Molecular origins of pH gradients in charge-regulated biomolecular condensates

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Abstract
Biomolecular condensates exhibit spontaneous electrochemical microenvironments characterized by asymmetric ion distributions and pH gradients that emerge from protein-sequence-dependent charge regulation. Despite their biological importance, mechanistic understanding of these microenvironments has been constrained by the absence of computationally tractable frameworks capable of treating proton exchange, counterion partitioning, and buffer equilibria on consistent thermodynamic footing. Here, we introduce the buffered Charge-Regulation Monte Carlo (b-CR-MC) framework, which couples grand-canonical exchange of ions and buffer species with explicit charge regulation of titratable residues. By extending the CR-MC ion-merging strategy to multicomponent reservoirs and employing the restricted primitive model, b-CR-MC achieves computational efficiency while maintaining thermodynamic rigor, achievingquantitative agreement with the more expensive generalized grand-reaction Monte Carlo approach. Applied to full-length FUS (net positive) and PGL-3 (net negative) under physiological conditions, the framework reveals sequence-dependent pH gradients: the dense phase of FUS exhibits an alkaline shift, while that of PGL-3 exhibits an acidic shift, in both cases driving the condensate interior toward the protein's isoelectric point. Slab-geometry simulations further resolve the Donnan potential and continuous ion profiles across the condensate interface, confirming the direction of these electrochemical shifts. Additionally, we identify spatially resolved buffer depletion within dense phases, establishing that dynamic charge regulation is a primary determinant rather than a secondary correction to condensate electrochemistry. By establishing a sequence-resolved, thermodynamically consistent computational platform, b-CR-MC enables quantitative prediction of how mutations and post-translational modifications reprogram condensate microenvironments across biological and pathophysiological contexts.
Funding Information
  • National Institute of General Medical Sciences (R35GM153388)

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