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Effect of the Reaction Field on Molecular Forces and Torques Revealed by an Image-Charge Solvation Model

Published online by Cambridge University Press:  03 June 2015

Wei Song ,
Yuchun Lin ,
Andrij Baumketner ,
Shaozhong Deng ,
Wei Cai  and
Donald J. Jacobs
Wei Song*
Affiliation:
Departments of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28262, USA
Yuchun Lin*
Affiliation:
Departments of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, NC 28262, USA Departments of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28262, USA
Andrij Baumketner*
Affiliation:
Departments of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, NC 28262, USA On leave from Institute for Condensed Matter Physics, 1 Svientsitsky Str., Lviv 79011, Ukraine
Shaozhong Deng*
Affiliation:
Departments of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28262, USA
Wei Cai*
Affiliation:
Departments of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28262, USA
Donald J. Jacobs*
Affiliation:
Departments of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, NC 28262, USA
*
Email:[email protected]
Email:[email protected]
Email:[email protected]
Email:[email protected]
Email:[email protected]
Corresponding author.Email:[email protected]
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Abstract

We recently developed the Image-Charge Solvation Model (ICSM), which is an explicit/implicit hybrid model to accurately account for long-range electrostatic forces in molecular dynamics simulations [Lin et al., J. Chem. Phys., 131,154103,2009]. The ICSM has a productive spherical volume within the simulation cell for which key physical properties of bulk water are reproduced, such as density, radial distribution function, diffusion constants and dielectric properties. Although the reaction field (RF) is essential, it typically accounts for less than 2% of the total electrostatic force on a water molecule. This observation motivates investigating further the role of the RF within the ICSM. In this report we focus on distributions of forces and torques on water molecules as a function of distance from the origin and make extensive tests over a range of model parameters where Coulomb forces are decomposed into direct interactions from waters modeled explicitly and the RF. Molecular torques due to the RF typically account for 20% of the total torque, revealing why the RF plays an important role in the dielectric properties of simulated water. Moreover, it becomes clear that the buffer layer in the ICSM is essential to mitigate artifacts caused by the discontinuous change in dielectric constants at the explicit/implicit interface.

Keywords

61.20.Gy61.20.Ja41.20.Cv83.10.RsImage chargesreaction fieldforce distributiontorque distributiondipole moment
Type
Research Article
Information
Communications in Computational Physics , Volume 13 , Issue 1 , January 2013 , pp. 129 - 149
Copyright
Copyright © Global Science Press Limited 2013

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References

[1]Larsson, P., Hess, B., and Lindahl, E., Algorithm improvements for molecular dynamics sim-ulations, WIREs. Comput. Mol. Sci., 1, 93–108, 2011.Google Scholar
[2]Klepeis, J., Lindorff-Larsen, K., Dror, R., and Shaw, D., Long-timescale molecular dynamics simulations of protein structure and function, Curr. Opin. Struct. Biol., 19, 120–127, 2009.Google Scholar
[3]Gunsteren, W., Bakowies, D., Baron, R., Chandrasekhar, I., Christen, M., Daura, X., Gee, P., Geerke, D. P., Glattli, A., Hunenberger, P. H., Kastenholz, M. A., Oostenbrink, C., Schenk, M., Trzesniak, D., Vegt, N., and Yu, H. B., Biomolecular modeling: Goals, problems, perspectives, Angew. Chem. Int. Ed., 45, 4064–4092, 2006.Google Scholar
[4]Wang, J., Tan, C., Tan, Y., Lu, Q., and Luo, R., Poisson-Boltzmann solvents in molecular dynamics simulations, Commun. Comput. Phys., 3, 1010–1031, 2008.Google Scholar
[5]Roux, B., Implicit solvent models, in Computational Biochemistry and Biophysics, Dekker, O. M., MacKerell, A. D. Jr., Roux, B., Watanabe, M., Ed., New York, 133–150, 2001.Google Scholar
[6]Honig, B. and Nicholls, A., Classical electrostatics in biology and chemistry, Science, 268, 1144–1149, 1995.Google Scholar
[7]Baker, N. A., Improving implicit solvent simulations: A Poisson-centric view, Curr. Opin. Struct. Biol., 15, 137–143, 2005.Google Scholar
[8]Yu, Z., Jacobson, M. P., Josovitz, J.et al., First-shell solvation of ion pairs: Correction of systematic errors in implicit solvent models, J. Phys. Chem. B, 108, 6643–6654, 2004.Google Scholar
[9]Rubinstein, A. and Sherman, S., Influence of the solvent structure on the electrostatic interactions in proteins, Biophys. J., 87, 1544–1557, 2004.Google Scholar
[10]Allen, M. P. and Tildesley, D. J., Computer Simulation of Liquids, Oxford University Press, Oxford, 1987.Google Scholar
[11]Ewald, P. P., Die Berechnung optischer und elektrostatischer Gitterpotentiale, Ann. Phys, 369, 253–287, 1921.CrossRefGoogle Scholar
[12]Abagyan, R. and Totrov, M., Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins, J. Mol. Biol., 235, 983–1002, 1994.Google Scholar
[13]Essmann, U., Perera, L., Berkowitz, M., Darden, T., Lee, H., and Pedersen, L., A smooth particle mesh Ewald method, J. Chem. Phys., 103, 8577–8593, 1995.Google Scholar
[14]Darden, T. A., York, D. M., and Pedersen, L. G., Particle mesh Ewald: An Nlog(N) method for Ewald sums in large systems, J. Chem. Phys., 98, 10089–10092, 1993.Google Scholar
[15]Shimada, J., Kaneko, H., and Takada, T., Efficient calculations of coulombic interactions in biomolecular simulations with periodic boundary conditions, J. Comput. Chem., 14, 867–878, 1993.Google Scholar
[16]Luty, B., Davis, M., Tironi, I., and Gunsteren, W., A comparison of particle-particle, particlemesh and Ewald methods for calculating electrostatic interactions in periodic molecular systems, Mol. Simul., 14, 11–20, 1994.Google Scholar
[17]Greengard, L. and Rokhlin, V., A fast algorithm for particle simulations, J. Comput. Phys., 73, 325–348, 1987.Google Scholar
[18]Greengard, L., The Rapid Evaluation of Potential Fields in Particle Systems, MIT Press, Cambridge, 1988.Google Scholar
[19]Greengard, L. and Rokhlin, V., A new version of the Fast Multipole Method for the Laplace equation in three dimensions, Acta Numerica, 6, 229–269, 1997.CrossRefGoogle Scholar
[20]Gargallo, R., Hunenberger, P. H., Aviles, F. X., and Oliva, B., Molecular dynamics simulation of highly charged proteins: Comparison of the particle-particle particle-mesh and reaction field methods for the calculation of electrostatic interactions, Protein Sci., 12, 2161–2172, 2003.Google Scholar
[21]Lee, M., Salsbury, F., and Olson, M., An efficient hybrid explicit/implicit solvent method for biomolecular simulations, J. Comput. Chem., 25, 1967–1978, 2004.CrossRefGoogle ScholarPubMed
[22]Okur, A. and Simmerling, C., Hybrid explicit/implicit solvation methods, Ann. Rep. Comp. Chem., 2,97-109, 2006.Google Scholar
[23]Lee, M. S. and Olson, M. A., Evaluation of Poisson solvation models using a hybrid explicit/implicit solvent method, J. Phys. Chem. B, 109, 5223–5236, 2005.Google Scholar
[24]Kirkwood, J. G., Theory of solutions of molecules containing widely separated charges with special application to Zwitterions, J. Chem. Phys., 2, 351–361, 1934.CrossRefGoogle Scholar
[25]Lin, Y., Baumketner, A., Deng, S., Xu, Z., Jacobs, D. J., and Cai, W., An image-based reaction field method for electrostatic interactions in molecular dynamics simulations of aqueous solutions, J. Chem. Phys., 131, 154103, 2009.CrossRefGoogle ScholarPubMed
[26]Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., and Klein, M. L., Comparison of simple potential functions for simulating liquid water, J. Chem. Phys., 79, 926–935, 1983.Google Scholar
[27]Lin, Y., Baumketner, A., Song, W., Deng, S., Jacobs, D., and Cai, W., Ionic solvation studied by image-charge reaction field method, J. Chem. Phys., 134, 3530094,2011.Google Scholar
[28]Beglov, D. and Roux, B., Finite representation of an infinite bulk system: Solvent boundary potential for computer simulations, J. Chem. Phys.,100, 9050, 1994.Google Scholar
[29]Im, W., Berneche, S., and Roux, B., Generalized solvent boundary potential for computer simulations, J. Chem. Phys., 114, 2924, 2001.Google Scholar
[30]Bashford, D. and Case, D., Generalized Born models of macromolecular solvation effects, Ann. Rev. Phys. Chem., 51, 129–152, 2000.Google Scholar
[31]Kirkwood, J., Statistical mechanics of liquid solutions, Chem. Rev., 19, 275–307, 1936.Google Scholar
[32]Friedman, H., Image approximation to the reaction field, Mol. Phys., 29, 1533–1543, 1975.Google Scholar
[33]Tironi, I. G., Sperb, R., and Smith, P. E., Generalized reaction field method for molecular dynamics simulations, J. Chem. Phys., 102, 5451–5459, 1995.Google Scholar
[34]Morse, P. M. and Feshbach, H., Methods of Theoretical Physics, McGraw-Hill, New York, 1953.Google Scholar
[35]Neumann, C., Hydrodynamische untersuchen nebst einem anhang uber die probleme der elektrostatik und der magnetischen induktion, Teubner, Leipzig, 279, 1883.Google Scholar
[36]Finkelstein, A. V., Electrostatic interactions of charged groups in an aqueous medium and their effect on the formation of polypeptide chain secondary structure, Mol. Biol., 11, 811, 1977.Google Scholar
[37]Lindell, I. V., Electrostatic image theory for the dielectric sphere, Radio Sci., 27, 1–8, 1992.Google Scholar
[38]Norris, W. T., Charge images in a dielectric sphere, IEE Proc.: Sci., Meas. Technol., 142, 142150, 1995.Google Scholar
[39]Deng, S., Cai, W., and Jacobs, D. J., A comparable study of image approximations to the reaction field, Comput. Phys. Commun., 177, 689–699, 2007.Google Scholar
[40]Cai, W., Deng, S., and Jacobs, D. J., Extending the fast multipole method to charges inside or outside a dielectric sphere, J. Comput. Phys., 223, 846, 2007.Google Scholar
[41]Zhang, B., Huang, J., Pitsianis, N. P., and Sun, X., Revision of FMM-Yukawa: An adaptive fast multipole method for screened Coulomb interactions, Comput. Phys. Commun, 181, 2206–2207, 2010.Google Scholar
[42]Ying, L., Biros, G., and Zorin, D., A kernel-independent adaptive fast multipole algorithm in two and three dimensions, J. Comput. Phys., 196, 591–626, 2004.Google Scholar
[43]Huang, J., Jia, J., and Zhang, B., FMM-Yukawa: An adaptive fast multipole method for screened coulomb interactions, Comput. Phys. Commun, 180, 2331, 2009.Google Scholar
[44]Kastenholz, M. A. and Hunenberger, P. H., Computation of methodology-independent ionic solvation free energies from molecular simulations. II. The hydration free energy of the sodium cation, J. Chem. Phys., 124, 224501–224520, 2006.Google Scholar
[45]Kastenholz, M. A. and Hunenberger, P. H., Computation of methodology-independent ionic solvation free energies from molecular simulations. I. The electrostatic potential in molecular liquids, J. Chem. Phys., 124, 124106–124127, 2006.Google Scholar
[46]Ni, B. and Baumketner, A., Effect of atom-and group-based truncations on biomolecules simulated with reaction-field electrostatics, J. Mol. Model., 17, 2883–2893, 2011.Google Scholar
[47]Rodgersab, J. M. and Weeks, J. D., Interplay of local hydrogen-bonding and long-ranged dipolar forces in simulations of confined water, PNAS, 105, 19136–19141, 2008.Google Scholar
[48]Xu, Z., Deng, S., and Cai, W., Image charge approximations of reaction fields in solvents with arbitrary ionic strength, J. Comput. Phys., 228, 2092–2099, 2009.Google Scholar
[49]Ceruttia, D. S., Baker, N. A., and McCammon, J. A., Solvent reaction field potential inside an uncharged globular protein: A bridge between implicit and explicit solvent models?, J. Chem. Phys., 127, 155101–155112, 2007.Google Scholar