Quaternary structure modeling through chemical cross-linking mass spectrometry : Extending tx-ms jupyter reports
(2021) In Journal of Visualized Experiments- Abstract
Protein-protein interactions can be challenging to study yet provide insights into how biological systems function. Targeted cross-linking mass spectrometry (TX-MS), a method combining quaternary protein structure modeling and chemical cross-linking mass spectrometry, creates high-accuracy structure models using data obtained from complex, unfractionated samples. This removes one of the major obstacles to protein complex structure analysis because the proteins of interest no longer need to be purified in large quantities. Cheetah-MS web server was developed to make the simplified version of the protocol more accessible to the community. Considering the tandem MS/MS data, Cheetah-MS generates a Jupyter Notebook, a graphical report... (More)
Protein-protein interactions can be challenging to study yet provide insights into how biological systems function. Targeted cross-linking mass spectrometry (TX-MS), a method combining quaternary protein structure modeling and chemical cross-linking mass spectrometry, creates high-accuracy structure models using data obtained from complex, unfractionated samples. This removes one of the major obstacles to protein complex structure analysis because the proteins of interest no longer need to be purified in large quantities. Cheetah-MS web server was developed to make the simplified version of the protocol more accessible to the community. Considering the tandem MS/MS data, Cheetah-MS generates a Jupyter Notebook, a graphical report summarizing the most important analysis results. Extending the Jupyter Notebook can yield more in-depth insights and better understand the model and the mass spectrometry data supporting it. The technical protocol presented here demonstrates some of the most common extensions and explains what information can be obtained. It contains blocks to help analyze tandem MS/MS acquisition data and the overall impact of the detected XLs on the reported quaternary models. The result of such analyses can be applied to structural models that are embedded in the notebook using NGLView.
(Less)
- author
- Khakzad, Hamed ; Vermeul, Swen and Malmström, Lars LU
- organization
- publishing date
- 2021-10
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Visualized Experiments
- issue
- 176
- article number
- e60311
- publisher
- JoVE
- external identifiers
-
- pmid:34747410
- scopus:85121974289
- ISSN
- 1940-087X
- DOI
- 10.3791/60311
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2021 JoVE Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
- id
- f78c8570-da1a-40ba-b1f2-11bdd9ebf281
- date added to LUP
- 2022-02-21 14:48:39
- date last changed
- 2024-03-21 05:56:45
@article{f78c8570-da1a-40ba-b1f2-11bdd9ebf281,
abstract = {{<p>Protein-protein interactions can be challenging to study yet provide insights into how biological systems function. Targeted cross-linking mass spectrometry (TX-MS), a method combining quaternary protein structure modeling and chemical cross-linking mass spectrometry, creates high-accuracy structure models using data obtained from complex, unfractionated samples. This removes one of the major obstacles to protein complex structure analysis because the proteins of interest no longer need to be purified in large quantities. Cheetah-MS web server was developed to make the simplified version of the protocol more accessible to the community. Considering the tandem MS/MS data, Cheetah-MS generates a Jupyter Notebook, a graphical report summarizing the most important analysis results. Extending the Jupyter Notebook can yield more in-depth insights and better understand the model and the mass spectrometry data supporting it. The technical protocol presented here demonstrates some of the most common extensions and explains what information can be obtained. It contains blocks to help analyze tandem MS/MS acquisition data and the overall impact of the detected XLs on the reported quaternary models. The result of such analyses can be applied to structural models that are embedded in the notebook using NGLView.</p>}},
author = {{Khakzad, Hamed and Vermeul, Swen and Malmström, Lars}},
issn = {{1940-087X}},
language = {{eng}},
number = {{176}},
publisher = {{JoVE}},
series = {{Journal of Visualized Experiments}},
title = {{Quaternary structure modeling through chemical cross-linking mass spectrometry : Extending tx-ms jupyter reports}},
url = {{http://dx.doi.org/10.3791/60311}},
doi = {{10.3791/60311}},
year = {{2021}},
}