Pharmacophore-driven identification of PPARγ agonists from natural sources

R. K. Petersen, Kathrine Bisgaard Christensen, A. N. Assimopoulou, X. Fretté, V. P. Papageorgiou, K. Kristiansen, Irene Kouskoumvekaki

    Research output: Contribution to journalJournal articleResearchpeer-review


    In a search for more effective and safe anti-diabetic compounds, we developed a pharmacophore model based on partial agonists of PPARγ. The model was used for the virtual screening of the Chinese Natural Product Database (CNPD), a library of plant-derived natural products primarily used in folk medicine. From the resulting hits, we selected methyl oleanonate, a compound found, among others, in Pistacia lentiscus var. Chia oleoresin (Chios mastic gum). The acid of methyl oleanonate, oleanonic acid, was identified as a PPARγ agonist through bioassay-guided chromatographic fractionations of Chios mastic gum fractions, whereas some other sub-fractions exhibited also biological activity towards PPARγ. The results from the present work are two-fold: on the one hand we demonstrate that the pharmacophore model we developed is able to select novel ligand scaffolds that act as PPARγ agonists; while at the same time it manifests that natural products are highly relevant for use in virtual screening-based drug discovery.
    Original languageEnglish
    JournalJournal of Computer - Aided Molecular Design
    Issue number2
    Pages (from-to)107-116
    Publication statusPublished - 2011

    Bibliographical note

    The online version of this article (doi:10.1007/s10822-010-9398-5) contains supplementary material, which is available to authorized users.


    • PPARc agonist
    • Pharmacophore model
    • Virtual screening
    • Natural compounds

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