Very fast prediction and rationalization of pKa values for protein-ligand complexes

The PROPKA method for the prediction of the pK(a) values of ionizable residues in proteins is extended to include the effect of non-proteinaceous ligands on protein pK(a) values as well as predict the change in pK(a) values of ionizable groups on the ligand itself. This new version of PROPKA (PROPKA 2.0) is, as much as possible, developed by adapting the empirical rules underlying PROPKA 1.0 to ligand functional groups. Thus, the speed of PROPKA is retained, so that the pK(a) values of all ionizable groups are computed in a matter of seconds for most proteins. This adaptation is validated by comparing PROPKA 2.0 predictions to experimental data for 26 protein-ligand complexes including trypsin, thrombin, three pepsins, HIV-1 protease, chymotrypsin, xylanase, hydroxynitrile lyase, and dibydrofolate reductase. For trypsin and thrombin, large protonation state changes (vertical bar n vertical bar > 0.5) have been observed experimentally for 4 out of 14 ligand complexes. PROPKA 2.0 and Klebe's PEOE approach (Czodrowski P, et al. J Mol Biol 2007;367:1347-1356) both identify three of the four large protonation state changes. The protonation state changes due to plasmepsin 11, cathepsin D and endothiapepsin binding to pepstatin are predicted to within 0.4 proton units at pH 6.5 and 7.0, respectively. The PROPKA 2.0 results indicate that structural changes due to ligand binding contribute significantly to the proton uptake/release, as do residues far away from the binding site, primarily due to the change in the local environment of a particular residue and hence the change in the local hydrogen bonding network. Overall the results suggest that PROPKA 2.0 provides a good description of the protein-ligand interactions that have an important effect on the pK(a) values of titratable groups, thereby permitting fast and accurate determination of the protonation states of key residues and ligand functional