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SoluProtMut(DB): A manually curated database of protein solubility changes upon mutations
Protein solubility is an attractive engineering target primarily due to its relation to yields in protein production and manufacturing. Moreover, better knowledge of the mutational effects on protein solubility could connect several serious human diseases with protein aggregation. However, we have l...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678803/ https://www.ncbi.nlm.nih.gov/pubmed/36420168 http://dx.doi.org/10.1016/j.csbj.2022.11.009 |
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author | Velecký, Jan Hamsikova, Marie Stourac, Jan Musil, Milos Damborsky, Jiri Bednar, David Mazurenko, Stanislav |
author_facet | Velecký, Jan Hamsikova, Marie Stourac, Jan Musil, Milos Damborsky, Jiri Bednar, David Mazurenko, Stanislav |
author_sort | Velecký, Jan |
collection | PubMed |
description | Protein solubility is an attractive engineering target primarily due to its relation to yields in protein production and manufacturing. Moreover, better knowledge of the mutational effects on protein solubility could connect several serious human diseases with protein aggregation. However, we have limited understanding of the protein structural determinants of solubility, and the available data have mostly been scattered in the literature. Here, we present SoluProtMut(DB) – the first database containing data on protein solubility changes upon mutations. Our database accommodates 33 000 measurements of 17 000 protein variants in 103 different proteins. The database can serve as an essential source of information for the researchers designing improved protein variants or those developing machine learning tools to predict the effects of mutations on solubility. The database comprises all the previously published solubility datasets and thousands of new data points from recent publications, including deep mutational scanning experiments. Moreover, it features many available experimental conditions known to affect protein solubility. The datasets have been manually curated with substantial corrections, improving suitability for machine learning applications. The database is available at loschmidt.chemi.muni.cz/soluprotmutdb. |
format | Online Article Text |
id | pubmed-9678803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-96788032022-11-22 SoluProtMut(DB): A manually curated database of protein solubility changes upon mutations Velecký, Jan Hamsikova, Marie Stourac, Jan Musil, Milos Damborsky, Jiri Bednar, David Mazurenko, Stanislav Comput Struct Biotechnol J Data Article Protein solubility is an attractive engineering target primarily due to its relation to yields in protein production and manufacturing. Moreover, better knowledge of the mutational effects on protein solubility could connect several serious human diseases with protein aggregation. However, we have limited understanding of the protein structural determinants of solubility, and the available data have mostly been scattered in the literature. Here, we present SoluProtMut(DB) – the first database containing data on protein solubility changes upon mutations. Our database accommodates 33 000 measurements of 17 000 protein variants in 103 different proteins. The database can serve as an essential source of information for the researchers designing improved protein variants or those developing machine learning tools to predict the effects of mutations on solubility. The database comprises all the previously published solubility datasets and thousands of new data points from recent publications, including deep mutational scanning experiments. Moreover, it features many available experimental conditions known to affect protein solubility. The datasets have been manually curated with substantial corrections, improving suitability for machine learning applications. The database is available at loschmidt.chemi.muni.cz/soluprotmutdb. Research Network of Computational and Structural Biotechnology 2022-11-09 /pmc/articles/PMC9678803/ /pubmed/36420168 http://dx.doi.org/10.1016/j.csbj.2022.11.009 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Data Article Velecký, Jan Hamsikova, Marie Stourac, Jan Musil, Milos Damborsky, Jiri Bednar, David Mazurenko, Stanislav SoluProtMut(DB): A manually curated database of protein solubility changes upon mutations |
title | SoluProtMut(DB): A manually curated database of protein solubility changes upon mutations |
title_full | SoluProtMut(DB): A manually curated database of protein solubility changes upon mutations |
title_fullStr | SoluProtMut(DB): A manually curated database of protein solubility changes upon mutations |
title_full_unstemmed | SoluProtMut(DB): A manually curated database of protein solubility changes upon mutations |
title_short | SoluProtMut(DB): A manually curated database of protein solubility changes upon mutations |
title_sort | soluprotmut(db): a manually curated database of protein solubility changes upon mutations |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678803/ https://www.ncbi.nlm.nih.gov/pubmed/36420168 http://dx.doi.org/10.1016/j.csbj.2022.11.009 |
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