Harmonizing structural mass spectrometry analyses in the mass spec studio.
Covalent labeling
Crosslinking
Hydrogen/deuterium exchange
Integrative modeling
Structural mass spectrometry
Journal
Journal of proteomics
ISSN: 1876-7737
Titre abrégé: J Proteomics
Pays: Netherlands
ID NLM: 101475056
Informations de publication
Date de publication:
15 08 2020
15 08 2020
Historique:
received:
24
01
2020
revised:
23
05
2020
accepted:
24
05
2020
pubmed:
2
6
2020
medline:
22
6
2021
entrez:
2
6
2020
Statut:
ppublish
Résumé
Structural Mass Spectrometry (SMS) provides a comprehensive toolbox for the analysis of protein structure and function. It offers multiple sources of structural information that are increasingly useful for integrative structural modeling of complex protein systems. As MS-based structural workflows scale to larger systems, consistent and coherent data interpretation resources are needed to better support modeling. Unlike the proteomics community, practitioners of SMS lack adequate computational tools. Here, we review new developments in the Mass Spec Studio: an expandable ecosystem of workflows for the analysis of complementary SMS techniques with linkages to modeling. Current functionality in the Studio (version 2) supports three major SMS workflows (crosslinking, hydrogen/deuterium exchange and covalent labelling) and two pipelines for structural modeling, with a special focus on data integration. The Mass Spec Studio is an architecture focused on rapid and robust extension of functionality by a community of developers. SIGNIFICANCE: This review surveys the new data analysis capabilities within the Mass Spec Studio, a rich framework for rapid software development specifically targeting the community of structural proteomics and structural mass spectrometry. Updates to crosslinking, hydrogen/deuterium-exchange and covalent labeling apps are provided as well as a utility for translating such analyses into restraints that support integrative structural modeling. These new capabilities, together with the underlying design tools and content, provide the community with a wealth of resources to tackle complex structural problem and design new approaches to data analysis.
Identifiants
pubmed: 32480078
pii: S1874-3919(20)30212-8
doi: 10.1016/j.jprot.2020.103844
pii:
doi:
Substances chimiques
Proteins
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
103844Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest None.