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

EnzymeMiner: automatické dolování rozpustných enzymů s různorodými strukturami, katalytickými vlastnostmi a stabilitou

software

Use of the result by another entity is possible without acquiring a license in some cases

The licensor does not require a license fee for the result

Borko Simeon, Ing.
Hon Jiří, Ing., Ph.D.
Bednář David
Damborský Jiří, prof. Mgr., Dr. (UMEL)
Martínek Tomáš, doc. Ing., Ph.D. (DCSY)
Prokop Zbyněk
Štourač Jan
Zendulka Jaroslav, doc. Ing., CSc. (UIFS)

computational characterization, enzyme mining, enzyme diversity, novel
biocatalysts

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/.

https://loschmidt.chemi.muni.cz/enzymeminer/

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

Department of Information Systems (DIFS)