DelPhiPKa: Including salt in the calculations and enabling polar residues to titrate

S Pahari, L Sun, S Basu… - … : Structure, Function, and …, 2018 - Wiley Online Library
Proteins: Structure, Function, and Bioinformatics, 2018Wiley Online Library
DelPhiPKa is a widely used and unique approach to compute pKa's of ionizable groups that
does not require molecular surface to be defined. Instead, it uses smooth Gaussian‐based
dielectric function to treat computational space via Poisson‐Boltzmann equation (PBE).
Here, we report an expansion of DelPhiPKa functionality to enable inclusion of salt in the
modeling protocol. The method considers the salt mobile ions in solvent phase without
defining solute‐solvent boundary. Instead, the ions are penalized to enter solute interior via …
Abstract
DelPhiPKa is a widely used and unique approach to compute pKa's of ionizable groups that does not require molecular surface to be defined. Instead, it uses smooth Gaussian‐based dielectric function to treat computational space via Poisson‐Boltzmann equation (PBE). Here, we report an expansion of DelPhiPKa functionality to enable inclusion of salt in the modeling protocol. The method considers the salt mobile ions in solvent phase without defining solute‐solvent boundary. Instead, the ions are penalized to enter solute interior via a desolvation penalty term in the Boltzmann factor in the framework of PBE. Hence, the concentration of ions near the protein is balanced by the desolvation penalty and electrostatic interactions. The study reveals that correlation between experimental and calculated pKa's is improved significantly by taking into consideration the presence of salt. Furthermore, it is demonstrated that DelphiPKa reproduces the salt sensitivity of experimentally measured pKa's. Another new development of DelPhiPKa allows for computing the pKa's of polar residues such as cysteine, serine, threonine and tyrosine. With this regard, DelPhiPKa is benchmarked against experimentally measured cysteine and tyrosine pKa's and for cysteine it is shown to outperform other existing methods (DelPhiPKa RMSD of 1.73 vs RMSD between 2.40 and 4.72 obtained by other existing pKa prediction methods).
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