Resumen
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.
| Idioma original | English |
|---|---|
| Páginas (desde-hasta) | 6077-6086 |
| Número de páginas | 10 |
| Publicación | Bioorganic and Medicinal Chemistry |
| Volumen | 19 |
| N.º | 20 |
| DOI | |
| Estado | Published - oct 15 2011 |
Nota bibliográfica
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.
Financiación
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.
| Financiadores | Número del financiador |
|---|---|
| National Institutes of Health (NIH) | |
| National Institute of Mental Health | RC1MH088480 |
ASJC Scopus subject areas
- Biochemistry
- Molecular Medicine
- Molecular Biology
- Pharmaceutical Science
- Drug Discovery
- Clinical Biochemistry
- Organic Chemistry
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