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

optional - free

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

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/

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