| Autor: |
Juan D Chavez, Jimmy K Eng, Devin K Schweppe, Michelle Cilia, Keith Rivera, Xuefei Zhong, Xia Wu, Terrence Allen, Moshe Khurgel, Akhilesh Kumar, Athanasios Lampropoulos, Mårten Larsson, Shuvadeep Maity, Yaroslav Morozov, Wimal Pathmasiri, Mathew Perez-Neut, Coriness Pineyro-Ruiz, Elizabeth Polina, Stephanie Post, Mark Rider, Dorota Tokmina-Roszyk, Katherine Tyson, Debora Vieira Parrine Sant'Ana, James E Bruce |
| Jazyk: |
angličtina |
| Rok vydání: |
2016 |
| Předmět: |
|
| Zdroj: |
PLoS ONE, Vol 11, Iss 12, p e0167547 (2016) |
| Druh dokumentu: |
article |
| ISSN: |
1932-6203 |
| DOI: |
10.1371/journal.pone.0167547 |
| Popis: |
Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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