Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/3847
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dc.contributor.authorMatthew Allen Bullock, Joshuaen_US
dc.contributor.authorSen, Neeladrien_US
dc.contributor.authorThalassinos, Konstantinosen_US
dc.contributor.authorTopf, Mayaen_US
dc.date.accessioned2019-09-09T11:25:51Z-
dc.date.available2019-09-09T11:25:51Z-
dc.date.issued2018-07en_US
dc.identifier.citationStructure, 26(7), 1015-1024.e2.en_US
dc.identifier.issn0969-2126en_US
dc.identifier.issn1878-4186en_US
dc.identifier.urihttp://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/3847-
dc.identifier.urihttps://doi.org/10.1016/j.str.2018.04.016en_US
dc.description.abstractModeling 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.en_US
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.subjectCrosslinkingen_US
dc.subjectScoring functionen_US
dc.subjectCrosslinking mass spectrometryen_US
dc.subjectIntegrative modelingen_US
dc.subject3D electron microscopycryoen_US
dc.subjectEmproteinen_US
dc.subjectStructure modellingen_US
dc.subject2018en_US
dc.titleModeling Protein Complexes Using Restraints from Crosslinking Mass Spectrometryen_US
dc.typeArticleen_US
dc.contributor.departmentDept. of Biologyen_US
dc.identifier.sourcetitleStructureen_US
dc.publication.originofpublisherForeignen_US
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