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physics.chem-ph2026
Enerzyme: A Framework for Efficient Training of Reactive Neural Network Potentials for Enzyme Catalysis with Application to Methyltransferases
Weiliang Luo, Heather J. Kulik
Quantum mechanical (QM) cluster models provide an effective framework for mechanistic studies of enzymatic reactions but remain computationally demanding. Neural network potentials…
physics.chem-ph2026
Beyond the Training Domain: Robust Generative Transition State Models for Unseen Chemistry
Samir Darouich, Jacob W. Toney, Weiliang Luo +3
Transition states (TSs) govern the rates and outcomes of chemical reactions, making their accurate prediction a central challenge in computational chemistry. Although recent machin…