Incorporating the Effects of pH in Protein-Protein Docking

Abstract

Highly charged interfaces often frustrate protein-protein docking methods. Current approaches do not account for changes in the ionization states which may play a crucial role in binding. Predicting the charges on the residues would be the first step towards understanding the dependence of docking on pH. We developed a method to predict the pKa values of the common ionizable residues in proteins (Asp, Glu, Lys, His and Tyr) . It incorporates conformational flexibility through extensive amino-acid side-chain rotamer sampling and is based on the Rosetta energy function with an explicit term to account for the protonation state probabilities of the amino-acids. In approximately 80% of the cases, the method predicts the pKa value of a residue to an accuracy of 1 pH unit from the experimental value and 95% of the time it predicts a value within 2 units of pH. The method is comparable in accuracy to the other published computational pKa prediction methods and is fast enough to be used to dynamically predict and alter the ionization states of the amino-acid side chains during protein-protein docking. We expect the new protocol to lead to improvements in conformational sampling during docking as well as help in the discrimination and ranking of the generated ensemble of tentative protein complexes.