Publication details

SoluProtMutDB: A manually curated database of protein solubility changes upon mutations

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Authors

VELECKÝ Jan HAMŠÍKOVÁ Marie ŠTOURAČ Jan MUSIL Miloš DAMBORSKÝ Jiří BEDNÁŘ David MAZURENKO Stanislav

Year of publication 2022
Type Article in Periodical
Magazine / Source Computational and Structural Biotechnology Journal
MU Faculty or unit

Faculty of Science

Citation
web https://www.sciencedirect.com/science/article/pii/S2001037022005025?via%3Dihub
Doi http://dx.doi.org/10.1016/j.csbj.2022.11.009
Keywords Mutational database; Protein engineering; Soluble expression; Protein yield; Machine learning; Protein aggregation
Attached files
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 SoluProtMutDB – 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.
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