Abstract

Protonation / deprotonation reactions of ionizable residues, referred to as charge regulation, can have a profound impact on the conformational ensembles of intrinsically disordered proteins (IDPs). Charge regulation is likely to be impacted mainly by local sequence contexts of ionizable residues. This can lead to context-dependent pKa values for ionizable residues that engender cryptic order-to-disorder or disorder-to-order transitions that cannot be modeled using simulations based on fixed charges or anticipated using sequence-based disorder predictors. To remedy this, we introduced the q-canonical sampling method for simulations of the linkage between charge regulation and conformational equilibria for IDPs with multiple ionizable residues. This approach leverages information from ABSINTH-based all-atom simulations of the full complement of relevant charge microstates, which are distinct sequences defined by combinations of charged and neutral versions of ionizable residues. Due to the exponential increase in the numbers of charge microstates to be considered, the q-canonical method can become computationally intractable for realistic IDPs. Here, we present a method that enables significant a priori pruning of relevant microstates. The method, which is probabilistic, relies on a decomposition of the total ionization free energy for each of the charge microstates while accounting for the effects of local sequence contexts. The probabilistic pruning relies on ionization free energies derived from prior applications q-canonical sampling to a database of pentapeptides where the central amino acid is the ionizable residue in question. Using the simulations of pentapeptides as priors, we achieve drastic reductions in the combinatorial complexity of relevant charge microstates. The improvements enable the application of q-canonical sampling to predictions of the pH dependence of the linkage between charge regulation and conformational equilibria of realistic IDPs.

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