Modeling protein complexes using restraints from Crosslinking Mass Spectrometry
Bullock, Joshua M.A. and Sen, N. and Thalassinos, Konstantinos and Topf, Maya (2018) Modeling protein complexes using restraints from Crosslinking Mass Spectrometry. Structure 26 (7), 1015-1024.e2. ISSN 0969-2126.
|
Text
22562.pdf - Published Version of Record Available under License Creative Commons Attribution. Download (4MB) | Preview |
Abstract
Modeling macromolecular assemblies with restraints from crosslinking mass spectrometry (XL-MS) tends to focus solely on distance violation. Recently, we identified three different modeling features inherent in crosslink data: (1) expected distance between crosslinked residues; (2) violation of the crosslinker's maximum bound; and (3) solvent accessibility of crosslinked residues. Here, we implement these features in a scoring function. cMNXL, and demonstrate that it outperforms the commonlyused crosslink distance violation. We compare the different methods of calculating the distance between crosslinked residues, which shows no significant change in performance when using Euclidean distance compared with the solvent-accessible surface distance. Finally, we create a combined score that incorporates information from 3D electron microscopy maps as well as crosslinking. This achieves, on average, better results than either information type alone and demonstrates the potential of integrative modeling with XL-MS and low-resolution cryoelectron microscopy.
Metadata
Item Type: | Article |
---|---|
Keyword(s) / Subject(s): | crosslinking, scoring function, crosslinking mass spectrometry, integrative modeling, 3D electron microscopy, cryo-EM, protein structure modelling |
School: | Birkbeck Faculties and Schools > Faculty of Science > School of Natural Sciences |
SWORD Depositor: | Mr Joe Tenant |
Depositing User: | Mr Joe Tenant |
Date Deposited: | 29 May 2018 15:55 |
Last Modified: | 02 Aug 2023 17:42 |
URI: | https://eprints.bbk.ac.uk/id/eprint/22562 |
Statistics
Additional statistics are available via IRStats2.