Virtual high-throughput screening of peroxisome proliferator-activated receptor Inhibitors
Loading...
Date
2012
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
CCSHAU
Abstract
Peroxisome proliferator-activated receptors are ligand activated transcription factors that belong to the
nuclear receptor super family and are involved in control of energy, lipid and glucose homeostasis.
There are three different isotypes of the receptor namely, PPARα, PPARβ/δ and PPARγ. The moderate
(or partial) levels of PPAR-γ activation coordinate an evolutionary beneficial and adaptive response.
Current evidence shows that there are natural PPAR activators, which brings this tightly regulated
system out of balance, and contributes to the pathogenesis of life-style associated diseases, such as
obesity, type2 diabetes, and atherosclerosis. This also indicates that inhibiting PPAR activity, rather
than activating, might be the preferred therapeutic strategy to treat the above disorders. In this study,
virtual high throughput screening of PPAR inhibitors was performed using UCSF DOCK 6.0. The
three sets of databases were prepared namely, NCI database, ZIN C (target-wise) database and ZINC
(lead-like) database. PPARγ was selected as the receptor as the three isotypes were 80% similar. The
ouput of the first run (NCI database) contained 1516 compounds. The output of second run (ZINC
target-wise) contained 20 compounds. The output of third run (ZINC lead-like) contained 103
compounds. Scoring was done for each compound by summing the energies calculated by DOCK. The
cluster analysis was done using Ches-Mapper. In the first run, NCI dataset was used, in which 1516
compounds were taken and resulted in the identification of 8 ligands. Out of 20 compounds obtained
from virtual screening of ZINC (target-wise), two of them were identified as the ligands. In the third
run, ZINC (lead-like) database was used in which 7 ligands were obtained. Lastly, the obtained hits
were compared with the known inhibitors and it was found that the groups present in the inhibitors are
similar to the groups present in the hits.
Description
Keywords
Ligands, Zinc, Biological phenomena, Selection, Organic compounds, Biochemical compounds, Acidity, Proteins, Diseases, Transcription