Ceratamine B

Drug screening technologies are experimental and computational strategies used to identify small molecules or chemical probes that modulate a defined molecular target, signaling pathway, cellular phenotype, disease model, or patient-derived response profile. High-throughput screening tests many compounds in miniaturized assay formats, while quantitative high-throughput screening tests compounds across concentration ranges so that potency and efficacy can be inferred from concentration-response behavior rather than from a single-point signal. The core biological function of a drug-screening strategy is to connect compound exposure with measurable pathway activity, target modulation, cell-state change, viability, cytotoxicity, morphology, or disease-relevant phenotype. Assay performance must be evaluated before screening because hit identification depends on the separation between positive and negative controls, control variability, plate effects, outliers, and the statistical framework

Compound databases support drug-discovery research by organizing chemical structures, identifiers, bioactivity values, targets, annotations, purchasability, and literature-derived evidence into searchable resources for virtual screening, target prediction, repurposing, and hit prioritization. General chemical databases such as PubChem, ChEMBL, DrugBank, BindingDB, and ZINC differ in scope: PubChem emphasizes broad chemical and assay data, ChEMBL and BindingDB emphasize bioactivity and target relationships, DrugBank emphasizes approved and investigational drugs, and ZINC emphasizes purchasable docking-ready compounds. Natural-product and traditional-medicine databases add species source, phytochemical, and ethnopharmacology information, but reviews show that database accessibility, redundancy, inconsistent structure annotation, and uneven curation remain major limitations. Unresolved questions include how to harmonize identifiers across databases, how to remove duplicate or erroneous st