Evidence map›Paper›PMID 25840810›Full record

ArticleJournal of the American Society for Mass Spectrometry2015

Photocross-Linked Peptide-Protein Complexes Analysis: A Comparative Study of CID and ETD Fragmentation Modes.

Séverine Clavier, Gérard Bolbach, Emmanuelle Sachon

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Séverine ClavierSorbonne Université, UPMC-Univ Paris 6, Ecole Normale Supérieure, PSL Research university, Département de chimie, CNRS, UMR7203 Laboratoire des BioMolécules, 4 place Jussieu, 75252, Paris, Cedex 05, France.
Gérard Bolbach
Emmanuelle Sachon

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein-protein interactions are among the keys to organizing cellular processes in space and time. One of the only direct ways to identify such interactions in their cellular environment is to covalently bond the interacting partners to fix the interaction. Photocross-linking in living cells is thus a very promising technique. The feasibility of in cellulo photocross-linking reactions has been shown and mass spectrometry is a tool of choice to analyze photocross-linked proteins. However, the interpretation of the MS and MS/MS spectra of photocross-linked peptides remains one of the most important bottlenecks of the method and still limits its potential for large-scale applications (interactomics). Fundamental studies are still necessary to understand and characterize the fragmentation behavior of photocross-linked peptides. Here, we report the successful identification of the interaction sites in a well-characterized model of in vitro interaction between a protein and a peptide. We describe in detail the fragmentation pattern of these photocross-linked species in order to identify trends that could be generalized. In particular, we compare CID and ETD fragmentation modes (and HCD in a lesser extent), demonstrating the complementarity of both methods and the advantage of ETD for the analysis of photocross-linked species. The information should help further development of dedicated software to properly score MS/MS spectra of photocross-linked species.

Indexed as

Amino Acid SequenceMolecular Sequence DataPeptidesSerum Albumin, BovineSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTandem Mass SpectrometryUltraviolet RaysPeptidesSerum Albumin, Bovine

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.