Novel human mPGES-1 inhibitors identified through structure-based virtual screening

Adel Hamza, Xinyun Zhao, Min Tong, Hsin Hsiung Tai, Chang Guo Zhan

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

Microsomal prostaglandin E synthase-1 (mPGES-1) is an inducible prostaglandin E synthase after exposure to pro-inflammatory stimuli and, therefore, represents a novel target for therapeutic treatment of acute and chronic inflammatory disorders. It is essential to identify mPGES-1 inhibitors with novel scaffolds as new leads or hits for the purpose of drug design and discovery that aim to develop the next-generation anti-inflammatory drugs. Herein we report novel mPGES-1 inhibitors identified through a combination of large-scale structure-based virtual screening, flexible docking, molecular dynamics simulations, binding free energy calculations, and in vitro assays on the actual inhibitory activity of the computationally selected compounds. The computational studies are based on our recently developed three-dimensional (3D) structural model of mPGES-1 in its open state. The combined computational and experimental studies have led to identification of new mPGES-1 inhibitors with new scaffolds. In particular, (Z)-5-benzylidene-2-iminothiazolidin-4-one is a promising novel scaffold for the further rational design and discovery of new mPGES-1 inhibitors. To our best knowledge, this is the first time a 3D structural model of the open state mPGES-1 is used in structure-based virtual screening of a large library of available compounds for the mPGES-1 inhibitor identification. The positive experimental results suggest that our recently modeled trimeric structure of mPGES-1 in its open state is ready for the structure-based drug design and discovery.

Original languageEnglish
Pages (from-to)6077-6086
Number of pages10
JournalBioorganic and Medicinal Chemistry
Volume19
Issue number20
DOIs
StatePublished - Oct 15 2011

Bibliographical note

Funding Information:
This work was supported in part by the NIH (Grant RC1MH088480 to C.-G. Zhan). The authors also acknowledge the Center for Computational Sciences (CCS) at University of Kentucky for supercomputing time on IBM X-series Cluster with 340 nodes or 1360 processors and a Dell Supercomputer Cluster consisting of 388 nodes or 4816 processors.

Keywords

  • Anti-inflammatory drug
  • Structure-based drug design

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Medicine
  • Molecular Biology
  • Pharmaceutical Science
  • Drug Discovery
  • Clinical Biochemistry
  • Organic Chemistry

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