtain comp#L-17-1 and comp#L-3-1.4.Through the pharmacophore screening,CDOCKER,ADMET prediction and molecular dynamics simulation of the CHEMBL database,the compound CHEMBL 230490 was gained with druggability and stable interactions with PPARα/γ.Conclusion: This paper based on PPARs targets.We use virtual screening,3D-QSAR,core hopping,pharmacophore,ADMET prediction and molecular dynamics simulation methods and got 8 PPARα/γ dual agonists and PPARγ antagonists.These compounds can form stable hydrogen bonds and hydrophobic interactions with receptors,and have low toxicities and side effects.It provides a theoretical basis for the study of novel antidiabetic drugs.