MS2PIP prediction server: compute and visualize MS2 peak intensity predictions for CID and HCD fragmentation

被引:53
|
作者
Degroeve, Sven [1 ,2 ]
Maddelein, Davy [1 ,2 ]
Martens, Lennart [1 ,2 ]
机构
[1] Univ Ghent VIB, Dept Med Prot Res, B-9000 Ghent, Belgium
[2] Univ Ghent, Fac Med & Hlth Sci, Dept Biochem, B-9000 Ghent, Belgium
关键词
MASS-SPECTROMETRY; DISSOCIATION; PROTEOMICS; PEPTIDES; SPECTRA; LIBRARY;
D O I
10.1093/nar/gkv542
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
We present an MS2 peak intensity prediction server that computes MS2 charge 2+ and 3+ spectra from peptide sequences for the most common fragment ions. The server integrates the Unimod public domain post-translational modification database for modified peptides. The prediction model is an improvement of the previously published (MSPIP)-P-2 model for Orbitrap-LTQ CID spectra. Predicted MS2 spectra can be downloaded as a spectrum file and can be visualized in the browser for comparisons with observations. In addition, we added prediction models for HCD fragmentation (Q-Exactive Orbitrap) and show that these models compute accurate intensity predictions on par with CID performance. We also show that training prediction models for CID and HCD separately improves the accuracy for each fragmentation method.
引用
收藏
页码:W326 / W330
页数:5
相关论文
共 15 条
  • [1] MS2PIP: a tool for MS/MS peak intensity prediction
    Degroeve, Sven
    Martens, Lennart
    [J]. BIOINFORMATICS, 2013, 29 (24) : 3199 - 3203
  • [2] Updated MS2PIP web server delivers fast and accurate MS2 peak intensity prediction for multiple fragmentation methods, instruments and labeling techniques
    Gabriels, Ralf
    Martens, Lennart
    Degroeve, Sven
    [J]. NUCLEIC ACIDS RESEARCH, 2019, 47 (W1) : W295 - W299
  • [3] Updated MS2PIP web server supports cutting-edge proteomics applications
    Declercq, Arthur
    Bouwmeester, Robbin
    Chiva, Cristina
    Sabido, Eduard
    Hirschler, Aurelie
    Carapito, Christine
    Martens, Lennart
    Degroeve, Sven
    Gabriels, Ralf
    [J]. NUCLEIC ACIDS RESEARCH, 2023, 51 (W1) : W338 - W342
  • [4] Thunder-DDA-PASEF enables high-coverage immunopeptidomics and is boosted by MS2Rescore with MS2PIP timsTOF fragmentation prediction model
    Gomez-Zepeda, David
    Arnold-Schild, Danielle
    Beyrle, Julian
    Declercq, Arthur
    Gabriels, Ralf
    Kumm, Elena
    Preikschat, Annica
    Lacki, Mateusz Krzysztof
    Hirschler, Aurelie
    Rijal, Jeewan Babu
    Carapito, Christine
    Martens, Lennart
    Distler, Ute
    Schild, Hansjoerg
    Tenzer, Stefan
    [J]. NATURE COMMUNICATIONS, 2024, 15 (01)
  • [5] Prosit Transformer: A transformer for Prediction of MS2 Spectrum Intensities
    Ekvall, Markus
    Truong, Patrick
    Gabriel, Wassim
    Wilhelm, Mathias
    Kall, Lukas
    [J]. JOURNAL OF PROTEOME RESEARCH, 2022, 21 (05) : 1359 - 1364
  • [6] Distinctive and Complementary MS2 Fragmentation Characteristics for Identification of Sulfated Sialylated N-Glycopeptides by nanoLC-MS/MS Workflow
    [J]. Khoo, Kay-Hooi (kkhoo@gate.sinica.edu.tw), 1600, Springer Science and Business Media, LLC (29):
  • [7] Distinctive and Complementary MS2 Fragmentation Characteristics for Identification of Sulfated Sialylated N-Glycopeptides by nanoLC-MS/MS Workflow
    Kuo, Chu-Wei
    Guu, Shih-Yun
    Khoo, Kay-Hooi
    [J]. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY, 2018, 29 (06) : 1166 - 1178
  • [8] Application of ESI/MS, CID/MS and tandem MS/MS to the fragmentation study of eriodictyol 7-O-glucosyl-(1→2)-glucoside and luteolin 7-O-glucosyl-(1→2)-glucoside
    Es-Safi, NE
    Kerhoas, L
    Einhorn, J
    Ducrot, PH
    [J]. INTERNATIONAL JOURNAL OF MASS SPECTROMETRY, 2005, 247 (1-3) : 93 - 100
  • [9] Comparing Targeted vs. Untargeted MS2 Data-Dependent Acquisition for Peak Annotation in LC-MS Metabolomics
    Ten-Domenech, Isabel
    Martinez-Sena, Teresa
    Moreno-Torres, Marta
    Daniel Sanjuan-Herraez, Juan
    Castell, Jose, V
    Parra-Llorca, Anna
    Vento, Maximo
    Quintas, Guillermo
    Kuligowski, Julia
    [J]. METABOLITES, 2020, 10 (04)
  • [10] PhosphoScan: A probability-based method for phosphorylation site prediction using MS2/MS3 pair information
    Wan, Yunhu
    Cripps, Diane
    Thomas, Stefani
    Campbell, Patricia
    Ambulos, Nicholas
    Chen, Ting
    Yang, Austin
    [J]. JOURNAL OF PROTEOME RESEARCH, 2008, 7 (07) : 2803 - 2811