Pharmacophore-based virtual screening, biological evaluation and binding mode analysis of a novel protease-activated receptor 2 antagonist

Nam Chul Cho, Seoung Hwan Seo, Dohee Kim, Ji Sun Shin, Jeongmin Ju, Jihye Seong, Seon Hee Seo, Iiyoun Lee, Kyung Tae Lee, Yun Kyung Kim, Kyoung Tai No, Ae Nim Pae

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Protease-activated receptor 2 (PAR2) is a G protein-coupled receptor, mediating inflammation and pain signaling in neurons, thus it is considered to be a potential therapeutic target for inflammatory diseases. In this study, we performed a ligand-based virtual screening of 1.6 million compounds by employing a common-feature pharmacophore model and two-dimensional similarity search to identify a new PAR2 antagonist. The common-feature pharmacophore model was established based on the biological screening results of our in-house library. The initial virtual screening yielded a total number of 47 hits, and additional biological activity tests including PAR2 antagonism and anti-inflammatory effects resulted in a promising candidate, compound 43, which demonstrated an IC50 value of 8.22 µM against PAR2. In next step, a PAR2 homology model was constructed using the crystal structure of the PAR1 as a template to explore the binding mode of the identified ligands. A molecular docking method was optimized by comparing the binding modes of a known PAR2 agonist GB110 and antagonist GB83, and applied to predict the binding mode of our hit compound 43. In-depth docking analyses revealed that the hydrophobic interaction with Phe2435.39 is crucial for PAR2 ligands to exert antagonistic activity. MD simulation results supported the predicted docking poses that PAR2 antagonist blocked a conformational rearrangement of Na+ allosteric site in contrast to PAR2 agonist that showed Na+ relocation upon GPCR activation. In conclusion, we identified new a PAR2 antagonist together with its binding mode, which provides useful insights for the design and development of PAR2 ligands.

Original languageEnglish
Pages (from-to)625-637
Number of pages13
JournalJournal of Computer-Aided Molecular Design
Volume30
Issue number8
DOIs
Publication statusPublished - 2016 Aug 1

All Science Journal Classification (ASJC) codes

  • Drug Discovery
  • Computer Science Applications
  • Physical and Theoretical Chemistry

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