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Selenzyme: enzyme selection tool for pathway design

Abstract : Summary: Synthetic biology applies the principles of engineering to biology in order to create biological functionalities not seen before in nature. One of the most exciting applications of synthetic biology is the design of new organisms with the ability to produce valuable chemicals including pharmaceuticals and biomaterials in a greener; sustainable fashion. Selecting the right enzymes to catalyze each reaction step in order to produce a desired target compound is, however, not trivial. Here, we present Selenzyme, a free online enzyme selection tool for metabolic pathway design. The user is guided through several decision steps in order to shortlist the best candidates for a given pathway step. The tool graphically presents key information about enzymes based on existing databases and tools such as: similarity of sequences and of catalyzed reactions; phylogenetic distance between source organism and intended host species; multiple alignment highlighting conserved regions, predicted catalytic site, and active regions and relevant properties such as predicted solubility and transmembrane regions. Selenzyme provides bespoke sequence selection for automated workflows in biofoundries. Availability and implementation: The tool is integrated as part of the pathway design stage into the design-build-test-learn SYNBIOCHEM pipeline. The Selenzyme web server is available at http:// selenzyme.synbiochem.co.uk. Supplementary information: Supplementary data are available at Bioinformatics online.
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Pablo Carbonell, Jerry Wong, Neil Swainston, Erika Takano, Nicholas J. Turner, et al.. Selenzyme: enzyme selection tool for pathway design. Bioinformatics, Oxford University Press (OUP), 2018, 34 (12), pp.2153-2154. ⟨10.1093/bioinformatics/bty065⟩. ⟨hal-02621189⟩



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