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Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro
Published on: September 26, 2025
Energetically optimized pharmacophore modeling to identify dual negative allosteric modulators against group I mGluRs
Sitrarasu Vijaya Prabhu1, Sanjeev Kumar Singh1
1Computer Aided Drug Designing and Molecular Modeling Laboratory, Department of Bioinformatics, Alagappa University, Karaikudi, India.
Abstract:
Glutamate is the key neurotransmitter in human brain that regulates the important functions such as learning, memory and cognition. Abnormal regulation of glutamate leads to various neurodegenerative disorders. To regulate the glutamate signaling pathway we have employed a computational technique called energetically optimized pharmacophore model. We selected four-point pharmacophore (HRRR) based on the glide energy scores and screened the eMolecules database having more than 10 million compounds to find the potential dual negative allosteric modulators for both mGluR1 and mGluR5. The pharmacokinetic properties were calculated to filter out the unwanted molecules. Further, molecular docking, enrichment calculations and molecular dynamics simulations were executed. Finally, the top two compounds (1080734, 22696638) selected from the screened database could be potent dual negative allosteric modulators for the targeted proteins mGluR1 and mGluR5. AbbreviationsCNScentral nervous systemGPCRG-protein coupled receptormGluRmetabotropic glutamate receptorIFDinduced fit dockingPOPCpalmitoyloleoylphosphatidylcholineVFTVenus flytrap domainRMSDroot mean square deviationRMSFroot mean square fluctuation7TMseven transmembraneCommunicated by Ramaswamy H. Sarma.
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