title: Latent hit series hidden in high-throughput screening data.
abstract: Recently a novel method termed compound set enrichment (CSE) has been described that uses the activity distribution of a structural class of compounds to identify hit series from primary screening data. This report describes how this method can be used to identify such hit series, even when no hits according to conventional hit-calling methods for a given structural class are present in the data set. Such series, which were called latent hit series, were identified prospectively in a cell-based screening campaign and also in a series of retrospective analyses of publicly available data sets from PubChem. The assay used for the prospective case study was developed to identify compounds modulating protein translation directed from the internal ribosome entry site (IRES) of the encephalomyocarditis virus (EMCV) genomic RNA. The assay was designed with the ability to detect two assay readouts. The first assay readout monitors compound effects on IRES-directed translation, and the second readout monitors the cell viability and general effect on protein expression. By applying CSE separately to both of them, six validated latent hit series with apparently no effects on cell viability were identified. For each of these series, further testing of new compounds enabled identification of additional hits, also apparently with no effect on cell viability. These validated latent hit series would have been missed by a conventional cutoff-based hit-calling approach. This prospective study further supports CSE as a method for the analysis of high-throughput screening experiments.
authors.affiliation: Novartis Institutes for BioMedical Research, Forum 1, Novartis Campus, CH-4056 Basel, Switzerland. thibault.varin@novartis.com
authors.forename: Thibault
authors.initials: T
authors.lastname: Varin
authors.forename: Marie-Cecile
authors.initials: MC
authors.lastname: Didiot
authors.forename: Christian N
authors.initials: CN
authors.lastname: Parker
authors.forename: Ansgar
authors.initials: A
authors.lastname: Schuffenhauer
mesh_terms: D045744:Cell Line, Tumor; D002470:Cell Survival / Q000187:drug effects; D016208:Databases, Factual; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D004686:Encephalomyocarditis virus / Q000235:genetics; D017930:Genes, Reporter; D057166:High-Throughput Screening Assays; D006801:Humans; D049409:Luciferases, Firefly / Q000096:biosynthesis / Q000235:genetics; D014176:Protein Biosynthesis / Q000187:drug effects; D021281:Quantitative Structure-Activity Relationship; D012367:RNA, Viral / Q000235:genetics; D012270:Ribosomes / Q000235:genetics; D053586:Virus Internalization
chemical_list: D012367:RNA, Viral; D049409:Luciferases, Firefly