Result Details

EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities

Created: 2020
Type
software
Language
English
Authors
Borko Simeon, Ing.
Hon Jiří, Ing., Ph.D., DIFS (FIT)
Bednář David, FIT (FIT)
Damborský Jiří, prof. Mgr., Dr., UMEL (FEEC)
Martínek Tomáš, doc. Ing., Ph.D., DCSY (FIT)
Prokop Zbyněk, FIT (FIT)
Štourač Jan, FIT (FIT)
Zendulka Jaroslav, doc. Ing., CSc., DIFS (FIT)
Description

EnzymeMiner prioritizes sequences that are more likely to preserve the catalytic activity and are heterologously expressible in a soluble form in Escherichia coli. The solubility prediction employs the in-house SoluProt predictor developed using machine learning. EnzymeMiner reduces the time devoted to data gathering, multi-step analysis, sequence prioritization and selection from days to hours. The successful use case for the haloalkane dehalogenase family is described in a comprehensive tutorial available on the EnzymeMiner web page. EnzymeMiner is a universal tool applicable to any enzyme family that provides an interactive and easy-to-use web interface freely available at https://loschmidt.chemi.muni.cz/enzymeminer/.

Keywords

computational characterization, enzyme mining, enzyme diversity, novel biocatalysts

URL
License
Use of the result by another entity is possible without acquiring a license in some cases
License Fee
The licensor does not require a license fee for the result
Projects
Metody AI pro zabezpečení kybernetického prostoru a řídicí systémy, BUT, Vnitřní projekty VUT, FIT-S-20-6293, start: 2020-03-01, end: 2023-02-28, completed
Departments
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