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Comput Biol Chem ; 112: 108142, 2024 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-39004027

RESUMO

This study demonstrated the correlation of molecular structures of Peroxisome proliferator-activated receptor gamma (PPARγ) modulators and their biological activities. Bayesian classification, and recursive partitioning (RP) studies have been applied to a dataset of 323 PPARγ modulators with diverse scaffolds. The results provide a deep insight into the important sub-structural features modulating PPARγ. The molecular docking analysis again confirmed the significance of the identified sub-structural features in the modulation of PPARγ activity. Molecular dynamics simulations further underscored the stability of the complexes formed by investigated modulators with PPARγ. Overall, the integration of many computational approaches unveiled key structural motifs essential for PPARγ modulatory activity that will shed light on the development of effective modulators in the future.


Assuntos
Hipoglicemiantes , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , PPAR gama , PPAR gama/química , PPAR gama/metabolismo , PPAR gama/agonistas , Hipoglicemiantes/química , Hipoglicemiantes/farmacologia , Humanos , Teorema de Bayes , Estrutura Molecular
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