Generalized solvent boundary potential for computer simulations

Copyright 2001 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in The Journal of Chemical Physics and may be found at http://dx.doi.org/10.1063/1.1336570.A general approach has been developed to allow accurate simulations of a small region part of a large macromolecular system while incorporating the influence of the remaining distant atoms with an effective boundary potential. The method is called the Generalized Solvent Boundary Potential (GSBP). By representing the surrounding solvent as a continuum dielectric, both the solvent-shielded static field from the distant atoms of the macromolecule and the reaction field from the dielectricsolvent acting on the atoms in the region of interest are included. The static field is calculated once, using the finite-difference Poisson–Boltzmann (PB) equation, and the result is stored on a discrete grid for efficient simulations. The solventreaction field is developed using a basis-set expansion whose coefficients correspond to generalized electrostatic multipoles. A matrix representing the reaction field Green’s function between those generalized multipoles is calculated only once using the PB equation and stored for efficient simulations. In the present work, the formalism is applied to both spherical and orthorhombic simulation regions for which orthonormal basis-sets exist based on spherical harmonics or cartesian Legendre polynomials. The GSBP method is also tested and illustrated with simple model systems and two detailed atomic systems: the active site region of aspartyl-tRNA synthetase (spherical region) and the interior of the KcsA potassium channel (orthorhombic region). Comparison with numerical finite-difference PB calculations shows that GSBP can accurately describe all long-range electrostatic interactions and remain computationally inexpensive

Electrostatic free energy calculations using the generalized solvent boundary potential method

Copyright 2002 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in The Journal of Chemical Physics and may be found at http://dx.doi.org/10.1063/1.1507108.Free energyperturbation (FEP) calculations using all-atom molecular dynamics simulations with a large number of explicit solvent molecules are a powerful approach to study ligand–macromolecule association processes at the atomic level. One strategy to carry out FEP calculations efficiently and reduce computational time is to consider the explicit dynamics of only a small number of atoms in a localized region around the ligand. Such an approximation is motivated by the observation that the factors governing binding specificity are dominated by interactions in the vicinity of the ligand. However, a straightforward truncation of the system may yield inaccurate results as the influence exerted by the remote regions of the macromolecule and the surrounding solvent through long-range electrostatic effects may be significant. To obtain meaningful results, it is important to incorporate the influence of the remote regions of the ligand–macromolecule complex implicitly using some effective potential. The generalized solvent boundary potential (GSBP) that was developed recently [W. Im, S. Bernèche, and B. Roux, J. Chem. Phys. 114, 2924 (2001)] is an efficient computational method to represent the long-range electrostaticinteractions arising from remote (outer) regions in simulations of a localized (inner) region with a small number of explicit atoms. In the present work, FEP calculations combined with GSBP are used to illustrate the importance of these long-range electrostatic factors in estimation of the charging free energy of an aspartate ligand bound to the aspartyl-tRNA synthetase. Calculations with explicit spherical simulation inner regions of different radii are used to test the accuracy of the GSBP method and also illustrate the importance of explicit protein and solvent dynamics in the free energy estimation. The influence of the represented outer region is tested using separate simulations in which the reaction field and/or the protein static field are excluded. Both components are shown to be essential to obtain quantitatively meaningful results. The ability of implicitly treating the influence of protein fluctuations in the outer region using a protein dielectric constant is examined. It is shown that accurate charging free energy calculations can be performed for this system with a spherical region of 15 to 20 Å radius, which roughly corresponds to 1500–3500 moving atoms. The results indicate that GSBP in combination with FEP calculations is a precise and efficient approach to include long-range electrostatic effects in the study of ligand binding to large macromolecules

The Solvation Structure of Na⁺ and K⁺ in Liquid Water Determined from High Level <i>ab Initio</i> Molecular Dynamics Simulations

Knowledge of the hydration structure of Na⁺ and K⁺ in the liquid phase has wide ranging implications in the field of biological chemistry. Despite numerous experimental and computational studies, even basic features such as the coordination number of these alkali ions in liquid water, thought to play a critical role in selectivity, continue to be the subject of intensive debates. Simulations based on accurate potential energy surfaces offer one approach to resolve these issues by providing reliable results on ion hydration. In this article, we report the results from molecular dynamics simulations of Na⁺ and K⁺ hydration based on a novel and rigorous strategy designed to overcome the challenges of QM/MM simulations of solvent molecules in the liquid phase. In this method, which we call Flexible Inner Region Ensemble Separator (FIRES), the ion and a fixed number of nearest water molecules form a dynamical and flexible inner region that is represented with high level ab initio quantum mechanical (QM) methods, while the water molecules from the surrounding bulk form an outer region that is represented by a polarizable molecular mechanical (MM) force field. Simulations yield rigorously correct thermodynamic averages as long as the solvent molecules in the flexible inner and outer regions are not allowed to exchange. Extensive FIRES simulations were carried out based on a QM/MM model in which the Na⁺ or K⁺ ion and the 12 nearest water molecules were represented by high level ab initio methods (RI-MP2/def2-TZVP and density functional theory with PBE/def2-TZVP), while the surrounding MM water molecules were represented by the polarizable SWM4-NDP potential. On the basis of these results, the ion coordination numbers are estimated to be within the range of 5.7–5.8 for Na⁺ and 6.9–7.0 for K⁺

Molecular Structure of Canonical Liquid Crystal Interfaces

Numerous applications of liquid crystals rely on control of molecular orientation at an interface. However, little is known about the precise molecular structure of such interfaces. In this work, synchrotron X-ray reflectivity measurements, accompanied by large-scale atomistic molecular dynamics simulations, are used for the first time to reconstruct the air-liquid crystal interface of a nematic material, namely, 4-pentyl-4′-cyanobiphenyl (5CB). The results are compared to those for 4-octyl-4′-cyanobiphenyl (8CB) which, in addition to adopting isotropic and nematic states, can also form a smectic phase. Our findings indicate that the air interface imprints a highly ordered structure into the material; such a local structure then propagates well into the bulk of the liquid crystal, particularly for nematic and smectic phases

Self-Learning Adaptive Umbrella Sampling Method for the Determination of Free Energy Landscapes in Multiple Dimensions

The potential of mean force describing conformational changes of biomolecules is a central quantity for understanding the function of biomolecular systems. Calculating an energy landscape of a process that depends on three or more reaction coordinates requires extensive computational power, making some multidimensional calculations practically impossible. Here, we present an efficient automatized umbrella sampling strategy for calculating a multidimensional potential of mean force. The method progressively learns by itself, through a feedback mechanism, which regions of a multidimensional space are worth exploring and automatically generates a set of umbrella sampling windows that is adapted to the system. The selflearning adaptive umbrella sampling method is first explained with illustrative examples based on simplified reduced model systems and then applied to two nontrivial situations: the conformational equilibrium of the pentapeptide Met-enkephalin in solution and ion permeation in the KcsA potassium channel. With this method, it is demonstrated that a significant smaller number of umbrella windows needs to be employed to characterize the free energy landscape over the most relevant regions without any loss in accuracy