Computationally derived compound profiling matrices

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. Lay abstract: Screening of a given number of small molecules in different assays produces a so-called profiling matrix. This matrix reports for each compound inactivity or activity in all assays. Such profiling matrices are frequently produced in the pharmaceutical industry but rarely disclosed. We have recently reported a computational methodology to derive such matrices from independently conducted biological assays. Herein, we describe three large profiling matrices we have extracted from many experimental screens and made publicly available. These matrices should be helpful to investigators studying the interactions of small molecules with different biological targets. [GRAPHICS] .