Characterizing protein conformers by cross-linking mass spectrometry and pattern recognition
| Autor: | Luana O. dos Santos, Diogo B. Lima, Fabio C. Gozzo, Marlon D.M. Santos, Eduardo S B Lyra, Paulo C. Carvalho, Milan A. Clasen, Louise U. Kurt, Carlos H.I. Ramos |
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| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
0303 health sciences biology Computer science 030302 biochemistry & molecular biology Computational biology Mutually exclusive events Mass spectrometry Biochemistry Hsp90 Computer Science Applications 03 medical and health sciences Computational Mathematics Protein structure Computational Theory and Mathematics Pattern recognition (psychology) biology.protein Target protein Molecular Biology Conformational isomerism 030304 developmental biology |
| Zdroj: | Bioinformatics. 37:3035-3037 |
| ISSN: | 1460-2059 1367-4803 |
| DOI: | 10.1093/bioinformatics/btab149 |
| Popis: | Motivation Chemical cross-linking coupled to mass spectrometry (XLMS) emerged as a powerful technique for studying protein structures and large-scale protein-protein interactions. Nonetheless, XLMS lacks software tailored toward dealing with multiple conformers; this scenario can lead to high-quality identifications that are mutually exclusive. This limitation hampers the applicability of XLMS in structural experiments of dynamic protein systems, where less abundant conformers of the target protein are expected in the sample. Results We present QUIN-XL, a software that uses unsupervised clustering to group cross-link identifications by their quantitative profile across multiple samples. QUIN-XL highlights regions of the protein or system presenting changes in its conformation when comparing different biological conditions. We demonstrate our software’s usefulness by revisiting the HSP90 protein, comparing three of its different conformers. QUIN-XL’s clusters correlate directly to known protein 3D structures of the conformers and therefore validates our software. Availabilityand implementation QUIN-XL and a user tutorial are freely available at http://patternlabforproteomics.org/quinxl for academic users. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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