title: Developing hybrid approaches to predict pKa values of ionizable groups.
abstract: Accurate predictions of pKa values of titratable groups require taking into account all relevant processes associated with the ionization/deionization. Frequently, however, the ionization does not involve significant structural changes and the dominating effects are purely electrostatic in origin allowing accurate predictions to be made based on the electrostatic energy difference between ionized and neutral forms alone using a static structure and the subtle structural changes be accounted by using dielectric constant larger than two. On another hand, if the change of the charge state is accompanied by a large structural reorganization of the target protein, then the relevant conformational changes have to be explicitly taken into account in the pKa calculations. Here we report a hybrid approach that first predicts the titratable groups whose ionization is expected to cause large conformational changes, termed "problematic" residues, and then applies a special protocol on them, while the rest of the pK(a)s are predicted with rigid backbone approach as implemented in multi-conformation continuum electrostatics (MCCE) method. The backbone representative conformations for "problematic" groups are generated with either molecular dynamics simulations with charged and uncharged amino acid or with ab-initio local segment modeling. The corresponding ensembles are then used to calculate the titration curves of the "problematic" residues and then the results are averaged to obtain the corresponding pKa.
authors: Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, South Carolina 29634, USA.
authors: Shawn
authors: S
authors: Witham
authors: Kemper
authors: K
authors: Talley
authors: Lin
authors: L
authors: Wang
authors: Zhe
authors: Z
authors: Zhang
authors: Subhra
authors: S
authors: Sarkar
authors: Daquan
authors: D
authors: Gao
authors: Wei
authors: W
authors: Yang
authors: Emil
authors: E
authors: Alexov
mesh_terms: D000596:Amino Acids / Q000737:chemistry / Q000378:metabolism; D001426:Bacterial Proteins / Q000737:chemistry / Q000378:metabolism; D003198:Computer Simulation; D006863:Hydrogen-Ion Concentration; D008836:Micrococcal Nuclease / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism*; D008956:Models, Chemical; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D009154:Mutation; D011487:Protein Conformation; D017434:Protein Structure, Tertiary; D011522:Protons; D055672:Static Electricity; D013816:Thermodynamics
chemical_list: D000596:Amino Acids; D001426:Bacterial Proteins; D011522:Protons; D008836:Micrococcal Nuclease