Enzyme Promiscuity Prediction Using Hierarchy-Informed Multi-Label Classification.
Journal:
Bioinformatics (Oxford, England)
Published Date:
Aug 4, 2021
Abstract
MOTIVATION: As experimental efforts are costly and time consuming, computational characterization of enzyme capabilities is an attractive alternative. We present and evaluate several machine-learning models to predict which of 983 distinct enzymes, as defined via the Enzyme Commission (EC) numbers, are likely to interact with a given query molecule. Our data consists of enzyme-substrate interactions from the BRENDA database. Some interactions are attributed to natural selection and involve the enzyme's natural substrates. The majority of the interactions however involve non-natural substrates, thus reflecting promiscuous enzymatic activities.