Abstract

Charge regulation, defined as the regulation of charge states of ionizable residues through the uptake or release of protons, can influence the conformational ensembles and distributions of charge states that are accessible to intrinsically disordered proteins. These influences are exerted through sequence- and conformational-context dependent pKa values. We recently developed and deployed a q-canonical ensemble that allows for the linked analyses of separate measurements, of charge and conformation as a function of pH. When combined with atomistic, q-canonical Monte Carlo simulations based on the ABSINTH implicit solvation model, we were able to uncover the pH-dependent interplay of charge state and conformational heterogeneity. However, the combinatorial increase in the number of charge states to consider has remained a persistent challenge. Here, we introduce a breakthrough that allows us to predict the extent of charge regulation to be expected for IDPs arbitrary numbers of ionizable residues. The algorithm leverages prior information regarding the effects of local sequence contexts on charge regulation. Longer sequences with arbitrary numbers of ionizable residues are built up using a chain-growth Monte Carlo procedure, each step building on extant information for peptide fragments. We have deployed the new methodology in a high-throughput investigation of sequences drawn from the IDRome, which is the sub-proteome of intrinsically disordered regions (IDRs). We find that the apparent charge, obtained by assuming model compound pKa values, is rarely the same as the real charge that one predicts based on an accounting of charge regulation effects. This work paves the way to understanding the sequence features that result in charge regulation effects, and their importance to biomolecular processes.

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