Virtual identification of novel PPARα/γ dual agonists by 3D-QSAR, molecule docking and molecular dynamics studies
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. AbbreviationsDM
diabetes mellitus
T2DMtype 2 diabetes
PPARsperoxisome proliferator-activated receptors
LBDDligand based drug design
3D-QSARthree-dimensional quantitative structure activity relationship
CoMFAcomparative molecular field analysis
PLSpartial least square
LOOleave-one-out
q2cross-validated correlation coefficient
ONCoptimal number of principal components
r2non-cross-validated correlation coefficient
SEEstandard error of estimate
Fthe Fischer ratio
r2predpredictive correlation coefficient
DBDDNA binding domain
MDmolecular dynamics
RMSDroot-mean-square deviation
RMSFroot mean square fluctuations
diabetes mellitus
type 2 diabetes
peroxisome proliferator-activated receptors
ligand based drug design
three-dimensional quantitative structure activity relationship
comparative molecular field analysis
partial least square
leave-one-out
cross-validated correlation coefficient
optimal number of principal components
non-cross-validated correlation coefficient
standard error of estimate
the Fischer ratio
predictive correlation coefficient
DNA binding domain
molecular dynamics
root-mean-square deviation
root mean square fluctuations
Communicated by Ramaswamy H. Sarma
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.
