T2384

Thiazolidinone derivatives have been found to exhibit a wide range of pharmacological activities. 2-Thiazolylimino-5-benzylidene-thiazolidin-4-one derivatives show antibacterial activity in in vitro tests which are comparable to marketed drugs. However, the target for this scaffold remains yet to be identified. In our work, we identified seven putative targets for this scaffold using web servers such as DRAR-CPI, PharmMapper, and TarFisDock and databases such as BindingDB and ChEMBL. Each of these servers used different algorithms and scoring functions for protein target identification. Further, these targets are substantiated by molecular docking analysis. Based on the docking studies, scaffold 2-thiazolylimino-5-benzylidene-thiazolidin-4-one is observed to exhibit affinity against diverse targets, particularly, towards COX-2, acetylcholinesterase, aldose reductase, and thyroid hormone receptor alpha. This study describes an initial probability that these proteins may be targeted by this scaffold.

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.