1
Return

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

delete2026-07-16
delete0
PRE
AI
S
Shanshan Li *
S
Shijia Yuan
H
Huiting Luo
J
Jingyi Xu
Z
Zhaoyu Zhang
R
Ronghui Lou
H
Hebin Liu
C
Chengpin Shen
W
Wenqing Shui *
DOI:10.1021/acs.analchem.6c02411delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Emerging as a powerful structural proteomics approach, limited proteolysis mass spectrometry (LiP-MS) has been widely employed to interrogate proteome-wide protein structural alterations, identify drug targets and drug-binding pockets, and probe protein–protein interactions. However, LiP-MS-based proteomics data analysis is fundamentally different from that of conventional proteomics informatics. LiP-MS relies on peptide-centric analysis in order to pinpoint structural regions or residues within a protein that exhibit conformational changes. The presence of a large number of semitryptic peptides substantially increases LiP-MS data complexity. Moreover, there is a lack of consensus on the statistical criteria for defining structural changes. To evaluate informatics workflows for DIA-based LiP-MS, we generated a high-quality benchmark data set comprising more than 170,000 LiP peptides with defined composition. We then performed a comprehensive assessment of major DIA analysis platforms incorporating different spectral libraries, and introduced DIA-LiPQuan, an informatics pipeline tailored to DIA LiP-MS quantification and downstream analysis. Data reanalysis by DIA-LiPQuan with in silico libraries allows sensitive and robust detection of both site-specific structural remodeling of proteins and drug-bound protein targets from the cellular proteome. Collectively, our study provides a valuable benchmark resource and informatics package for LiP-MS data mining, which would facilitate its broader applications in structural proteomics and drug discovery.
Keywords:
Mass spectrometry
Peptide identification
Peptides and proteins
Protein identification
Proteomics

Journal

Analytical Chemistry cover
Analytical Chemistry
IF:
6.7
Papers:
4.7W
Citations:
15.9W

Organization

S
shanghai omicsolution co., ltd
Scholars:
3
Papers: 1
Citations: 0
S
ShanghaiTech University
Scholars:
9.4K
Papers: 5.8K
Citations: 1.6W
Cited Papers

Cited Papers

Citing Papers

Citing Papers