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Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling
Covalent labeling (CL) in combination with mass spectrometry can be used as an analytical tool to study and determine structural properties of protein-protein complexes. However, data from these experiments is sparse and does not unambiguously elucidate protein structure. Thus, computational algorit...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9772387/ https://www.ncbi.nlm.nih.gov/pubmed/36543826 http://dx.doi.org/10.1038/s41467-022-35593-8 |
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author | Drake, Zachary C. Seffernick, Justin T. Lindert, Steffen |
author_facet | Drake, Zachary C. Seffernick, Justin T. Lindert, Steffen |
author_sort | Drake, Zachary C. |
collection | PubMed |
description | Covalent labeling (CL) in combination with mass spectrometry can be used as an analytical tool to study and determine structural properties of protein-protein complexes. However, data from these experiments is sparse and does not unambiguously elucidate protein structure. Thus, computational algorithms are needed to deduce structure from the CL data. In this work, we present a hybrid method that combines models of protein complex subunits generated with AlphaFold with differential CL data via a CL-guided protein-protein docking in Rosetta. In a benchmark set, the RMSD (root-mean-square deviation) of the best-scoring models was below 3.6 Å for 5/5 complexes with inclusion of CL data, whereas the same quality was only achieved for 1/5 complexes without CL data. This study suggests that our integrated approach can successfully use data obtained from CL experiments to distinguish between nativelike and non-nativelike models. |
format | Online Article Text |
id | pubmed-9772387 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97723872022-12-23 Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling Drake, Zachary C. Seffernick, Justin T. Lindert, Steffen Nat Commun Article Covalent labeling (CL) in combination with mass spectrometry can be used as an analytical tool to study and determine structural properties of protein-protein complexes. However, data from these experiments is sparse and does not unambiguously elucidate protein structure. Thus, computational algorithms are needed to deduce structure from the CL data. In this work, we present a hybrid method that combines models of protein complex subunits generated with AlphaFold with differential CL data via a CL-guided protein-protein docking in Rosetta. In a benchmark set, the RMSD (root-mean-square deviation) of the best-scoring models was below 3.6 Å for 5/5 complexes with inclusion of CL data, whereas the same quality was only achieved for 1/5 complexes without CL data. This study suggests that our integrated approach can successfully use data obtained from CL experiments to distinguish between nativelike and non-nativelike models. Nature Publishing Group UK 2022-12-21 /pmc/articles/PMC9772387/ /pubmed/36543826 http://dx.doi.org/10.1038/s41467-022-35593-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Drake, Zachary C. Seffernick, Justin T. Lindert, Steffen Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling |
title | Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling |
title_full | Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling |
title_fullStr | Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling |
title_full_unstemmed | Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling |
title_short | Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling |
title_sort | protein complex prediction using rosetta, alphafold, and mass spectrometry covalent labeling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9772387/ https://www.ncbi.nlm.nih.gov/pubmed/36543826 http://dx.doi.org/10.1038/s41467-022-35593-8 |
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