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Photo-Induced Cross-Linking of Unmodified Proteins PICUP Applied to Amyloidogenic Peptides
Published on: January 12, 2009
Identification of Cross-linked Peptides Using Isotopomeric Cross-linkers
Jie Luo1, Jacob Bassett1, Jeff Ranish2
1Institute for Systems Biology, 401 Terry Ave North, Seattle, WA, 98109, USA.
Isotopomeric cross-linkers (ICLs) enable confident identification of cross-linked peptides in complex mixtures. This novel chemical cross-linking mass spectrometry (CL-MS) approach uses unique isotopic patterns for reliable protein interaction mapping.
Area of Science:
- Biochemistry
- Proteomics
- Chemical Biology
Background:
- Chemical cross-linking combined with mass spectrometry (CL-MS) is vital for protein assembly and interaction studies.
- Identifying cross-linked peptides in complex samples remains a significant challenge.
- MS cleavable cross-linkers improve identification reliability through database searching.
Purpose of the Study:
- Introduce a novel class of MS cleavable cross-linkers: isotopomeric cross-linkers (ICLs).
- Enable confident and efficient identification of cross-linked peptides via whole proteome database searching.
- Present the ICL-MS method for protein interaction analysis.
Main Methods:
- Developed isotopomeric cross-linkers (ICLs) with asymmetric heavy/light isotope incorporation.
- ICLs generate pairs of isotopomeric cross-linked peptides.
- Utilized unique isotopic doublet ions from MS/MS fragmentation for peptide identification and mass determination.
Main Results:
- ICLs facilitate confident identification of cross-linked peptides by generating distinct isotopic doublet ions.
- The ICL-MS workflow allows determination of cross-linked peptide masses from a single MS2 spectrum.
- Demonstrated ICL-MS performance in increasingly complex mixtures using whole proteome database searching.
Conclusions:
- ICLs represent a significant advancement in CL-MS for reliable protein interaction mapping.
- The ICL-MS method enhances the efficiency and confidence of cross-linked peptide identification.
- This approach is particularly valuable for analyzing complex biological samples.
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