Publication Details
EnzymeMiner: Web Server for Automated Mining and Annotation of Soluble Enzymes in Genomic Databases
Borko Simeon, Ing. (FIT BUT)
Marušiak Martin, Ing. (FIT BUT)
Martínek Tomáš, doc. Ing., Ph.D. (DCSY FIT BUT)
Bednář David, Mgr. (LL)
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 [1]. Traditional biochemical characterization techniques are time-demanding, cost-ineffective, and low-throughput. To address these limitations, we have developed EnzymeMiner web server for automated and periodic in silico screening of diverse family members. EnzymeMiner helps to effectively prioritize and select novel putative enzyme sequences by providing sequence similarity network visualization, active site and Pfam annotations, observations from BioProject database and prediction of protein solubility using SoluProt method [2]. EnzymeMiner provides highly interactive and easy-to-use web interface enabling well-informed selection of promising soluble enzymes for further experimental characterization. The only required input is an EC number. Using EnzymeMiner, a number of novel haloalkane dehalogenases with potential practical uses have been identified, characterized, and made available to the community in industry and academia [1]. A further application of EnzymeMiner to other enzyme families will expand our knowledge of protein evolution and will lead to the discovery of novel biocatalysts.
[1] Vanacek et al. 2018, Exploration of Enzyme Diversity by Integrating Bioinformatics with Expression Analysis and Biochemical Characterization. ACS Catalysis 8: 2402-2412
[2] Hon et al. 2019, SoluProt: Prediction of Protein Solubility. Bioinformatics (in preparation)