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Development of large-scale cross-linking mass spectrometry

Barysz, Helena Maria LU and Malmstroem, Johan LU (2017) In Molecular and Cellular Proteomics
Abstract

Cross-linking mass spectrometry (CLMS) provides distance constraints to study the structure of proteins, multiprotein complexes and protein-protein interactions which are critical for the understanding of protein function. CLMS is an attractive technology to bridge the gap between high-resolution structural biology techniques and proteomic-based interactome studies. However, as outlined in this review there are still several bottlenecks associated with CLMS which limit its application on a proteome-wide level. Specifically, there is an unmet need for comprehensive software that can reliably identify cross-linked peptides from large datasets. In this review we provide supporting information to reason that targeted proteomics of... (More)

Cross-linking mass spectrometry (CLMS) provides distance constraints to study the structure of proteins, multiprotein complexes and protein-protein interactions which are critical for the understanding of protein function. CLMS is an attractive technology to bridge the gap between high-resolution structural biology techniques and proteomic-based interactome studies. However, as outlined in this review there are still several bottlenecks associated with CLMS which limit its application on a proteome-wide level. Specifically, there is an unmet need for comprehensive software that can reliably identify cross-linked peptides from large datasets. In this review we provide supporting information to reason that targeted proteomics of cross-links may provide the required sensitivity to reliably detect and quantify cross-linked peptides and that a reporter ion signature for cross-linked peptides may become a useful approach to increase confidence in the identification process of cross-linked peptides. In addition, the review summarizes the recent advances in CLMS workflows using the analysis of condensin complex in intact chromosomes as a model complex.

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organization
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Contribution to journal
publication status
epub
subject
in
Molecular and Cellular Proteomics
publisher
American Society for Biochemistry and Molecular Biology
ISSN
1535-9484
DOI
10.1074/mcp.R116.061663
language
English
LU publication?
yes
id
1863652d-a7b2-455b-865f-da33444d36c1
date added to LUP
2017-09-04 17:26:37
date last changed
2017-09-05 11:14:05
@article{1863652d-a7b2-455b-865f-da33444d36c1,
  abstract     = {<p>Cross-linking mass spectrometry (CLMS) provides distance constraints to study the structure of proteins, multiprotein complexes and protein-protein interactions which are critical for the understanding of protein function. CLMS is an attractive technology to bridge the gap between high-resolution structural biology techniques and proteomic-based interactome studies. However, as outlined in this review there are still several bottlenecks associated with CLMS which limit its application on a proteome-wide level. Specifically, there is an unmet need for comprehensive software that can reliably identify cross-linked peptides from large datasets. In this review we provide supporting information to reason that targeted proteomics of cross-links may provide the required sensitivity to reliably detect and quantify cross-linked peptides and that a reporter ion signature for cross-linked peptides may become a useful approach to increase confidence in the identification process of cross-linked peptides. In addition, the review summarizes the recent advances in CLMS workflows using the analysis of condensin complex in intact chromosomes as a model complex.</p>},
  author       = {Barysz, Helena Maria and Malmstroem, Johan},
  issn         = {1535-9484},
  language     = {eng},
  month        = {04},
  publisher    = {American Society for Biochemistry and Molecular Biology},
  series       = {Molecular and Cellular Proteomics},
  title        = {Development of large-scale cross-linking mass spectrometry},
  url          = {http://dx.doi.org/10.1074/mcp.R116.061663},
  year         = {2017},
}