ProTargetMiner as a proteome signature library of anticancer molecules for functional discovery

Area of Science:

• Proteomics
• Chemical Biology
• Drug Discovery

Background:

• Understanding anticancer compound targets and mechanisms is crucial for effective drug development.
• Existing resources often lack comprehensive proteomic data linking compounds to their cellular targets.

Purpose of the Study:

• To introduce ProTargetMiner, a publicly accessible, expandable proteome signature library for anticancer molecules.
• To provide a platform for deconvoluting drug targets and action mechanisms in cancer cell lines.

Main Methods:

• Utilized proteomic data from 287 A549 adenocarcinoma cell line samples treated with 56 compounds.
• Developed a dataset of 7,328 proteins and 1,307,859 protein-drug pairs.
• Employed partial least square modeling for target and mechanism deconvolution.

Main Results:

• Proteomic signatures clustered by compound targets and mechanisms.
• Deep proteome datasets were generated for 9 diverse anticancer molecules across MCF-7, RKO, and A549 cell lines.
• Analysis revealed common drug targets and cell-specific differences when combining data from multiple cell lines.

Conclusions:

• ProTargetMiner serves as a valuable chemical proteomics resource for the cancer research community.
• The database facilitates the identification of drug targets and mechanisms, supporting drug discovery efforts.
• The expandable nature of ProTargetMiner allows for integration of new compound signatures.