AIMC Topic: Aminohydrolases

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Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases.

Proteins Nov 10, 2020
Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequence- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they gener...
Machine Learning Molecular Docking Simulation Protein Binding Bacterial Proteins Ligands Chemical Phenomena Catalytic Domain Nitriles Aminohydrolases
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Machine learning modelling for the ultrasonication-mediated disruption of recombinant E. coli for the efficient release of nitrilase.

Ultrasonics Jun 10, 2019
The ultrasonication-mediated cell disruption of recombinant E. coli was modeled using three machine learning techniques namely Multiple linear regression (MLR), Multi-layer perceptron (MLP) and Sequential minimal optimization (SMO). The four attribut...
Neural Networks, Computer Machine Learning Time Factors Escherichia coli Sonication Aminohydrolases
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