Differential geometry based solvation model I: Eulerian formulation

被引:103
作者
Chen, Zhan [1 ]
Baker, Nathan A. [2 ]
Wei, G. W. [1 ,3 ]
机构
[1] Michigan State Univ, Dept Math, E Lansing, MI 48824 USA
[2] Pacific NW Natl Lab, Richland, WA 99352 USA
[3] Michigan State Univ, Dept Elect & Comp Engn, E Lansing, MI 48824 USA
关键词
Generalized Poisson-Boltzmann equation; Biomolecular surface formation and evolution; Potential driving geometric flows; Solvation free energy; Multiscale models; POISSON-BOLTZMANN EQUATION; MOLECULAR-DYNAMICS SIMULATIONS; GENERALIZED-BORN MODEL; IMPLICIT SOLVENT MODELS; BOUNDARY MIB METHOD; PROTEIN-PROTEIN INTERACTIONS; POLARIZABLE CONTINUUM MODEL; STATE SMOLUCHOWSKI EQUATION; COMPUTING MINIMAL-SURFACES; FINITE-ELEMENT-ANALYSIS;
D O I
10.1016/j.jcp.2010.06.036
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents a differential geometry based model for the analysis and computation of the equilibrium property of solvation. Differential geometry theory of surfaces is utilized to define and construct smooth interfaces with good stability and differentiability for use in characterizing the solvent-solute boundaries and in generating continuous dielectric functions across the computational domain. A total free energy functional is constructed to couple polar and nonpolar contributions to the solvation process. Geometric measure theory is employed to rigorously convert a Lagrangian formulation of the surface energy into an Eulerian formulation so as to bring all energy terms into an equal footing. By optimizing the total free energy functional, we derive coupled generalized Poisson-Boltzmann equation (GPBE) and generalized geometric flow equation (GGFE) for the electrostatic potential and the construction of realistic solvent-solute boundaries, respectively. By solving the coupled GPBE and GGFE, we obtain the electrostatic potential, the solvent-solute boundary profile, and the smooth dielectric function, and thereby improve the accuracy and stability of implicit solvation calculations. We also design efficient second-order numerical schemes for the solution of the GPBE and GGFE. Matrix resulted from the discretization of the GPBE is accelerated with appropriate preconditioners. An alternative direct implicit (ADI) scheme is designed to improve the stability of solving the GGFE. Two iterative approaches are designed to solve the coupled system of nonlinear partial differential equations. Extensive numerical experiments are designed to validate the present theoretical model, test computational methods, and optimize numerical algorithms. Example solvation analysis of both small compounds and proteins are carried out to further demonstrate the accuracy, stability, efficiency and robustness of the present new model and numerical approaches. Comparison is given to both experimental and theoretical results in the literature. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码:8231 / 8258
页数:28
相关论文
共 191 条
[1]   Efficient and precise solvation free energies via alchemical adiabatic molecular dynamics [J].
Abrams, Jerry B. ;
Rosso, Lula ;
Tuckerman, Mark E. .
JOURNAL OF CHEMICAL PHYSICS, 2006, 125 (07)
[2]   Self-consistent-field calculation of Pauli repulsion and dispersion contributions to the solvation free energy in the polarizable continuum model [J].
Amovilli, C ;
Mennucci, B .
JOURNAL OF PHYSICAL CHEMISTRY B, 1997, 101 (06) :1051-1057
[3]   The determinants of pK(a)s in proteins [J].
Antosiewicz, J ;
McCammon, JA ;
Gilson, MK .
BIOCHEMISTRY, 1996, 35 (24) :7819-7833
[4]   Convergence of molecular and macroscopic continuum descriptions of ion hydration [J].
Ashbaugh, HS .
JOURNAL OF PHYSICAL CHEMISTRY B, 2000, 104 (31) :7235-7238
[5]   PDB_Hydro: incorporating dipolar solvents with variable density in the Poisson-Boltzmann treatment of macromolecule electrostatics [J].
Azuara, Cyril ;
Lindahl, Erik ;
Koehl, Patrice ;
Orland, Henri ;
Delarue, Marc .
NUCLEIC ACIDS RESEARCH, 2006, 34 :W38-W42
[6]  
Baker N.A., 2006, New algorithms for macromolecular simulation
[7]   Biomolecular applications of Poisson-Boltzmann methods [J].
Baker, NA .
REVIEWS IN COMPUTATIONAL CHEMISTRY, VOL 21, 2005, 21 :349-379
[8]   Improving implicit solvent simulations: a Poisson-centric view [J].
Baker, NA .
CURRENT OPINION IN STRUCTURAL BIOLOGY, 2005, 15 (02) :137-143
[9]  
Baker NA, 2004, METHOD ENZYMOL, V383, P94
[10]  
Baker Nathan A, 2003, Methods Biochem Anal, V44, P427