ORAC: A Molecular dynamics program to simulate complex molecular systems with realistic electrostatic interactions

In this study, we present a new molecular dynamics program for simulation of complex molecular systems. The program, named ORAC, combines state‐of‐the‐art molecular dynamics (MD) algorithms with flexibility in handling different types and sizes of molecules. ORAC is intended for simulations of molecular systems and is specifically designed to treat biomolecules efficiently and effectively in solution or in a crystalline environment. Among its unique features are: (i) implementation of reversible and symplectic multiple time step algorithms (or r‐RESPA, reversible reference system propagation algorithm) specifically designed and tuned for biological systems with periodic boundary conditions; (ii) availability for simulations with multiple or single time steps of standard Ewald or smooth particle mesh Ewald (SPME) for computation of electrostatic interactions; and (iii) possibility of simulating molecular systems in a variety of thermodynamic ensembles. We believe that the combination of these algorithms makes ORAC more advanced than other MD programs using standard simulation algorithms. © 1997 John Wiley & Sons, Inc. J Comput Chem 18: 1848–1862, 1997

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

[2]  K. Schmidt,et al.  Implementing the fast multipole method in three dimensions , 1991 .

[3]  Hans De Raedt,et al.  Applications of the generalized Trotter formula , 1983 .

[4]  B. Berne,et al.  MULTIPLE TIME SCALE METHODS FOR CONSTANT PRESSURE MOLECULAR DYNAMICS SIMULATIONS OF MOLECULAR SYSTEMS , 1994 .

[5]  B. Montgomery Pettitt,et al.  Ewald artifacts in liquid state molecular dynamics simulations , 1996 .

[6]  Mark E. Tuckerman,et al.  Explicit reversible integrators for extended systems dynamics , 1996 .

[7]  P. Kollman,et al.  An all atom force field for simulations of proteins and nucleic acids , 1986, Journal of computational chemistry.

[8]  Stephen K. Gray,et al.  Symplectic integrators for large scale molecular dynamics simulations: A comparison of several explicit methods , 1994 .

[9]  Leslie Greengard,et al.  A fast algorithm for particle simulations , 1987 .

[10]  H. C. Andersen.  Molecular dynamics simulations at constant pressure and/or temperature , 1980 .

[11]  H. G. Petersen.  Accuracy and efficiency of the particle mesh Ewald method , 1995 .

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

[13]  J. W. Humberston.  Classical mechanics , 1980, Nature.

[14]  S. Nosé,et al.  Constant pressure molecular dynamics for molecular systems , 1983 .

[15]  L. Verlet.  Computer "Experiments" on Classical Fluids. I. Thermodynamical Properties of Lennard-Jones Molecules , 1967 .

[16]  J. Banavar,et al.  Computer Simulation of Liquids , 1988 .

[17]  Michele Parrinello,et al.  Integrating the Car–Parrinello equations. I. Basic integration techniques , 1994 .

[18]  P. Kollman,et al.  A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules , 1995 .

[19]  Shuichi Nosé,et al.  Constant Temperature Molecular Dynamics Methods , 1991 .

[20]  Giovanni Ciccotti,et al.  Molecular dynamics simulation of rigid molecules , 1986 .

[21]  Mark E. Tuckerman,et al.  Molecular dynamics in systems with multiple time scales: Systems with stiff and soft degrees of freedom and with short and long range forces , 1991 .

[22]  R W Hockney,et al.  Computer Simulation Using Particles , 1966 .

[23]  J. Perram,et al.  Simulation of electrostatic systems in periodic boundary conditions. I. Lattice sums and dielectric constants , 1980, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[24]  D. J. Tildesley,et al.  Computer simulation in chemical physics, NATO ASI Series C , 1993 .

[25]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[26]  Mark E. Tuckerman,et al.  Molecular dynamics algorithm for multiple time scales: Systems with disparate masses , 1991 .

[27]  T. Darden,et al.  Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems , 1993 .

[28]  M. Klein,et al.  Nosé-Hoover chains : the canonical ensemble via continuous dynamics , 1992 .

[29]  Mark E. Tuckerman,et al.  Molecular dynamics algorithm for multiple time scales: Systems with long range forces , 1991 .

[30]  U. Singh,et al.  A NEW FORCE FIELD FOR MOLECULAR MECHANICAL SIMULATION OF NUCLEIC ACIDS AND PROTEINS , 1984 .

[31]  M. Karplus,et al.  SIMULATIONS OF MACROMOLECULES BY MULTIPLE TIME-STEP METHODS , 1995 .

[32]  Michele Parrinello,et al.  Integrating the Car–Parrinello equations. II. Multiple time scale techniques , 1994 .

[33]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[34]  Giovanni Ciccotti,et al.  Introduction of Andersen’s demon in the molecular dynamics of systems with constraints , 1983 .

[35]  Mark E. Tuckerman,et al.  Reversible multiple time scale molecular dynamics , 1992 .

[36]  P. P. Ewald.  Die Berechnung optischer und elektrostatischer Gitterpotentiale , 1921 .

[37]  B. Berne,et al.  A Multiple-Time-Step Molecular Dynamics Algorithm for Macromolecules , 1994 .

[38]  Aneesur Rahman,et al.  Correlations in the Motion of Atoms in Liquid Argon , 1964 .

[39]  S. Nosé.  A unified formulation of the constant temperature molecular dynamics methods , 1984 .

[40]  T. Darden,et al.  MOLECULAR DYNAMICS SIMULATION STUDIES OF A HIGH RESOLUTION Z-DNA CRYSTAL , 1995 .

[41]  P. Procacci,et al.  Taming the Ewald sum in molecular dynamics simulations of solvated proteins via a multiple time step algorithm , 1996 .

[42]  M. Parrinello,et al.  Crystal structure and pair potentials: A molecular-dynamics study , 1980 .

[43]  Minoru Saito,et al.  Molecular dynamics simulations of proteins in solution: Artifacts caused by the cutoff approximation , 1994 .

[44]  Piero Procacci,et al.  Computer simulation of solid C60 using multiple time‐step algorithms , 1994 .

[45]  Michael P. Allen,et al.  Computer simulation in chemical physics , 1993 .

[46]  J. Stewart.  Optimization of parameters for semiempirical methods II. Applications , 1989 .

[47]  Piero Procacci,et al.  A Very Fast Molecular Dynamics Method To Simulate Biomolecular Systems with Realistic Electrostatic Interactions , 1996 .

[48]  Giovanni Ciccotti,et al.  Molecular dynamics of rigid systems in cartesian coordinates: A general formulation , 1982 .