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Detailed and systematic understanding of the biological effects of millionsof available compounds on living cells is a significant challenge. As mostcompounds impact multiple targets and pathways, traditional methods foranalyzing structure-function relationships are not comprehensive enough.Therefore more advanced integrative models are needed for predicting biologicaleffects elicited by specific chemical features. As a step towards creating suchcomputational links we developed a data-driven chemical systems biologyapproach to comprehensively study the relationship of 76 structural3D-descriptors (VolSurf, chemical space) of 1159 drugs with the gene expressionresponses (biological space) they elicited in three cancer cell lines. Theanalysis covering 11350 genes was based on data from the Connectivity Map. Wedecomposed these biological response profiles into components, each linked to acharacteristic chemical descriptor profile. The integrated quantitativeanalysis of the chemical and biological spaces was more informative aboutprotein-target based drug similarity than either dataset separately. Weidentified ten major components that link distinct VolSurf features acrossmultiple compounds to specific biological activity types. For example,component 2 (hydrophobic properties) strongly links to DNA damage response,while component 3 (hydrogen bonding) connects to metabolic stress. Individualstructural and biological features were often linked to one cell line only,such as leukemia cells (HL-60) specifically responding to cardiac glycosides.In summary, our approach identified specific chemical structures shared acrossmultiple drugs causing distinct biological responses. The decoding of suchsystematic chemical-biological relationships is necessary to build bettermodels of drug effects, including unidentified types of molecular propertieswith strong biological effects.

Comprehensive data-driven analysis of the impact of chemoinformatic  structure on the genome-wide biological response profiles of cancer cells to  1159 drugs