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Virtual identification of novel PPARα/γ dual agonists by 3D-QSAR, molecule docking and molecular dynamics studies.
Liu, Ya-Ya; Feng, Xiao-Yan; Jia, Wen-Qing; Jing, Zhi; Xu, Wei-Ren; Cheng, Xian-Chao.
Afiliación
  • Liu YY; Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin, China.
  • Feng XY; Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin, China.
  • Jia WQ; Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin, China.
  • Jing Z; Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin, China.
  • Xu WR; Tianjin Key Laboratory of Molecular Design and Drug Discovery, Tianjin Institute of Pharmaceutical Research, Tianjin, China.
  • Cheng XC; Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin, China.
J Biomol Struct Dyn ; 38(9): 2672-2685, 2020 Jun.
Article en En | MEDLINE | ID: mdl-31418313
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. AbbreviationsDMdiabetes mellitusT2DMtype 2 diabetesPPARsperoxisome proliferator-activated receptorsLBDDligand based drug design3D-QSARthree-dimensional quantitative structure activity relationshipCoMFAcomparative molecular field analysisPLSpartial least squareLOOleave-one-outq2cross-validated correlation coefficientONCoptimal number of principal componentsr2non-cross-validated correlation coefficientSEEstandard error of estimateFthe Fischer ratior2predpredictive correlation coefficientDBDDNA binding domainMDmolecular dynamicsRMSDroot-mean-square deviationRMSFroot mean square fluctuationsCommunicated by Ramaswamy H. Sarma.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Relación Estructura-Actividad Cuantitativa / PPAR alfa / PPAR gamma Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Biomol Struct Dyn Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Relación Estructura-Actividad Cuantitativa / PPAR alfa / PPAR gamma Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Biomol Struct Dyn Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido