A Machine Learning-based Chemoproteomic Approach to Identify Drug Targets and Binding Sites in Complex Proteomes

Piazza I, Beaton N, Bruderer R, Knobloch T, Barbisan C, Chandat L, Sudau A, Siepe I, Rinner O, de Souza N, Picotti P, Reiter L. Nature Communications.

Chemoproteomics enables protein target identification of bioactive compounds, unraveling the mode of action of drugs. In this joint effort with Prof. Picotti’s group, ETH Zurich, we presented a novel chemoproteomic workflow combining LiP and machine learning-based data analysis. This next-generation proteomics approach enables the identification of small molecule drug targets in complex proteomes and the analysis of their binding properties across species and drug target classes.

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