4.7 Article

CIMAGE2.0: An Expanded Tool for Quantitative Analysis of Activity-Based Protein Profiling (ABPP) Data

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 20, Issue 10, Pages 4893-4900

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.1c00455

Keywords

activity-based protein profiling; LC-MS/MS; quantitative proteomics; software

Funding

  1. National Natural Science Foundation of China [21778004, 21925701, 91953109]

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ABPP is a powerful chemical proteomic method for studying protein activity, modifications, and interactions, where accurate quantification is crucial. CIMAGE is a specialized quantification software for ABPP data analysis, providing efficient and accurate quantification with the ability to visualize results conveniently.
Activity-based protein profiling (ABPP) is a powerful chemical proteomic method for studying protein activity, modifications, and interactions in a high-throughput manner. In ABPP experiments, accurate quantification is crucial to determine the extent of probe labeling at the level of either target proteins or specific amino acid side chains. CIMAGE has been developed as an in-house quantification software specifically designed for ABPP data analysis that incorporates (1) a relaxed peak extraction algorithm and (2) stringent post-quantification checks for efficient and accurate quantification. It also can generate table and image data for users to conveniently visualize their results. Here we provide a retrospective introduction of the software and describe our recent upgrade efforts to enable (1) interfacing with different database search engines as input, (2) triplex quantification of ABPP data by reductive dimethylation, and (3) envelope checking for chemical elements with special isotopic distributions. We show that the updated CIMAGE can maintain its ability to quantify ABPP data with dramatic depth and high accuracy, and it also has similar quantification performance in benchmarked SILAC data as compared with MaxQuant. We believe that CIMAGE2.0 will continue to serve as a powerful analytical tool for ABPP studies.

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