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

• Published in: Journal of biomolecular structure & dynamics Vol. 38; no. 9; pp. 2672 - 2685
• Main Authors: Liu, Ya-Ya, Feng, Xiao-Yan, Jia, Wen-Qing, Jing, Zhi, Xu, Wei-Ren, Cheng, Xian-Chao
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis 12.06.2020
• Subjects: Antidiabetic; CoMFA; Diabetes Mellitus, Type 2 - drug therapy; Humans; molecular docking; Molecular Docking Simulation; Molecular Dynamics Simulation; PPAR alpha - agonists; PPAR gamma - agonists; PPARα/γ; Quantitative Structure-Activity Relationship; structural optimization; PPARα/γ; molecular docking; Antidiabetic; structural optimization; CoMFA
• ISSN: 0739-1102; 1538-0254
• DOI: 10.1080/07391102.2019.1656110

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 q 2 value of 0.741 and a conventional r 2 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 q 2 and r 2 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 q 2 cross-validated correlation coefficient ONC optimal number of principal components r 2 non-cross-validated correlation coefficient SEE standard error of estimate F the Fischer ratio r 2 pred 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 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.