The Multiplicity of Serotonin Receptors: Uselessly Diverse Molecules or an Embarrassment of Riches?

By Bryan L. Roth, E. Lopez, Shamil Patel, W. Kroeze. 2000

360 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Molecular Biology

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Citations in the corpus

ChEMBL: a large-scale bioactivity database for drug discovery (2011, methodology): “PDSP Ki database stores screening data from the National Institute of Mental Health’s Psychoactive Drug Screening Program (13).”
Global mapping of pharmacological space (2006, background): “1 7,849 8 D(4) dopamine receptor Aminergic GPCRs 15.”
STITCH 4: integration of protein–chemical interactions with user data (2013, methodology): “The second channel is made up of manually curated drug–target databases: DrugBank (12), GLIDA (13), Matador (14), TTD (15) and CTD (16); and pathway databases: KEGG (17), NCI/Nature Pathway Interaction Database (18), Reactome (19) and BioCyc (20) .”
A side effect resource to capture phenotypic effects of drugs (2010, methodology): “Other databases, such as DrugBank, the PSDP K i database and BindingDB, contain binding information (Roth et al , 2000; Liu et al , 2007; Wishart et al , 2008).”
Advancing translational research with the Semantic Web (2007, background): “The PDSP Ki Database [65] is a repository of experimental results about receptor-ligand interactions and has a strong emphasis on neuroreceptors.”
GPCRdb in 2018: adding GPCR structure models and ligands (2017, background): “A further resource is the Ki database of the psychoactive drug screening programme containing broad target profiling, however most of which are singlepoint values (12).”
Machine learning approaches and databases for prediction of drug–target interaction: a survey paper (2020, background): “PDSP Ki [301] is a public database that stored binding affinities data of drugs/chemical compounds for four different types of proteins, i.e. receptors, neurotransmitter transporters, ion channels and enzymes.”