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findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM
Although experimental protein-structure determination usually targets known proteins, chains of unknown sequence are often encountered. They can be purified from natural sources, appear as an unexpected fragment of a well characterized protein or appear as a contaminant. Regardless of the source of...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733886/ https://www.ncbi.nlm.nih.gov/pubmed/35059213 http://dx.doi.org/10.1107/S2052252521011088 |
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author | Chojnowski, Grzegorz Simpkin, Adam J. Leonardo, Diego A. Seifert-Davila, Wolfram Vivas-Ruiz, Dan E. Keegan, Ronan M. Rigden, Daniel J. |
author_facet | Chojnowski, Grzegorz Simpkin, Adam J. Leonardo, Diego A. Seifert-Davila, Wolfram Vivas-Ruiz, Dan E. Keegan, Ronan M. Rigden, Daniel J. |
author_sort | Chojnowski, Grzegorz |
collection | PubMed |
description | Although experimental protein-structure determination usually targets known proteins, chains of unknown sequence are often encountered. They can be purified from natural sources, appear as an unexpected fragment of a well characterized protein or appear as a contaminant. Regardless of the source of the problem, the unknown protein always requires characterization. Here, an automated pipeline is presented for the identification of protein sequences from cryo-EM reconstructions and crystallographic data. The method’s application to characterize the crystal structure of an unknown protein purified from a snake venom is presented. It is also shown that the approach can be successfully applied to the identification of protein sequences and validation of sequence assignments in cryo-EM protein structures. |
format | Online Article Text |
id | pubmed-8733886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-87338862022-01-19 findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM Chojnowski, Grzegorz Simpkin, Adam J. Leonardo, Diego A. Seifert-Davila, Wolfram Vivas-Ruiz, Dan E. Keegan, Ronan M. Rigden, Daniel J. IUCrJ Research Papers Although experimental protein-structure determination usually targets known proteins, chains of unknown sequence are often encountered. They can be purified from natural sources, appear as an unexpected fragment of a well characterized protein or appear as a contaminant. Regardless of the source of the problem, the unknown protein always requires characterization. Here, an automated pipeline is presented for the identification of protein sequences from cryo-EM reconstructions and crystallographic data. The method’s application to characterize the crystal structure of an unknown protein purified from a snake venom is presented. It is also shown that the approach can be successfully applied to the identification of protein sequences and validation of sequence assignments in cryo-EM protein structures. International Union of Crystallography 2021-12-01 /pmc/articles/PMC8733886/ /pubmed/35059213 http://dx.doi.org/10.1107/S2052252521011088 Text en © Grzegorz Chojnowski et al. 2022 https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. |
spellingShingle | Research Papers Chojnowski, Grzegorz Simpkin, Adam J. Leonardo, Diego A. Seifert-Davila, Wolfram Vivas-Ruiz, Dan E. Keegan, Ronan M. Rigden, Daniel J. findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM |
title |
findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM |
title_full |
findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM |
title_fullStr |
findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM |
title_full_unstemmed |
findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM |
title_short |
findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM |
title_sort | findmysequence: a neural-network-based approach for identification of unknown proteins in x-ray crystallography and cryo-em |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733886/ https://www.ncbi.nlm.nih.gov/pubmed/35059213 http://dx.doi.org/10.1107/S2052252521011088 |
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