Determination of Ionic Hydration Free Energies with Grand Canonical Monte Carlo/Molecular Dynamics Simulations in Explicit Water.

Grand canonical Monte Carlo (GCMC) simulations of ionic solutions with explicit solvent models are known to be challenging. One challenge arises from the treatment of long-range electrostatics and finite-box size in Monte Carlo simulations when periodic boundary condition and Ewald summation methods are used. Another challenge is that constant excess chemical potential GCMC simulations for charged solutes suffer from inadequate insertion and deletion acceptance ratios. In this work, we address those problems by implementing an oscillating excess chemical potential GCMC algorithm with smooth particle mesh Ewald and finite-box-size corrections to treat the long-range electrostatics. The developed GCMC simulation program was combined with GROMACS to perform GCMC/MD simulations of ionic solutions individually containing Li+, Na+, K+, Rb+, Cs+, F-, Cl-, Br-, I-, Ca2+, and Mg2+, respectively. Our simulation results show that the combined GCMC/MD approach can approximate the ionic hydration free energies with proper treatment of long-range electrostatics. Our developed simulation approach can open up new avenues for simulating complex chemical and biomolecular systems and for drug discovery.

[1]  Gregory A Ross,et al.  Biomolecular Simulations under Realistic Macroscopic Salt Conditions , 2017, bioRxiv.

[2]  Gregory A Ross,et al.  Replica-Exchange and Standard State Binding Free Energies with Grand Canonical Monte Carlo , 2017, Journal of chemical theory and computation.

[3]  Peng Bai,et al.  Assessment and Optimization of Configurational-Bias Monte Carlo Particle Swap Strategies for Simulations of Water in the Gibbs Ensemble. , 2017, Journal of chemical theory and computation.

[4]  Alexander D. MacKerell,et al.  Characterization of Mg2+ Distributions around RNA in Solution , 2016, ACS omega.

[5]  Gregory A Ross,et al.  Water Sites, Networks, And Free Energies with Grand Canonical Monte Carlo. , 2015, Journal of the American Chemical Society.

[6]  J. Forsman,et al.  Evaluating Force Fields for the Computational Prediction of Ionized Arginine and Lysine Side-Chains Partitioning into Lipid Bilayers and Octanol. , 2015, Journal of chemical theory and computation.

[7]  B. Roux,et al.  An Overview of Electrostatic Free Energy Computations for Solutions and Proteins. , 2014, Journal of chemical theory and computation.

[8]  Alexander D. MacKerell,et al.  Sampling of Organic Solutes in Aqueous and Heterogeneous Environments Using Oscillating Excess Chemical Potentials in Grand Canonical-like Monte Carlo-Molecular Dynamics Simulations , 2014, Journal of chemical theory and computation.

[9]  B. L. de Groot,et al.  Quantifying Artifacts in Ewald Simulations of Inhomogeneous Systems with a Net Charge. , 2014, Journal of chemical theory and computation.

[10]  Alexander D. MacKerell,et al.  Inclusion of Multiple Fragment Types in the Site Identification by Ligand Competitive Saturation (SILCS) Approach , 2013, J. Chem. Inf. Model..

[11]  Delin Sun,et al.  Effect of water content on microstructures and oxygen permeation in PSiMA–IPN–PMPC hydrogel: a molecular simulation study , 2012 .

[12]  Alexander D. MacKerell,et al.  Computational Fragment-Based Binding Site Identification by Ligand Competitive Saturation , 2009, PLoS Comput. Biol..

[13]  Dor Ben-Amotz,et al.  Unraveling water's entropic mysteries: a unified view of nonpolar, polar, and ionic hydration. , 2008, Accounts of chemical research.

[14]  T. Cheatham,et al.  Determination of Alkali and Halide Monovalent Ion Parameters for Use in Explicitly Solvated Biomolecular Simulations , 2008, The journal of physical chemistry. B.

[15]  Sandeep Patel,et al.  Hydration free energies of monovalent ions in transferable intermolecular potential four point fluctuating charge water: an assessment of simulation methodology and force field performance and transferability. , 2007, The Journal of chemical physics.

[16]  B. Roux,et al.  Absolute hydration free energy scale for alkali and halide ions established from simulations with a polarizable force field. , 2006, The journal of physical chemistry. B.

[17]  Gerrit Groenhof,et al.  GROMACS: Fast, flexible, and free , 2005, J. Comput. Chem..

[18]  D. Ben‐Amotz,et al.  New mean-energy formulae for free energy differences , 2005 .

[19]  G. Graziano.  Water: cavity size distribution and hydrogen bonds , 2004 .

[20]  Benoît Roux,et al.  Grand canonical Monte Carlo simulations of water in protein environments. , 2004, The Journal of chemical physics.

[21]  Pengyu Y. Ren,et al.  Ion solvation thermodynamics from simulation with a polarizable force field. , 2003, Journal of the American Chemical Society.

[22]  Alexander D. MacKerell,et al.  All-atom empirical potential for molecular modeling and dynamics studies of proteins. , 1998, The journal of physical chemistry. B.

[23]  P. Attard.  A grand canonical simulation technique for dense and confined fluids with application to a Lennard-Jones fluid , 1997 .

[24]  Ronald M. Levy,et al.  On Finite-Size Corrections to the Free Energy of Ionic Hydration , 1997 .

[25]  Mihaly Mezei,et al.  Simulated Annealing of Chemical Potential: A General Procedure for Locating Bound Waters. Application to the Study of the Differential Hydration Propensities of the Major and Minor Grooves of DNA , 1996 .

[26]  T. Hansson,et al.  On the Validity of Electrostatic Linear Response in Polar Solvents , 1996 .

[27]  Gerhard Hummer,et al.  Free Energy of Ionic Hydration , 1996 .

[28]  T. Darden,et al.  A smooth particle mesh Ewald method , 1995 .

[29]  J. Aqvist,et al.  A new method for predicting binding affinity in computer-aided drug design. , 1994, Protein engineering.

[30]  Benoît Roux,et al.  Molecular basis for the Born model of ion solvation , 1990 .

[31]  Hoover,et al.  Canonical dynamics: Equilibrium phase-space distributions. , 1985, Physical review. A, General physics.

[32]  S. Nosé.  A molecular dynamics method for simulations in the canonical ensemble , 1984 .

[33]  W. L. Jorgensen,et al.  Comparison of simple potential functions for simulating liquid water , 1983 .

[34]  M. Parrinello,et al.  Polymorphic transitions in single crystals: A new molecular dynamics method , 1981 .

[35]  Mihaly Mezei,et al.  A cavity-biased (T, V, μ) Monte Carlo method for the computer simulation of fluids , 1980 .

[36]  Charles H. Bennett,et al.  Efficient estimation of free energy differences from Monte Carlo data , 1976 .

[37]  D. J. Adams,et al.  Chemical potential of hard-sphere fluids by Monte Carlo methods , 1974 .