monster.bib

@String{BTacr   = "Acc. Chem. Res."}
@String{BTacb   = "Act. Cryst. B."}
@String{BTacd   = "Act. Cryst. D."}
@String{BTacp   = "Adv. Chem. Phys."}
@String{BTang	= "Angew. Chemie"}
@String{BTarbb	= "Annu. Rev. Biophys. Biomol. Struct."}
@String{BTarbbc = "Annu. Rev. Biophys. Biophys. Chem."}
@String{BTarbc	= "Annu. Rev. Biochem."}
@String{BTarbp	= "Annu. Rev. Biophys."}
@String{BTarpc	= "Annu. Rev. Phys. Chem."}
@String{BTarp	= "Annu. Rev. Physiol."}
@String{BTarchbb= "Arch. Bioch. Bioph."}
@String{BTbba	= "Biochim. Biophys. Acta"}
@String{BTbcb	= "Biochem. Cell. Biol."}
@String{BTbbpc  = "Ber. Bunsenges. Phys. Chem."}
@String{BTbbrc	= "Biochem. Biophys. Res. Comm."}
@String{BTbioch	= "Biochemistry"}
@String{BTbiopc	= "Bioph. Chem."}
@String{BTbj	= "Biophys. J."}
@String{BTbiop	= "Biopolymers"}
@String{BTbi	= "Bioch. Int."}
@String{BTbmbi	= "Biochem. Mol. Biol. Int."}
@String{BTcb	= "Curr. Biol."}
@String{BTcosb	= "Curr. Opin. Struct. Biol."}
@String{BTcpc	= "Comp. Phys. Comm."}
@String{BTcpl	= "Chem. Phys. Lett."}
@String{BTcp	= "Chem. Phys."}
@String{BTcr	= "Chem. Rev."}
@String{BTcsr	= "Chem. Soc. Rev."}
@String{BTejb	= "Eur. J. Biochem."}
@String{BTebj	= "Eur. Biophys. J."}
@String{BTfaseb = "FASEB J."}
@String{BTfebs	= "FEBS Lett."}
@String{BTijqc	= "Int. J. Quant. Chem."}
@String{BTijpp	= "Int. J. Pept. Prot. Res."}
@String{BTisrjc	= "Isr. J. Chem."}
@String{BTjacs	= "J. Am. Chem. Soc."}
@String{BTjapl  = "J. Appl. Crystallogr."}
@String{BTjaplp = "J. Appl. Phys."}
@String{BTjbc	= "J. Biol. Chem."}
@String{BTjbnmr	= "J. Biomol. NMR"}
@String{BTjbsd	= "J. Biomol. Struct. Dyn."}
@String{BTjcaid	= "J. Comp. Aid. Mol. Design"}
@String{BTjcc	= "J. Comp. Chem."}
@String{BTjced  = "J. Chem. Eng. Data"}
@String{BTjcomp	= "J. Comp. Phys."}
@String{BTjcp	= "J. Chem. Phys."}
@String{BTjcsft = "J. Chem. Soc. Far. Trans."}
@String{BTjctc  = "J. Chem. Theory Comp."}
@String{BTjmb	= "J. Mol. Biol."}
@String{BTjmag  = "J. Magn. Reson."}
@String{BTjmagb = "J. Magn. Reson. Ser. B"}
@String{BTjmm	= "J. Mol. Mod."}
@String{BTjmst	= "J. Mol. Struct. (THEOCHEM)"}
@String{BTjms	= "J. Mol. Struct."}
@String{BTjpa	= "J. Phys. A."}
@String{BTjpc	= "J. Phys. Chem."}
@String{BTjpca	= "J. Phys. Chem. A."}
@String{BTjpcb	= "J. Phys. Chem. B."}
@String{BTlang  = "Langmuir"}
@String{BTmph	= "Mol. Phys."}
@String{BTmcb	= "Mol. Cell. Bioch."}
@string{BTmie   = "Methods in Enyzmology"}
@String{BTmsim	= "Mol. Sim."}
@String{BTnature= "Nature"}
@String{BTnsb	= "Nature Struct. Biol."}
@String{BTpeng	= "Prot. Eng."}
@String{BTpnas	= "Proc. Natl. Acad. Sci. USA"}
@String{BTpr	= "Phys. Rev."}
@String{BTpra	= "Phys. Rev. {\bf A}"}
@String{BTprb	= "Phys. Rev. {\bf B}"}
@String{BTpre	= "Phys. Rev. {\bf E}"}
@String{BTprl	= "Phys. Rev. Lett."}
@String{BTprot	= "PROTEINS: Struct. Funct. Gen."}
@String{BTpsci	= "Prot. Sci."}
@String{BTsci   = "Science"}
@String{BTstr	= "Structure"}
@String{BTtchim	= "Theor. Chim. Acta."}
@String{BTtibs	= "Trends Biochem. Sci."}
@String{BTtibtech= "Trends Biotech."}

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@Book{Allen87,
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@MastersThesis{Bekker87,
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@InCollection{Bekker92,
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@InProceedings{Bekker93a,
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@Article{Bekker95,
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  year =         "1981",
  pages =        "331--342",
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  journal =      BTjcp,
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@InCollection{Berendsen84b,
  author = 	 {H. J. C. Berendsen and W. F. van Gunsteren},
  title = 	 {Molecular Dynamics Simulations: Techniques and Approaches},
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  publisher =	 {Reidel},
  year =	 1984,
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@Proceedings{Berendsen86a,
  title =        "Molecular-Dynamics Simulations of
                 Statistical-Mechanical Systems",
  year =         "1986",
  editor =       "G. Ciccotti and W. G. Hoover",
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@InProceedings{Berendsen86b,
  author =       "H. J. C. Berendsen and W. F. van Gunsteren",
  title =        "Practical Algorithms for Dynamics Simulations",
  year =         "1986",
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@Article{Berendsen87,
  author =       "H. J. C. Berendsen and J. R. Grigera and T. P.
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@InCollection{Berendsen91,
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  booktitle =    "Computer Simulations in Material Science",
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  publisher =    "Kluwer",
  year =         "1991",
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@InCollection{Berendsen93a,
  author =       "H. J. C. Berendsen",
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  title =        "Electrostatic interactions",
  publisher =    "ESCOM",
  year =         "1993",
  editor =       "W. F. van Gunsteren and P. K. Weiner and A. J.
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  pages =        "161--181",
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@Article{Berendsen93b,
  author =       "H. J. C. Berendsen and J. Mavri",
  title =        "Quantum Simulation of Reaction Dynamics by Density
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  journal =      BTjpc,
  year =         "1993",
  volume =       "97",
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@InCollection{Berendsen94,
  author =       "Herman J. C. Berendsen and David van der Spoel",
  booktitle =    "Aspects of Computational Science",
  title =        "Molecular Dynamics simulations",
  publisher =    "National Computing Facilities Foundation",
  address =      "P.O. Box 93120, 2509 AC Den Haag, The Netherlands",
  year =         "1994",
  editor =       "Aad van der Steen",
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@Article{Berendsen95a,
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@InCollection{Caflisch94,
  author =       "Amadeo Caflisch and Martin Karplus",
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  publisher =    "Birkh{\"a}user",
  year =         "1994",
  editor =       "Kenneth M. {Merz Jr.} and Scott M. {Le Grand}",
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@Article{Berendsen95b,
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@Manual{Buuren94a,
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@Proceedings{Buuren94b,
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@Article{Eastwood2010,
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% J. Chem. Theory Comput., Articles ASAP (As Soon As Publishable)
% Publication Date (Web): May 24, 2010 (Article)
% DOI: 10.1021/ct9002916


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values for 


Since $\dEdq \approx$ 

therefore $\xi$ should be about three orders of magnitude
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$\frac{\partial P}{\partial C_{12}} > 0,
\frac{\partial E}{\partial C_6}    < 0$ and
$\frac{\partial E}{\partial q}	   < 0$.
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@Article{Bush2006a,
   author  = {I. J. Bush and I. T. Todorov and W. Smith},
  title   = {A DAFT DL_POLY1 distributed memory adaptation of the smoothed particle mesh Ewald method},
  journal = {Comput. Phys. Commun.},
  volume  = {175},
  year    = {2006},
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  OPTabstract = {The Smoothed Particle Mesh Ewald method [U. Essmann, L. Perera, M.L.
Berkowtz, T. Darden, H. Lee, L.G. Pedersen, J. Chem. Phys. 103 (1995)
8577] for calculating long ranged forces in molecular simulation has
been adapted for the parallel molecular dynamics code DL_POLY_3 [I.T.
Todorov, W. Smith, Philos. Trans. Roy. Soc. London 362 (2004) 18351,
making use of a novel 3D Fast Fourier Transform (DAFT) [ I.J. Bush, The
Daresbury Advanced Fourier transform, Daresbury Laboratory, 19991 that
perfectly matches the Domain Decomposition (DD) parallelisation
strategy [W. Smith, Comput. Phys. Comm. 62 (1991) 229; M.R.S. Pinches,
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Phys. Comm. 62 (1991) 217] of the DL_POLY_3 code. In this article we
describe software adaptations undertaken to import this functionality
and provide a review of its performance. (C) 2006 Elsevier B.V. All
rights reserved.
0010-4655}
}

@Article{Masella2006a,
   author  = {M. Masella},
  title   = {The multiple time step r-RESPA procedure and polarizable potentials based on induced dipole moments},
  journal = {Mol. Phys.},
  volume  = {104},
  year    = {2006},
  pages   = {415-428},
  OPTabstract = {In the present study, we present an accelerating scheme based on the
reversible multiple time step r-RESPA method to be used in molecular
dynamics simulations with polarizable potentials based on induced
dipole moments. Even if the induced dipoles are estimated with an
iterative self-consistent procedure, this scheme significantly reduces
the CPU time needed to perform a molecular dynamics simulation, up to a
factor 2, as compared to the Car-Parrinello method where additional
dynamical variables are introduced for the treatment of the induced
dipoles. The tests show that stable and reliable molecular dynamics
trajectories can be generated with that scheme, and that the physical
properties derived from the trajectories are equivalent to those
computed with the classical all atom iterative approach and the
Car-Parrinello one.
0026-8976}
}

@Article{Wang2005a,
   author  = {W. Wang and R. D. Skeel},
  title   = {Fast evaluation of polarizable forces},
  journal = {J. Chem. Phys.},
  volume  = {123},
  year    = {2005},
  pages   = {164107},
  OPTabstract = {Polarizability is considered to be the single most significant
development in the next generation of force fields for biomolecular
simulations. However, the self-consistent computation of induced atomic
dipoles in a polarizable force field is expensive due to the cost of
solving a large dense linear system at each step of a simulation. This
article introduces methods that reduce the cost of computing the
electrostatic energy and force of a polarizable model from about 7.5
times the cost of computing those of a nonpolarizable model to less
than twice the cost. This is probably sufficient for the routine use of
polarizable forces in biomolecular simulations. The reduction in
computing time is achieved by an efficient implementation of the
particle-mesh Ewald method, an accurate and robust predictor based on
least-squares fitting, and non-stationary iterative methods whose fast
convergence is accelerated by a simple preconditioner. Furthermore,
with these methods, the self-consistent approach with a larger timestep
is shown to be faster than the extended Lagrangian approach. The use of
dipole moments from previous timesteps to calculate an accurate initial
guess for iterative methods leads to an energy drift, which can be made
acceptably small. The use of a zero initial guess does not lead to
perceptible energy drift if a reasonably strict convergence criterion
for the iteration is imposed. (c) 2005 American Institute of Physics.
0021-9606}
}

@Article{Izaguirre2005a,
   author  = {J. A. Izaguirre and S. S. Hampton and T. Matthey},
  title   = {Parallel multigrid summation for the N-body problem},
  journal = {J. Parallel Distrib. Comput.},
  volume  = {65},
  year    = {2005},
  pages   = {949-962},
  OPTabstract = {An Theta(n) parallel multigrid summation method (MG) for the N-body
problem is presented. The method was originally devised for vacuum
boundary conditions. Here, it is extended to periodic boundary
conditions and implemented in parallel using force decomposition and
MPI. MG is based on a hierarchical decomposition of computational
kernels on multiple grids. For low accuracy calculations, appropriate
for molecular dynamics, a sequential implementation is as fast or
faster than particle mesh Ewald (PME). Our parallel implementation is
more scalable than PME. The method can be combined with multiple time
stepping integrators to produce a powerful simulation protocol for
simulation of biological molecules and other materials. The parallel
implementation is tested on both a Linux cluster with Myrinet
interconnect and a shared memory computer. It is available as
open-source at http://protomol.sourceforge.net. An auxiliary tool
allows the automatic selection of optimal parameters for MG, and is
available at http://mdsimaid.cse.nd.edu. (c) 2005 Elsevier Inc. All
rights reserved.
0743-7315}
}

@Article{Crocker2005a,
   author  = {M. S. Crocker and S. S. Hampton and T. Matthey and J. A. Izaguirre},
  title   = {MDSIMAID: Automatic parameter optimization in fast electrostatic algorithms},
  journal = {J. Comput. Chem.},
  volume  = {26},
  year    = {2005},
  pages   = {1021-1031},
  OPTabstract = {MDSIMAID is a recommender system that optimizes parallel Particle Mesh
Ewald (PME) and both sequential and parallel multigrid (MG) summation
fast electrostatic solvers. MDSIMAID optimizes the running time or
parallel scalability of these methods within a given error tolerance.
MDSIMAID performs a run time constrained search on the parameter space
of each method starting from semiempirical performance models.
Recommended parameters are presented to the user. MDSIMAID'S
optimization of MG leads to configurations that are up to 14 times
faster or 17 times more accurate than published recommendations.
Optimization of PME can improve its parallel scalability, making it run
twice as fast in parallel in our tests. MDSIMAID and its Python source
code are accessible through a Web portal located at
http://mdsimaid.cse.nd.edu. (c) 2005 Wiley Periodicals, Inc.
0192-8651}
}

@Article{Germain2005a,
   author  = {R. S. Germain and Y. Zhestkov and M. Eleftheriou and A. Rayshubskiy and F. Suits and T. J. C. Ward and B. G. Fitch},
  title   = {Early performance data on the Blue Matter molecular simulation framework},
  journal = {IBM J. Res. Dev.},
  volume  = {49},
  year    = {2005},
  pages   = {447-455},
  OPTabstract = {Blue Matter is the application framework being developed in conjunction
with the scientific portion of the IBM Blue Gene(&REG;) project. We
describe the parallel decomposition currently, being used to target the
Blue Gene/L machine and discuss the application-based trace tools used
to analyze the performance of the application. We also present the
resuits of early performace studies, including a comparison of the
performance of the Ewald and the particle-particle particle-mesh (P3ME)
methods, compare the measured performance of some key collective
operations with the limitations imposed by the hardware, and discuss
some future directions for research.
0018-8646}
}

@Article{Peter2002a,
   author  = {C. Peter and W. F. van Gunsteren and P. H. Hunenberger},
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  volume  = {116},
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  OPTabstract = {An iterative algorithm based on fast Fourier transforms is proposed to
solve the Poisson equation for systems of heterogeneous permittivity
(e.g., solute cavity in a solvent) under periodic boundary conditions.
The method makes explicit use of the dipole-dipole interaction tensor,
and is thus easily generalizable to arbitrary forms of electrostatic
interactions (e.g., Coulomb's law with straight or smooth cutoff
truncation). The convergence properties of the algorithm and the
influence of various model parameters are investigated in detail, and a
set of appropriate values for these parameters is determined. The
algorithm is further tested by application to three types of systems (a
single spherical ion, two spherical ions, and small biomolecules), and
comparison with analytical results (single ion) and with results
obtained using a finite-difference solver under periodic boundary
conditions. The proposed algorithm performs very well in terms of
accuracy and convergence properties, with an overall speed comparable
in the current implementation to that of a typical finite-difference
solver. Future developments and applications of the algorithm will
include: (i) the assessment of periodicity- and cutoff-induced
artifacts in explicit-solvent simulations; (ii) the design of new
electrostatic schemes for explicit-solvent simulations mimicking more
accurately bulk solution; (iii) a faster evaluation of solvation free
energies based on continuum electrostatics in cases where
periodicity-induced artifacts can be neglected. (C) 2002 American
Institute of Physics.
0021-9606}
}

@Article{Beckers1998a,
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  volume  = {20},
  year    = {1998},
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  OPTabstract = {We describe results obtained from a new implementation of Hockney's
Particle-Particle Particle-Mesh (PPPM) method for evaluation of Coulomb
energies and forces in simulations of charged particles. Rather than
taking the usual approach, solving Poisson's equation by means of a
Fourier transformation, we use an iterative Poisson solver. In a
molecular dynamics (MD) simulation the solution from the previous
time-step provides a good starting point for the next solution. This
reduces the number of iterations per time-step to acceptable values.
The iterative scheme has a complexity O(N), and, in contrast with the
Fourier transform based approach, it is easily implemented on a
parallel architecture with a minimum of communication overhead.
We examine the origin of the errors in the algorithm and find that
reasonable accuracies in the Coulomb interaction can best be attained
by making the charge density profile as smooth as possible. This
involves spreading the particle charges over a large number of grid
points. Assigning these charges then becomes the most time consuming
part of the algorithm. We show how we can then gain a considerable
saving in computing time by employing a diffusion equation as a charge
spreading mechanism.
The effect of employing the algorithm with an accuracy less than that
typically tolerated in an Ewald summation is studied by computing, from
an MD simulation of silica, quantities that are sensitive to the long
range part of the Coulomb interaction. These results are compared to
full Ewald sum reference simulations and found to be within the
statistical error.
0892-7022}
}

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