Computationally derived compound profiling matrices

Abstract

Aim: Screening of compounds against panels of targets yields profiling matrices. Such matrices are excellent test cases for the analysis and prediction of ligand-target interactions. We made three matrices freely available that were extracted from public screening data. Methodology: A new algorithm was used to derive complete profiling matrices from assay data. Data: Two profiling matrices were derived from confirmatory assays containing 53 different targets and 109,925 and 143,310 distinct compounds, respectively. A third matrix was extracted from primary screening assays covering 171 different targets and 224,251 compounds. Next steps: Profiling matrices can be used to test computational chemogenomics methods for their ability to predict ligand-target pairs. Additional matrices will be generated for individual target families.