GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction

doi:10.1021/acs.analchem.5c02375

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	GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction
	Ren, Yihui 1,2; Bu, Dongbo 1; Duan, Bo 3; Zhang, Chunming 3; Cong, Bin 4; Sun, Shiwei 1
	2025-12-23
发表期刊	ANALYTICAL CHEMISTRY
ISSN	0003-2700
卷号	97 期号:50 页码:27560-27568
摘要	Protein glycosylation is a critical post-translational modification involved in numerous biological processes and disease states. While mass spectrometry has emerged as the primary tool for glycoproteomics analysis, the structural complexity and heterogeneity of glycopeptides pose significant analytical challenges. Existing glycopeptide identification tools primarily rely on mass matching, underutilizing intensity information from mass spectra, which limits their ability to discriminate between similar glycopeptides (glycopeptides bearing analogous glycans/peptide backbones). Here we present GPMassSimulator, an innovative deep learning framework for accurate prediction of intact N-glycopeptide tandem mass spectrometry (MS/MS) spectra and retention time. GPMassSimulator employs the GpepFormer module to effectively represent and integrate both peptide sequences and glycan structures, capturing their complex dependencies. The integrated representation is then passed through the Prediction module to generate the theoretical MS/MS spectra and the retention time of the glycopeptides. Our method demonstrated an outstanding performance on the benchmark set. In the experiment distinguishing similar glycan compositions, GPMassSimulator achieved an identification accuracy of 97.1%. Furthermore, in distinguishing isomeric structures, our method achieved more accurate Top-1 identifications than the current approaches. Additionally, the rescoring experiment on pGlyco3 highlighted the significant improvement in the sensitivity of our model for glycopeptide identification. These excellent results showcased the promising potential of our approach in glycoproteomics.
DOI	10.1021/acs.analchem.5c02375
收录类别	SCI
语种	英语
WOS研究方向	Chemistry
WOS类目	Chemistry, Analytical
WOS记录号	WOS:001634142600001
出版者	AMER CHEMICAL SOC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/42930
专题	中国科学院计算技术研究所
通讯作者	Cong, Bin; Sun, Shiwei
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Western Inst Comp Technol, Chongqing 400000, Peoples R China 4.Hebei Med Univ, Dept Physiol, Shijiazhuang 050017, Hebei, Peoples R China
推荐引用方式 GB/T 7714	Ren, Yihui,Bu, Dongbo,Duan, Bo,et al. GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction[J]. ANALYTICAL CHEMISTRY,2025,97(50):27560-27568.
APA	Ren, Yihui,Bu, Dongbo,Duan, Bo,Zhang, Chunming,Cong, Bin,&Sun, Shiwei.(2025).GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction.ANALYTICAL CHEMISTRY,97(50),27560-27568.
MLA	Ren, Yihui,et al."GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction".ANALYTICAL CHEMISTRY 97.50(2025):27560-27568.