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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F22%3A00078809" target="_blank" >RIV/00159816:_____/22:00078809 - isvavai.cz</a>

Alternative codes found

RIV/00216305:26230/22:PU146770 RIV/00216224:14310/22:00130114

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S2001037022005025?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2001037022005025?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.csbj.2022.11.009" target="_blank" >10.1016/j.csbj.2022.11.009</a>

Result language

angličtina

Original language name

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

Original language 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 33000 measurements of 17000 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. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10608 - Biochemistry and molecular biology

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computational and Structural Biotechnology Journal

ISSN

2001-0370

e-ISSN

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Volume of the periodical

20

Issue of the periodical within the volume

2022

Country of publishing house

SE - SWEDEN

Number of pages

9

Pages from-to

6339-6347

UT code for WoS article

001043880900004

EID of the result in the Scopus database

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