Publication Details

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

VELECKÝ, J.; HAMŠÍKOVÁ, M.; ŠTOURAČ, J.; MUSIL, M.; DAMBORSKÝ, J.; BEDNÁŘ, D.; MAZURENKO, S. SoluProtMutDB: A manually curated database of protein solubility changes upon mutations. Computational and Structural Biotechnology Journal, 2022, vol. 20, no. 1, p. 6339-6347. ISSN: 2001-0370.
Czech title
SoluProtMutDB: manuálně spravovaná databáze proteinové solubility při zanesení mutace
Type
journal article
Language
English
Authors
Velecký Jan, Ing.
Hamšíková Marie
Štourač Jan (FIT)
Musil Miloš, Ing., Ph.D. (DIFS)
Damborský Jiří, prof. Mgr., Dr. (UMEL)
Bednář David (FIT)
Mazurenko Stanislav, Ph.D.
URL
Keywords

Mutational database, Protein engineering, Protein yield, Machine learning, Protein aggregation

Abstract

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.

Published
2022
Pages
6339–6347
Journal
Computational and Structural Biotechnology Journal, vol. 20, no. 1, ISSN 2001-0370
DOI
10.1016/j.csbj.2022.11.009
EID Scopus
2-s2.0-85142188313
BibTeX 
@article{BUT180690,
  author="Jan {Velecký} and Marie {Hamšíková} and Jan {Štourač} and Miloš {Musil} and Jiří {Damborský} and David {Bednář} and Stanislav {Mazurenko}",
  title="SoluProtMutDB: A manually curated database of protein solubility changes upon mutations",
  journal="Computational and Structural Biotechnology Journal",
  year="2022",
  volume="20",
  number="1",
  pages="6339--6347",
  doi="10.1016/j.csbj.2022.11.009",
  issn="2001-0370",
  url="https://reader.elsevier.com/reader/sd/pii/S2001037022005025?token=47A572AECBA6EE5C334462194E5EFC9034D184A71EC41EC7B29311B976C644C5FCFBB5B1B449E84DD1A99A04BCFA8708&originRegion=eu-west-1&originCreation=20230110080940"
}
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