We propose an efficient algorithm to predict the acid dissociation constant (pKa) value of amino acid in a protein by using 3D-RISM-SCF theory.Protonation and de-protonation process are very important in vivo chemical reaction. The protonation states sometime plays essential role to determine the reactivity of enzyme, the structural stability, and so forth. Therefore, predicting the protonation states is one of the most important task of computational and theoretical chemistry. A protonation state of amino acid residues can be measured by the acid dissociation constant (pKa). Many theoretical schemes to predict of pKavalue of amino acid are proposed.Recently, Matsui et al. proposed the efficient algorithm to predict the pKa value of amino acid using quantum- chemical calculation combined with a polarizable continuum model[1]. In the method, pKavalue of amino acids is evaluated using least square fitting using parameters determined for small reference molecules. Using this scheme, we can obtain a semi-quantitative pKa value of specific chemical groups, like COOH, NH3+, and so on. However, this scheme is not considered about the effect of hydrogen bond between amino-acid and solvent water and solvation entropy.To improve this scheme, we employ 3D-RISM-SCF which is combined method of electronic structure theory with statistical mechanical theory for molecular liquid. We estimate pKa value of amino acid (Asp, Glu, Lys, Cys, Try, His and Ser) with parameters, which determined by 3D-RISM-SCF calculation. The results quantitatively agree with the experimental results.References  [1]T. Matsui, T. Baba, K. Kamiya, Y. Shigeta, Phys. Chem. Chem. Phys. 2012, 14, 4181-4187

Theoretical prediction of p<i>K</i><sub>a </sub>value of amino acid using 3D-RISM-SCF

248th National Meeting (2014)

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Theoretical prediction of pKa value of amino acid using 3D-RISM-SCF

Theoretical prediction of pK_avalue of amino acid using 3D-RISM-SCF