Connell William, Garcia Kristle, Goodarzi Hani, Keiser Michael J
Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA.
Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA.
bioRxiv. 2023 Aug 28:2023.08.26.554851. doi: 10.1101/2023.08.26.554851.
Chemical probes interrogate disease mechanisms at the molecular level by linking genetic changes to observable traits. However, comprehensive chemical screens in diverse biological models are impractical. To address this challenge, we developed ChemProbe, a model that predicts cellular sensitivity to hundreds of molecular probes and drugs by learning to combine transcriptomes and chemical structures. Using ChemProbe, we inferred the chemical sensitivity of cancer cell lines and tumor samples and analyzed how the model makes predictions. We retrospectively evaluated drug response predictions for precision breast cancer treatment and prospectively validated chemical sensitivity predictions in new cellular models, including a genetically modified cell line. Our model interpretation analysis identified transcriptome features reflecting compound targets and protein network modules, identifying genes that drive ferroptosis. ChemProbe is an interpretable screening tool that allows researchers to measure cellular response to diverse compounds, facilitating research into molecular mechanisms of chemical sensitivity.
