GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction
文献类型：期刊论文
| 作者 | Ren, Yihui2,3; Bu, Dongbo2; Duan, Bo1; Zhang, Chunming1; Cong, Bin4; Sun, Shiwei2 |
| 刊名 | ANALYTICAL CHEMISTRY
 |
| 出版日期 | 2025-12-23 |
| 卷号 | 97期号:50页码:27560-27568 |
| ISSN号 | 0003-2700 |
| DOI | 10.1021/acs.analchem.5c02375 |
| 英文摘要 | 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. |
| 资助项目 | National Natural Science Foundation of China[32271297] ; National Key Research and Development Program of China[2020YFA0907000] |
| WOS研究方向 | Chemistry |
| 语种 | 英语 |
| WOS记录号 | WOS:001634142600001 |
| 出版者 | AMER CHEMICAL SOC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/42929]  |
| 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.Western Inst Comp Technol, Chongqing 400000, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, 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. |
入库方式： OAI收割
来源：计算技术研究所
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