Chemogenomics data sets play a central role in current drug discovery endeavors including polypharmacology and drug repurposing projects. In this work, we present a general method to systematically analyzing the structure-activity relationships of a large screening profile data with emphasis on identifying structural changes that have a significant impact on the number of proteins to which a compound binds. At the core of this approach is the Structure-Promiscuity Index Difference (SPID) metric that captures differences in the number of proteins bound related to changes in molecular structure. The SPID measure is inspired by the Structure-Activity Landscape Index (SALI) measure commonly used in activity landscape modeling. We discuss applications of this approach to mine a public data set of more than 15,000 compounds from different sources screened across 100 sequence-unrelated proteins.

Navigation through chemogenomics data with SPID

245th National Meeting (2013)

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