A Customized Bayesian Algorithm to Optimize Enzyme-Catalyzed Reactions.

ABSTRACT: Design of experiments (DoE) plays an important role in optimizing the catalytic performance of chemical reactions. The most commonly used DoE relies on the response surface methodology (RSM) to model the variable space of experimental conditions with the fewest number of experiments. However, the RSM leads to an exponential increase in the number of required experiments as the number of variables increases. Herein we describe a Bayesian optimization algorithm (BOA) to optimize the continuous parameters (e.g., temperature, reaction time, reactant and enzyme concentrations, etc.) of enzyme-catalyzed reactions with the aim of maximizing performance. Compared to existing Bayesian optimization methods, we propose an improved algorithm that leads to better results under limited resources and tim

SUBMITTER: Tachibana R 

PROVIDER: S-EPMC10445256 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature