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This paper introduces a charge-space electronic collective variable (eCV) based on atomic charges to represent the electronic component of chemical reaction progress. A neural network model is trained on QM/MM data within an iterative sampling-training workflow to provide atomic charges and CV gradients for enhanced sampling. The eCV demonstrates transferability across reactions in diverse environments and reveals coupled electronic and conformational components in reaction progress, reducing reliance on geometric descriptors.
Representing chemical reactions in charge-space, rather than geometric space, unlocks a transferable electronic collective variable that captures the electronic component of reaction progress.
Chemical reaction sampling critically depends on collective variables (CVs) that capture the slow degrees of freedom governing reactive transformations. However, existing reaction CVs are often defined in geometric space or learned in a system-specific manner, which limits their transferability and leaves open the more fundamental question of how reaction progress should be represented. From a physical perspective, chemical reactions are defined by electron redistribution. Here, we introduce a charge-space electronic collective variable that describes the electronic component of reaction progress in a common linear form based on atomic charges. To enable its use in enhanced sampling, atomic charges and the corresponding CV gradients are provided by a neural-network model trained on QM/MM data within an iterative sampling-training workflow. Across multiple reactions in aqueous and enzymatic environments, we show that this electronic CV can be constructed in a common charge-space form, with the corresponding coefficients assigned in a simple manner from charge differences between relevant states. Our simulations further show that reaction progress generally involves coupled electronic and conformational components, and that the same framework can also be extended to restrain side reactions. These findings support charge-based electronic CVs as a physically motivated framework for describing the electronic component of chemical reaction progress with reduced reliance on handcrafted geometric descriptors.