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

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

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.