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This simulation study demonstrates enzyme catalysis through machine-learned potentials, indicating a new approach for efficiency in computational chemistry.
Enzyme catalysis can be simulated accurately and efficiently by coupling machine-learned potentials trained on gas-phase data to the environment (ML/MM) using electrostatic machine-learning embedding (EMLE).
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Gradisteanu et al. (2026) studied this question.
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