title: A statistical approach to the prediction of pK(a) values in proteins.
abstract: We propose a simple model for the calculation of pK(a) values of ionizable residues in proteins. It is based on the premise that the pK(a) shift of ionizable residues is linearly correlated to the interaction between a particular residue and the local environment created by the surrounding residues. Despite its simplicity, the model displays good prediction performance. Under the sixfold cross test prediction over a data set of 405 experimental pK(a) values in 73 protein chains with known structures, the root-mean-square deviation (RMSD) between the experimental and calculated pK(a) was found to be 0.77. The accuracy of this model increases with increasing size of the data set: the RMSD is 0.609 for glutamate (the largest data set with 141 sites) and approximately 1 pH unit for lysine, with a data set containing 45 sites.
authors.affiliation: National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Yun
authors.initials: Y
authors.lastname: He
authors.forename: Jialin
authors.initials: J
authors.lastname: Xu
authors.forename: Xian-Ming
authors.initials: XM
authors.lastname: Pan
mesh_terms: D006860:Hydrogen Bonding; D006863:Hydrogen-Ion Concentration; D007526:Isoelectric Point; D008958:Models, Molecular; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods; D011487:Protein Conformation; D011489:Protein Denaturation; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins