Evaluating DIA LiP-MS Analysis Workflows with a Hybrid LiP Proteome Benchmark

Area of Science:

• Structural proteomics
• Mass spectrometry
• Proteomics informatics

Background:

• Limited proteolysis mass spectrometry (LiP-MS) is a key technique for studying protein structure.
• LiP-MS data analysis presents unique challenges due to peptide complexity and lack of standardized statistical methods.
• Existing informatics workflows require evaluation for accurate analysis of DIA-based LiP-MS data.

Purpose of the Study:

• To develop and validate an informatics pipeline for quantitative analysis of DIA-based LiP-MS data.
• To establish a benchmark dataset for evaluating LiP-MS data analysis workflows.
• To enhance the detection of protein structural alterations and drug-target interactions.

Main Methods:

• Generation of a high-quality benchmark dataset of over 170,000 LiP peptides.
• Comprehensive assessment of major DIA analysis platforms using spectral libraries.
• Development and implementation of the DIA-LiPQuan informatics pipeline.

Main Results:

• DIA-LiPQuan demonstrates sensitive and robust detection of protein structural remodeling.
• The pipeline accurately identifies drug-bound protein targets within the cellular proteome.
• The benchmark dataset facilitates comparison and validation of LiP-MS analysis methods.

Conclusions:

• The DIA-LiPQuan pipeline offers a tailored solution for DIA LiP-MS quantification and analysis.
• This study provides a valuable resource for advancing structural proteomics and drug discovery.
• The developed informatics package supports broader applications of LiP-MS in biological research.