Academic Journal
Deep learning the collisional cross sections of the peptide universe from a million experimental values
| العنوان: | Deep learning the collisional cross sections of the peptide universe from a million experimental values |
|---|---|
| المؤلفون: | Meier, Florian, Köhler, Niklas D., Brunner, Andreas-David, Wanka, Jean-Marc H., Voytik, Eugenia, Strauss, Maximilian T., Theis, Fabian J., Mann, Matthias |
| سنة النشر: | 2021 |
| المجموعة: | Digital Library Thüringen |
| مصطلحات موضوعية: | article, ScholarlyArticle, ddc:500, Machine learning, Mass spectrometry, Proteomics |
| الوصف: | The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests of five organisms with trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF). The scale and precision (CV < 1%) of our data is sufficient to train a deep recurrent neural network that accurately predicts CCS values solely based on the peptide sequence. Cross section predictions for the synthetic ProteomeTools peptides validate the model within a 1.4% median relative error ( R > 0.99). Hydrophobicity, proportion of prolines and position of histidines are main determinants of the cross sections in addition to sequence-specific interactions. CCS values can now be predicted for any peptide and organism, forming a basis for advanced proteomics workflows that make full use of the additional information. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | 12 Seiten |
| اللغة: | English |
| Relation: | Nature Communications -- 2041-1723 -- http://uri.gbv.de/document/gvk:ppn:626457688 -- 2553671-0 -- http://www.nature.com/ncomms/ -- http://www.bibliothek.uni-regensburg.de/ezeit/?2553671 -- http://d-nb.info/1002399459 |
| DOI: | 10.1038/s41467-021-21352-8 |
| الاتاحة: | https://doi.org/10.1038/s41467-021-21352-8 https://nbn-resolving.org/urn:nbn:de:gbv:27-dbt-20230327-222053-007 https://www.db-thueringen.de/receive/dbt_mods_00056533 https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00059516/s41467-021-21352-8.pdf |
| Rights: | https://creativecommons.org/licenses/by/4.0/ ; public ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.ED668419 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1038/s41467-021-21352-8 |
|---|