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Canna~Fangled Abstracts

Docking based virtual screening and molecular dynamics study to identify potential monoacylglycerol lipase inhibitors

By June 19, 2014No Comments
 2014 Jun 19. pii: S0960-894X(14)00657-X. doi: 10.1016/j.bmcl.2014.06.029. [Epub ahead of print]

pm1Docking based virtual screening and molecular dynamics study to identify potential monoacylglycerol lipase inhibitors.

Afzal O1, Kumar S1, Kumar R1, Firoz A2, Jaggi M3, Bawa S4.

Author information 

Abstract

Monoacylglycerol lipase (MAGL) is one of the key enzymes of the endocannabinoid system (ECS). It hydrolyzes one of the major endocannabinoid, 2-arachidonoylglycerol (2-AG), an endogenous full agonist at G protein coupled cannabinoid receptors CB1 and CB2. Numerous studies showed that MGL inhibitors are potentially useful for the treatment of pain, inflammation, cancer and CNS disorders. These provocative findings suggested that pharmacological inhibition of MAGL function may confer significant therapeutic benefits. In this study, we presented hybrid ligand and structure-based approaches to obtain a novel set of virtual leads as MAGL inhibitors. The constraints used in this study, were Glide score, binding free energy estimates and ADME properties to screen the ZINC database, containing approximately 21 million compounds. A total of seven virtual hits were obtained, which showed significant binding affinity towards MAGL protein. Ligand, ZINC24092691 was employed in complex form with the protein MAGL, for molecular dynamics simulation study, because of its excellent glide score, binding free energy and ADME properties. The RMSD of ZINC24092691 was observed to stay at 0.1nm (1Å) in most of the trajectories, which further confirmed its ability to inhibit the protein MAGL. The hits were then evaluated for their ability to inhibit human MAGL. The compound ZINC24092691 displayed the noteworthy inhibitory activity reducing MAGL activity to 21.15% at 100nM concentration, with an IC50 value of 10nM.
Copyright © 2014 Elsevier Ltd. All rights reserved.

KEYWORDS: 

Binding free energy estimates; E-Pharmacophore mapping; MAGL inhibition assay; Molecular docking; Molecular dynamics simulation; Monoacylglycerol lipase; Virtual screening

PMID:

 25011912
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