Quantitative Structural Interpretation of Protein Crosslinks
| Autor: | Benjamin Bardiaux, Michael Nilges, Isaac Filella-Merce, Guillaume Bouvier |
|---|---|
| Přispěvatelé: | Bioinformatique structurale - Structural Bioinformatics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Universitat Pompeu Fabra [Barcelona] (UPF), This work was supported by the European Research Council (MN: FP7-IDEAS- ERC 294809)., We would like to thank R. Pellarin and B. Worley for helpful discussions and support. I.F.-M. acknowledges support from the Erasmus+ framework., European Project: 294809,EC:FP7:ERC,ERC-2011-ADG_20110310,BAYCELLS(2012), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Models
Molecular Web server sampling Computer science Protein Conformation MESH: Cross-Linking Reagents Context (language use) restraints computer.software_genre USable Mass Spectrometry 03 medical and health sciences Cross-links NRGXL MESH: Protein Conformation Structural Biology MESH: Markov Chains MESH: Proteins [SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry Molecular Biology/Biochemistry [q-bio.BM] Molecular Biology 030304 developmental biology Flexibility (engineering) MESH: Mass Spectrometry 0303 health sciences protein complexes Protein dynamics 030302 biochemistry & molecular biology Proteins modeling Grid Binary Classification study Markov Chains Euclidean distance Cross-Linking Reagents [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT] [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] Biological system computer Classifier (UML) MESH: Models Molecular |
| Zdroj: | Structure Structure, 2020, 28 (1), pp.75-82. ⟨10.1016/j.str.2019.10.018⟩ Structure, Elsevier (Cell Press), 2020, 28 (1), pp.75-82. ⟨10.1016/j.str.2019.10.018⟩ |
| ISSN: | 0969-2126 |
| DOI: | 10.1016/j.str.2019.10.018⟩ |
| Popis: | International audience; Chemical crosslinking, combined with mass spectrometry analysis, is a key source of information for characterizing the structure of large protein assemblies, in the context of molecular modeling. In most approaches, the interpretation is limited to simple spatial restraints, neglecting physico-chemical interactions between the crosslinker and the protein and their flexibility. Here we present a method, named NRGXL (new realistic grid for crosslinks), which models the flexibility of the crosslinker and the linked side-chains, by explicitly sampling many conformations. Also, the method can efficiently deal with overall protein dynamics. This method creates a physical model of the crosslinker and associated energy. A classifier based on it outperforms others, based on Euclidean distance or solvent-accessible distance and its efficiency makes it usable for validating 3D models from crosslinking data. NRGXL is freely available as a web server at: https://nrgxl.pasteur.fr. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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