An improved pairwise decomposable finite-difference Poisson-Boltzmann method for computational protein design.
Our goal is to develop accurate electrostatic models that can be implemented in current computational protein design protocols. To this end, we improve upon a previously reported pairwise decomposable, finite difference Poisson-Boltzmann (FDPB) model for protein design (Marshall et al., Protein Sci 2005, 14, 1293). The improvement involves placing generic sidechains at positions with unknown amino acid identity and explicitly capturing two-body perturbations to the dielectric environment. We compare the original and improved FDPB methods to standard FDPB calculations in which the dielectric environment is completely determined by protein atoms. The generic sidechain approach yields a two to threefold increase in accuracy per residue or residue pair over the original pairwise FDPB implementation, with no additional computational cost. Distance dependent dielectric and solvent-exclusion models were also compared with standard FDPB energies. The accuracy of the new pairwise FDPB method is shown to be superior to these models, even after reparameterization of the solvent-exclusion model.
Vizcarra
Christina L
CL
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA.
Zhang
Naigong
N
Marshall
Shannon A
SA
Wingreen
Ned S
NS
Zeng
Chen
C
Mayo
Stephen L
SL
D000596:Amino Acids / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D017076:Computer-Aided Design; D008956:Models, Chemical; D016012:Poisson Distribution; D011506:Proteins / Q000737:chemistry*; D015203:Reproducibility of Results; D055672:Static Electricity; D013816:Thermodynamics
D000596:Amino Acids; D011506:Proteins