Michael Hoopmann (Co-Chair) - Institute for Systems Biology, Seattle, WA
Pratik Jagtap (Co-Chair) - University of Minnesota, Minneapolis, MN
Viktoria Dorfer - University of Applied Sciences, Upper Austria (FH OOE), Hagenberg, Austria
Melanie Föll - University Medical Center Freiburg, Germany
Magnus Palmblad - Leiden University Medical Center, The Netherlands
Yasset Perez-Riverol - European Bioinformatics Institute, Hinxton, UK
Susan T. Weintraub (EB Liaison) - University of Texas Health Science Center at San Antonio
iPRG-2023 Proteome Informatics Research Group Study on Crosslinking
MS Data Analysis
Study Overview
Crosslinking MS is performed to infer interaction sites between proteins and structural restraints from individual proteins in purified or enriched protein complexes, or the full complement of proteins in a cellular lysate. For most experiments, proteins are chemically crosslinked, enzymatically digested, and analyzed by data-dependent acquisition on a high-performance mass spectrometer. Protein structure restraints and interactions are inferred by the identification of two distinct peptide sequences crosslinked in a tandem mass spectrum derived from a single precursor ion. Although crosslinked peptide analysis is fundamentally the same as typical data-dependent MS peptide analysis, processing pipelines for crosslinked peptide data often require specialized algorithms with parameters and constraints that differ from the more familiar ones employed for traditional protein identification/characterization.
Study Goals
The goal of this study is to gain information from the proteomics community about the different approaches for crosslinked peptide MS data analysis, showcasing the multitude of different pipelines and tools available, and providing guidance for improving the presentation of crosslinked MS results.
Study Participation
This study is open to everyone. Prior expertise is not required, and tutorials are provided to teach participants new to crosslinking MS. Participants are asked to use one or more database search methods to identify crosslinked residues of protein complexes from data-dependent mass spectrometry data. Two datasets of different protein complexes are provided for which the participants must identify a) the proteins that are crosslinked to each other, b) the specific residues that are crosslinked, and c) the certainty or confidence (e.g., probabilities or q-values) of their conclusions. Details are provided in the study package.
Study Package and Results Submission
The Study Package is available on https://osf.io/ycvw7
To submit results, contact [email protected] to receive access to a private submission portal.
Participants are welcome to submit up to three sets of results for the study. Each submission will be assigned an identifier and private results submission portal. We ask that contact information be provided in case the study committee has follow-up questions. Although results submission is not anonymous, all results will be reported anonymously. Participants may update their submissions via the submission portal at any time until the submission deadline. Results will be final on January 15, 2024.
Important note to corporate partners and commercial laboratories: ABRF imposes strict guidelines on the use of study results for marketing purposes. These guidelines are described in https://abrf.memberclicks.net/assets/docs/research_group_study_participation_guidelines_2010.pdf
Important Dates
November 27, 2023: Study commences
January 15, 2024: Deadline for results submission
April 21, 2024: Results presentation at the ABRF 2024 Annual Meeting
Questions and Additional Information
Please send questions to [email protected]. Follow this link to obtain a copy of the complete announcement letter for the iPRG-2023 Proteome Informatics Research Group Study on Crosslinking MS Data Analysis.
Proteomics Cloud Computing Workshops - September - November 2022
