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Related Experiment Video

Updated: May 7, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
14:34

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

Published on: April 3, 2026

Structure-based identification of novel PPAR gamma ligands.

Flávia M C da Silva1, Jademilson C dos Santos, Jéssica L O Campos

  • 1Universidade Federal do ABC, Rua Santa Adelia, 166 Bangu, Santo Andre, SP 09210-170, Brazil.

Bioorganic & Medicinal Chemistry Letters
|October 1, 2013
PubMed
Summary

New research identifies novel ligands that bind to Peroxisome proliferator-activated receptor gamma (PPARγ), offering potential therapeutic strategies for type 2 diabetes. These findings explore alternative approaches beyond full receptor activation for diabetes management.

Keywords:
DockingPPAR gammaVirtual screening

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Last Updated: May 7, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
14:34

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

Published on: April 3, 2026

Area of Science:

  • Pharmacology
  • Molecular Biology
  • Medicinal Chemistry

Background:

  • Peroxisome proliferator-activated receptor gamma (PPARγ) is crucial for glucose metabolism and a therapeutic target for type 2 diabetes.
  • Concerns exist regarding the safety of full PPARγ agonists like rosiglitazone due to links with myocardial infarction.
  • Partial agonists and antagonists of PPARγ have shown promise in improving insulin sensitivity and managing side effects.

Purpose of the Study:

  • To identify novel PPARγ ligands using a structure-based approach.
  • To explore alternative therapeutic strategies for type 2 diabetes by investigating compounds with varying PPARγ activation profiles.

Main Methods:

  • Structure-based virtual screening of the 'Drugs-Now' subset of the ZINC database.
  • Visual inspection and selection of 15 potential ligands.
  • In vitro testing of ligand binding affinity to PPARγ and molecular dynamic simulations.

Main Results:

  • Three novel compounds were identified as PPARγ ligands with IC50 values below 10μM: a benzoimidazol acetate, a bromobenzyl-thio-tetrazol benzoate, and a [[2-[(1,3-dioxoinden-2-ylidene)methyl]phenoxy]methyl]benzoate.
  • Molecular dynamics simulations highlighted key residues (H323, H449, Y327, Y473, K367, S289) involved in ligand binding within the PPARγ polar arm.

Conclusions:

  • The identified compounds represent potential new therapeutic agents for type 2 diabetes.
  • This study validates structure-based screening for discovering PPARγ modulators.
  • Understanding key binding interactions can guide the design of future PPARγ-targeting drugs.