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    Home > Biochemistry News > Biotechnology News > PLoS Biology: Artificial intelligence helps quantify enzyme activity

    PLoS Biology: Artificial intelligence helps quantify enzyme activity

    • Last Update: 2021-11-01
    • Source: Internet
    • Author: User
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    Image: A schematic diagram of the process of predicting the Michaelis constant of an enzyme using a deep learning method


    Source: HHU/Nazi Party emblem Mishra

    Without enzymes, organisms cannot survive


    In order to describe the metabolic processes promoted by enzymes, scientists have cited the Michaelis-Manten equation


    It takes a lot of time and effort to measure this constant in the laboratory


    They applied methods based on deep learning methods to 47 biological models, including bacteria, plants, and humans


    Professor Lercher evaluated the quality of the results in this way: "Using independent test data, we were able to prove that the process can predict the Michaelis constant with accuracy similar to the difference between experimental values ​​in different laboratories


    "Public Library of Science · Biology" magazine emphasized in an article that the Michaelis constants of all enzymes in model organisms are suddenly available, opening up a new way for metabolic computer modeling


    Alexander Kroll, Martin KM Engqvist, David Heckmann, Martin Lercher, Deep learning allows genome-scale prediction of Michaelis constants from structural features,PLOS Biology(2021).


    DOI: 10.



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