Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Monitoring Functional Post-Translational Modifications Using a Data-Driven Proteome Informatic Pipeline Based on PEIMAN2

Payman Nickchi, View ORCID ProfileMehdi Mirzaie, View ORCID ProfileMarc Baumann, View ORCID ProfileAmir Ata Saei, View ORCID ProfileMohieddin Jafari
doi: https://doi.org/10.1101/2022.11.09.515610
Payman Nickchi
1Department of Statistics and Actuarial Science, Simon Fraser University, British Columbia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mehdi Mirzaie
2Department of Pharmacology, Faculty of Medicine & Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
3Medicum, Department of Biochemistry and Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, Helsinki, Finland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mehdi Mirzaie
Marc Baumann
3Medicum, Department of Biochemistry and Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, Helsinki, Finland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Marc Baumann
Amir Ata Saei
4Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-171 65 Stockholm, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Amir Ata Saei
  • For correspondence: amirata.saei.dibavar@ki.se mohieddin.jafari@helsinki.fi
Mohieddin Jafari
3Medicum, Department of Biochemistry and Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, Helsinki, Finland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mohieddin Jafari
  • For correspondence: amirata.saei.dibavar@ki.se mohieddin.jafari@helsinki.fi
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

Post-translational modifications (PTMs) are under significant focus in molecular biomedicine due to their importance in signal transduction in most cellular and organismal processes. Characterization of PTMs, discrimination between functional and inert PTMs, quantification of their occupancies and PTM crosstalk are demanding tasks in each biosystem. On top of that, the study of each PTM often necessitates a particular laborious experimental design. Here, we present a PTM-centric proteome informatic pipeline for prediction of most probable and relevant PTMs in mass spectrometry-based proteomics data. Upon prediction, such PTMs can be incorporated in a refined database search. To demonstrate the applicability of our approach, using expression profiling, we identified cellular proteins that are differentially regulated in response to multikinase inhibitors dasatinib and staurosporine. Computational enrichment analysis was employed to determine the potential PTMs of protein targets for both drugs. Finally, we conducted an additional round of database search with the predicted probable PTMs. Our pipeline helped to analyze the enriched PTMs and even the detected proteins that were not identified in the initial search. Our findings support the idea of PTM-centric searching of MS data in proteomics based on computational enrichment analysis and we believe this strategy should be incorporated in future proteomics search engines.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/jafarilab/PEIMAN2

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted November 09, 2022.
Download PDF

Supplementary Material

Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Monitoring Functional Post-Translational Modifications Using a Data-Driven Proteome Informatic Pipeline Based on PEIMAN2
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Monitoring Functional Post-Translational Modifications Using a Data-Driven Proteome Informatic Pipeline Based on PEIMAN2
Payman Nickchi, Mehdi Mirzaie, Marc Baumann, Amir Ata Saei, Mohieddin Jafari
bioRxiv 2022.11.09.515610; doi: https://doi.org/10.1101/2022.11.09.515610
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Monitoring Functional Post-Translational Modifications Using a Data-Driven Proteome Informatic Pipeline Based on PEIMAN2
Payman Nickchi, Mehdi Mirzaie, Marc Baumann, Amir Ata Saei, Mohieddin Jafari
bioRxiv 2022.11.09.515610; doi: https://doi.org/10.1101/2022.11.09.515610

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Biochemistry
Subject Areas
All Articles
  • Animal Behavior and Cognition (4397)
  • Biochemistry (9629)
  • Bioengineering (7123)
  • Bioinformatics (24937)
  • Biophysics (12670)
  • Cancer Biology (9994)
  • Cell Biology (14400)
  • Clinical Trials (138)
  • Developmental Biology (7989)
  • Ecology (12147)
  • Epidemiology (2067)
  • Evolutionary Biology (16025)
  • Genetics (10951)
  • Genomics (14778)
  • Immunology (9905)
  • Microbiology (23739)
  • Molecular Biology (9506)
  • Neuroscience (51049)
  • Paleontology (370)
  • Pathology (1545)
  • Pharmacology and Toxicology (2692)
  • Physiology (4038)
  • Plant Biology (8693)
  • Scientific Communication and Education (1512)
  • Synthetic Biology (2404)
  • Systems Biology (6458)
  • Zoology (1350)