Abstract
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.
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Acknowledgments
IK acknowledges financial support from the Danish Research Council for Technology and Production Sciences (Grant 274-06-0301). This work was further supported by the Danish Council for Strategic Research (Grant No. 2101-01-0065).
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Rasmus K. Petersen and Kathrine B. Christensen have equally contributed to this article.
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Petersen, R.K., Christensen, K.B., Assimopoulou, A.N. et al. Pharmacophore-driven identification of PPARγ agonists from natural sources. J Comput Aided Mol Des 25, 107–116 (2011). https://doi.org/10.1007/s10822-010-9398-5
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DOI: https://doi.org/10.1007/s10822-010-9398-5