ArticleProteins2016
Blind testing of cross-linking/mass spectrometry hybrid methods in CASP11.
Article in Proteins, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Protein Structure Prediction with Mass Spectrometry Data.Annual review of physical chemistry · 2022Review
- Integrative Modeling of a Sin3/HDAC Complex Sub-structure.Cell reports · 2020Article
- Article
- Role of integrative structural biology in understanding transcriptional initiation.Methods (San Diego, Calif.) · 2019Review
- The First MS-Cleavable, Photo-Thiol-Reactive Cross-Linker for Protein Structural Studies.Journal of the American Society for Mass Spectrometry · 2019Article
- Cross-linking mass spectrometry: methods and applications in structural, molecular and systems biology.Nature structural & molecular biology · 2018Review
- Synthesis of CID-cleavable protein crosslinking agents containing quaternary amines for structural mass spectrometry.Organic & biomolecular chemistry · 2018Article
- Article
- Protein Tertiary Structure by Crosslinking/Mass Spectrometry.Trends in biochemical sciences · 2018Review
- Article
- A Novel MS-Cleavable Azo Cross-Linker for Peptide Structure Analysis by Free Radical Initiated Peptide Sequencing (FRIPS).Journal of the American Society for Mass Spectrometry · 2017Article
- Novel Concepts of MS-Cleavable Cross-linkers for Improved Peptide Structure Analysis.Journal of the American Society for Mass Spectrometry · 2017Article
- Surface Accessibility and Dynamics of Macromolecular Assemblies Probed by Covalent Labeling Mass Spectrometry and Integrative Modeling.Analytical chemistry · 2017Article
- Blind testing cross-linking/mass spectrometry under the auspices of the 11Wellcome open research · 2016Article
- Blind Evaluation of Hybrid Protein Structure Analysis Methods based on Cross-Linking.Trends in biochemical sciences · 2016Article
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Authors and funding
4 authors.
Funding
Abstract
Hybrid approaches combine computational methods with experimental data. The information contained in the experimental data can be leveraged to probe the structure of proteins otherwise elusive to computational methods. Compared with computational methods, the structures produced by hybrid methods exhibit some degree of experimental validation. In spite of these advantages, most hybrid methods have not yet been validated in blind tests, hampering their development. Here, we describe the first blind test of a specific cross-link based hybrid method in CASP. This blind test was coordinated by the CASP organizers and utilized a novel, high-density cross-linking/mass-spectrometry (CLMS) approach that is able to collect high-density CLMS data in a matter of days. This experimental protocol was developed in the Rappsilber laboratory. This approach exploits the chemistry of a highly reactive, photoactivatable cross-linker to produce an order of magnitude more cross-links than homobifunctional cross-linkers. The Rappsilber laboratory generated experimental CLMS data based on this protocol, submitted the data to the CASP organizers which then released this data to the CASP11 prediction groups in a separate, CLMS assisted modeling experiment. We did not observe a clear improvement of assisted models, presumably because the properties of the CLMS data-uncertainty in cross-link identification and residue-residue assignment, and uneven distribution over the protein-were largely unknown to the prediction groups and their approaches were not yet tailored to this kind of data. We also suggest modifications to the CLMS-CASP experiment and discuss the importance of rigorous blind testing in the development of hybrid methods. Proteins 2016; 84(Suppl 1):152-163. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.
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