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RESEARCH PRODUCT
Dynamic-shared Pharmacophore Approach as Tool to Design New Allosteric PRC2 Inhibitors, Targeting EED Binding Pocket.
Alessandro PadovaUgo PerriconePatrizia DianaBarbara ParrinoJessica LombinoDaniela CarboneMaría RosaMaria Rita GulottaGiada De SimoneStella CascioferroNedra Meknisubject
Computer scienceAllosteric regulationBinding pocketmacromolecular substancesComputational biologyMolecular Dynamics SimulationLigands01 natural sciences03 medical and health sciencesProtein structureStructural BiologyDrug DiscoveryHumans030304 developmental biologyEED0303 health sciencesVirtual screeningBinding SitesbiologyOrganic ChemistryMolecular DynamicPolycomb Repressive Complex 2Dynamic pharmacophorePRC20104 chemical sciencesComputer Science ApplicationsChromatinMolecular Docking Simulation010404 medicinal & biomolecular chemistryROC CurveDocking (molecular)Drug Designbiology.proteinMolecular MedicinePharmacophorePRC2Allosteric SiteProtein Bindingdescription
Abstract: The Polycomb Repressive complex 2 (PRC2) maintains a repressive chromatin state and silences many genes, acting as methylase on histone tails. This enzyme was found overexpressed in many types of cancer. In this work, we have set up a Computer-Aided Drug Design approach based on the allosteric modulation of PRC2. In order to minimize the possible bias derived from using a single set of coordinates within the protein-ligand complex, a dynamic workflow was developed. In details, molecular dynamic was used as tool to identify the most significant ligand-protein interactions from several crystallized protein structures. The identified features were used for the creation of dynamic pharmacophore models and docking grid constraints for the design of new PRC2 allosteric modulators. Our protocol was retrospectively validated using a dataset of active and inactive compounds, and the results were compared to the classic approaches, through ROC curves and enrichment factor. Our approach suggested some important interaction features to be adopted for virtual screening performance improvement
year | journal | country | edition | language |
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2020-06-15 | Molecular informaticsReferences |