What question did this study set out to answer?

The aim is to enhance reaction modeling and enzyme design using machine-learning force fields.

May 6, 2026Open Access

MAPLE: A Machine-Learning Force-Field-Native Platform for Automated Reaction Modeling and Enzyme Design

Key Points

The aim is to enhance reaction modeling and enzyme design using machine-learning force fields.
Developed a machine-learning force-field-native platform
Applied to automated reaction modeling
Focused on enzyme design
Utilized near-quantum mechanical accuracy
Improved computational cost comparable to conventional force fields
Enhanced accuracy for biomolecular simulations

Abstract

Machine-learning force fields (MLFFs) are reshaping computational chemistry and biology by delivering near-quantum mechanical accuracy at a computational cost comparable to conventional force fields, enabling applications in biomolecular simulation, catalysis,...

MAPLE: A Machine-Learning Force-Field-Native Platform for Automated Reaction Modeling and Enzyme Design

Key Points

Abstract

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