Publication Details
EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities
Borko Simeon, Ing. (FIT BUT)
Štourač Jan (LL)
Prokop Zbyněk, doc. RnDr., Ph.D. (LL)
Bednář David, Mgr. (LL)
Zendulka Jaroslav, doc. Ing., CSc. (DIFS FIT BUT)
Martínek Tomáš, doc. Ing., Ph.D. (DCSY FIT BUT)
Damborský Jiří, prof. Mgr., Dr. (LL)
computational characterization, enzyme mining, enzyme diversity, novel biocatalysts
Millions of protein sequences are being discovered at an incredible pace, representing an inexhaustible source of biocatalysts. Despite genomic databases growing exponentially, classical biochemical characterization techniques are time-demanding, cost-ineffective and low-throughput. Therefore, computational methods are being developed to explore the unmapped sequence space efficiently. Selection of putative enzymes for biochemical characterization based on rational and robust analysis of all available sequences remains an unsolved problem. To address this challenge, we have developed EnzymeMiner - a web server for automated screening and annotation of diverse family members that enables selection of hits for wet-lab experiments. 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/.
@ARTICLE{FITPUB12197, author = "Ji\v{r}\'{i} Hon and Simeon Borko and Jan \v{S}toura\v{c} and Zbyn\v{e}k Prokop and David Bedn\'{a}\v{r} and Jaroslav Zendulka and Tom\'{a}\v{s} Mart\'{i}nek and Ji\v{r}\'{i} Damborsk\'{y}", title = "EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities", pages = "104--109", journal = "Nucleic Acids Research", volume = 48, number = 1, year = 2020, ISSN = "1362-4962", doi = "10.1093/nar/gkaa372", language = "english", url = "https://www.fit.vut.cz/research/publication/12197" }