Vizcarra Christina L, Zhang Naigong, Marshall Shannon A, Wingreen Ned S, Zeng Chen, Mayo Stephen L
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA.
J Comput Chem. 2008 May;29(7):1153-62. doi: 10.1002/jcc.20878.
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.
我们的目标是开发能够在当前计算蛋白质设计协议中实现的精确静电模型。为此，我们改进了先前报道的用于蛋白质设计的成对可分解有限差分泊松-玻尔兹曼（FDPB）模型（Marshall等人，《蛋白质科学》2005年，第14卷，第1293页）。改进之处包括在氨基酸身份未知的位置放置通用侧链，并明确捕捉对介电环境的两体扰动。我们将原始和改进的FDPB方法与标准FDPB计算进行比较，在标准FDPB计算中，介电环境完全由蛋白质原子确定。通用侧链方法在每个残基或残基对的准确性上比原始的成对FDPB实现提高了两到三倍，且无需额外的计算成本。还将距离依赖介电和溶剂排除模型与标准FDPB能量进行了比较。即使在对溶剂排除模型进行重新参数化之后，新的成对FDPB方法的准确性仍被证明优于这些模型。
