2D QSAR of PPARγ agonist binding and transactivation.

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Authors

Multilinear QSAR models are developed for the largest and most diverse set of PPARγ agonists treated hitherto. Binding of these small molecules to the human nuclear receptor PPARγ is described by models that are built on simple 2D molecular descriptors and nevertheless are of good quality and predictive power (e.g., 144 compounds, 10 descriptors, r 2 = 0.79, r cv 2 = 0.76). The models presented are thoroughly validated by crossvalidation, randomization experiments, bootstrapping, and training set/test set partitioning. They may therefore be helpful in the design of new antidiabetic drug candidates. For gene transactivation, the functional activity of the agonists, a corresponding model for a similarly diverse compound set is of somewhat lower statistical quality.

Original languageEnglish
JournalBioorganic & Medicinal Chemistry
Volume14
Issue number15
Pages (from-to)5178-5195
Number of pages18
DOIs
Publication statusPublished - 01.08.2006
Externally publishedYes

    Research areas

  • Chemistry
  • 2D QSAR, PPARγ agonists, Type 2 diabetes