PubMed · 8464462
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O W van Assendelft. 1993-04-01. SI units explained.. https://doi.org/10.1038/362388c0
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MOTIVATION: Predicting enzyme function from its sequence is still an unsolved problem in the life sciences. Moreover, with the explosion of annotated genome data, we are inundated with potential enzymatic sequences that have not yet been biochemically characterized. While it is not possible to assign a not-yet-existing label to such a sequence, there is high value in placing the sequence as accurately as possible in known function space. Doing so can help provide more accurate falsifiable hypotheses for experimentalists wishing to characterize enzymes from specific functional families. RESULTS: Here we present a contrastive learning algorithm for predicting enzyme function from sequence. Our method, EnzPlacer, predicts the third, second, and first EC numbers for a protein whose fourth EC number is not in the training corpus. This novel prediction mechanism accurately places a protein sequence within a narrowed-down functional context, even if the precise function remains unknown. AVAILABILITY AND IMPLEMENTATION: EnzPlacer and data is available at https://github.com/drxiangma/EnzPlacer under a GPL3 license.
Of various commercial enzyme preparations examined, Cytolase M102 was found to contain the highest glucosyltransferase activity (55 U ml-1). It rapidly converted maltose to panose (Glc alpha-->6 Glc alpha l-->4 Glc) with a Vmax value of 5.8 mmol l-1 min-1 at 50 degrees C in 0.05 mol l-1 sodium acetate buffer (pH 4.4). The Km value of the enzyme for maltose was 750 mmol l-1. Yields of panose and glucose after 45 min of reaction, for example, were 47.2% and 52.8%, respectively, on the basis of the amount of maltose consumed.