Nucleic Acids Research · 2010 · 947 citations · 27 references
PharmacyBioinformaticsPharmacologyDrug DesignDrug DiscoveryStructural BioinformaticsComputational Drug DiscoveryDrug DatabasesDrug-target Interaction MappingMolecular DockingPharmacophore MappingPharmacophore-based Lead Discovery3D Pharmacophore MappingDrug-target Interaction DatabasesPharmacophore Feature MappingPharmacophore-based Database SearchingPharmacophore-based Hit IdentificationProtein-ligand Interaction Pharmacophore ModelsReceptor-based Pharmacophore ScreeningStructure-based Pharmacophore Mapping
In silico drug target identification, which converts target discovery into finding optimal interactions between small molecules and available 3D target structures, can also be achieved using pharmacophore mapping as an alternative to docking. PharmMapper is a freely accessible web server that automatically maps query molecules against its PharmTargetDB, a repository of over 7,000 receptor‑based pharmacophore models covering more than 1,500 drug targets, and returns the top‑scoring target candidates with annotated poses. The server’s triangle‑hashing mapping algorithm enables high‑throughput screening in about one hour and successfully identified tamoxifen’s targets within the top 300 candidates in retrospective benchmarking, and it is available at http://59.78.96.61/pharmmapper.
In silico drug target identification, which includes many distinct algorithms for finding disease genes and proteins, is the first step in the drug discovery pipeline. When the 3D structures of the targets are available, the problem of target identification is usually converted to finding the best interaction mode between the potential target candidates and small molecule probes. Pharmacophore, which is the spatial arrangement of features essential for a molecule to interact with a specific target receptor, is an alternative method for achieving this goal apart from molecular docking method. PharmMapper server is a freely accessed web server designed to identify potential target candidates for the given small molecules (drugs, natural products or other newly discovered compounds with unidentified binding targets) using pharmacophore mapping approach. PharmMapper hosts a large, in-house repertoire of pharmacophore database (namely PharmTargetDB) annotated from all the targets information in TargetBank, BindingDB, DrugBank and potential drug target database, including over 7000 receptor-based pharmacophore models (covering over 1500 drug targets information). PharmMapper automatically finds the best mapping poses of the query molecule against all the pharmacophore models in PharmTargetDB and lists the top N best-fitted hits with appropriate target annotations, as well as respective molecule's aligned poses are presented. Benefited from the highly efficient and robust triangle hashing mapping method, PharmMapper bears high throughput ability and only costs 1 h averagely to screen the whole PharmTargetDB. The protocol was successful in finding the proper targets among the top 300 pharmacophore candidates in the retrospective benchmarking test of tamoxifen. PharmMapper is available at http://59.78.96.61/pharmmapper.
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Helen M. Berman · Nucleic Acids Research · 2000 · 39.8K citations
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DrugBank: a knowledgebase for drugs, drug actions and drug targets
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Relating protein pharmacology by ligand chemistry
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