Toward accurate prediction of pKa values for internal protein residues: the importance of conformational relaxation and desolvation energy

Proteins. 2011 Dec;79(12):3364-73. doi: 10.1002/prot.23080. Epub 2011 Jul 11.

Abstract

Proton uptake or release controls many important biological processes, such as energy transduction, virus replication, and catalysis. Accurate pK(a) prediction informs about proton pathways, thereby revealing detailed acid-base mechanisms. Physics-based methods in the framework of molecular dynamics simulations not only offer pK(a) predictions but also inform about the physical origins of pK(a) shifts and provide details of ionization-induced conformational relaxation and large-scale transitions. One such method is the recently developed continuous constant pH molecular dynamics (CPHMD) method, which has been shown to be an accurate and robust pK(a) prediction tool for naturally occurring titratable residues. To further examine the accuracy and limitations of CPHMD, we blindly predicted the pK(a) values for 87 titratable residues introduced in various hydrophobic regions of staphylococcal nuclease and variants. The predictions gave a root-mean-square deviation of 1.69 pK units from experiment, and there were only two pK(a)'s with errors greater than 3.5 pK units. Analysis of the conformational fluctuation of titrating side-chains in the context of the errors of calculated pK(a) values indicate that explicit treatment of conformational flexibility and the associated dielectric relaxation gives CPHMD a distinct advantage. Analysis of the sources of errors suggests that more accurate pK(a) predictions can be obtained for the most deeply buried residues by improving the accuracy in calculating desolvation energies. Furthermore, it is found that the generalized Born implicit-solvent model underlying the current CPHMD implementation slightly distorts the local conformational environment such that the inclusion of an explicit-solvent representation may offer improvement of accuracy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Hydrogen-Ion Concentration
  • Hydrophobic and Hydrophilic Interactions
  • Models, Chemical
  • Models, Molecular
  • Molecular Dynamics Simulation*
  • Mutation
  • Protein Conformation*
  • Protein Structure, Tertiary
  • Proteins / chemistry*
  • Proteins / genetics
  • Proteins / metabolism*
  • Static Electricity
  • Statistics as Topic / methods
  • Thermodynamics

Substances

  • Proteins