Virtual identification of novel PPARα/γ dual agonists by 3D-QSAR, molecule docking and molecular dynamics studies

Abstract

Peroxisome proliferator-activated receptors (PPARs) are considered important targets for the treatment of Type 2 diabetes (T2DM). To accelerate the discovery of PPAR α/γ dual agonists, the comparative molecular field analysis (CoMFA) were performed for PPARα and PPARγ, respectively. Based on the molecular alignment, highly predictive CoMFA model for PPARα was obtained with a cross-validated q² value of 0.741 and a conventional r² of 0.975 in the non-cross-validated partial least-squares (PLS) analysis, while the CoMFA model for PPARγ with a better predictive ability was shown with q² and r² values of 0.557 and 0.996, respectively. Contour maps derived from the 3D-QSAR models provided information on main factors towards the activity. Then, we carried out structural optimization and designed several new compounds to improve the predicted biological activity. To investigate the binding modes of the predicted compounds in the active site of PPARα/γ, a molecular docking simulation was carried out. Molecular dynamic (MD) simulations indicated that the predicted ligands were stable in the active site of PPARα/γ. Therefore, combination of the CoMFA and structure-based drug design results could be used for further structural alteration and synthesis and development of novel and potent dual agonists.

Abbreviations
DM	=	diabetes mellitus
T2DM	=	type 2 diabetes
PPARs	=	peroxisome proliferator-activated receptors
LBDD	=	ligand based drug design
3D-QSAR	=	three-dimensional quantitative structure activity relationship
CoMFA	=	comparative molecular field analysis
PLS	=	partial least square
LOO	=	leave-one-out
q2	=	cross-validated correlation coefficient
ONC	=	optimal number of principal components
r2	=	non-cross-validated correlation coefficient
SEE	=	standard error of estimate
F	=	the Fischer ratio
r2pred	=	predictive correlation coefficient
DBD	=	DNA binding domain
MD	=	molecular dynamics
RMSD	=	root-mean-square deviation
RMSF	=	root mean square fluctuations

Communicated by Ramaswamy H. Sarma

Graphical Abstract

In this study, we explored the SARs of zwitterionic derivatives dually targeting PPARα/γ and designed novel PPARα/γ dual agonists, using 3D-QSAR studies. Molecular docking and molecular dynamics simulation served as validation and complement to the SAR results derived from the 3D-QSAR model.

Keywords:

• Antidiabetic
• PPARα/γ
• CoMFA
• structural optimization
• molecular docking

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the [Natural Science Foundation of Tianjin] under Grant [number 18JCYBJC28800]; [Opening Project of Shanghai Key Laboratory of New Drug Design] under Grant [number SKLNDD-KF-201803]; [National Natural Science Foundation of China] under Grant [number 21202120]; [China Postdoctoral Science Foundation] under Grant [number 2012T50237].