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This paper introduces a charge-space electronic collective variable (eCV) for describing and enhancing the sampling of chemical reactions, addressing limitations of geometric CVs. A neural network is trained on QM/MM data to provide atomic charges and eCV gradients within an iterative sampling-training loop. The eCV, constructed from atomic charge differences between reactant and product states, is demonstrated to effectively capture reaction progress across diverse chemical reactions in aqueous and enzymatic environments.
Representing chemical reactions through electron redistribution, rather than geometry, unlocks a transferable and physically grounded approach to reaction sampling.
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.
