Abstract

DelPhiPKa is widely used for accurate prediction of pKa's of ionizable residues in proteins, DNAs and RNAs. DelPhiPKa approach is unique because it does not define the molecular surface, rather it uses a smooth Gaussian-based dielectric function throughout the space. The new development considers the presence of salt in the modeling protocol in a non-trivial manner via desolvation penalty term within the Boltzmann factor of Poisson-Boltzmann equation. This factor penalizes the salt ions to enter in the solute interior in a smooth manner without requiring sharp border between solute-solvent. Therefore, the presence of salt near macromolecule is determined by a combination of favorable electrostatic interactions and desolvation penalty. The DelPhiPKa-computed pKa's are in very good agreement with the experimentally determined pKa, having RMSD of 0.74. The unique approach of Gaussian-based smooth dielectric results in improved pKa's predictions compared to the standard method of two dielectric regions. DelPhiPKa also enables the calculations of pKa's of polar residues such as serine, cysteine, tyrosine and threonine. It has been demonstrated that DelPhiPKa outperforms all the other existing methods, even the explicit water models, while benchmarking the calculated pKa's against experimental pKa's of cysteine. Furthermore, we calculated the pKa's shifts due to the mutations in the protein-protein complexes taken from the SKEMPI database. We demonstrate that significant fraction of mutations listed in SKEMPI database results in unusual pKa's for introduced mutation or induce pKa's shifts of neighboring titratable groups. This is discussed in term of altering pH-dependence of the binding free energy.

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