Catalysis Importance | Open Access Journals

Chemical Sciences Journal

ISSN: 2150-3494

Open Access

Catalysis Importance

Millions of protein sequences are being come across 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. The 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 come about EnzymeMiner—a web server for automated screening and annotation of diverse family members that enables the 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.

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