Moil: A Molecular Dynamics Program with Emphasis on Conformational Searches and Reaction Path Calculations

  • Ron Elber
  • Adrian Roitberg
  • Carlos Simmerling
  • Robert Goldstein
  • Gennady Verkhivker
  • Haiying Li
  • Alex Ulitsky
Part of the NATO ASI Series book series (NSSB, volume 325)


The field of computational biology has expanded considerably in the last few years. Insight to the dynamics of biomolecules, the design of new drugs and the interactions that lead to stability of macromolecules has been obtained. Crucial in bringing these changes was the introduction of “user friendly” computer programs so that the number of potential users expanded considerably. It is now possible to visualize complex molecules and to study their structure and thermodynamics properties. The strength of this approach and what makes it so attractive is the possibility of studying the behavior of a variety of molecules using essentially the same set of tools. Constructing a large number of molecules was made possible by the use of a data base of molecular pieces: Different molecules are described using common fragments. For example, all proteins are constructed from the same monomers — amino acids. Another example of repeating fragments is found in the base-pairs of DNA. The fragment solution is chemically intuitive, however, it is approximate. In general the intramolecular interactions in an amino acid are influenced by its neighborhood. For example the charge distribution is determined not only by the identity of the amino acid (as is usually assumed) but also by the solvent, the nearby amino acids and the specific conformation of the fragment. Nevertheless, this approximate approach has a number of successes that are documented in the literature1 and therefore not covered in this manuscript.


Free Energy Calculation Nonbonded Interaction Property File Exclusion List Coordinate File 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    U. Burkert and N.L. Allinger, “Molecular Mechanics”, ACS, Washington D.C., 1982.Google Scholar
  2. 2.
    S.J. Weiner, P.A. Kollman, D.A. Case, U.C. Singh, C. Ghio, G. Alagons, S. Profeta Jr. and P. Weiner, “A new force field for molecular mechanical simulatiori of nucleic acids and proteins”, J. Amer. Chem. Soc. 106: 765 (1984).CrossRefGoogle Scholar
  3. 3.
    B.R. Brooks, R.E. Bruccoleri, B.D. Olafson, D.J. States, S. Swaminathan and M. Karplus, “CHARMM: A program for macromolecular energy, minimization, and dynamics calculations”, J. of Comput. Chem. 4: 187 (1983).CrossRefGoogle Scholar
  4. 4.
    Groningen Molecular Simulation program manual, version GROM87, BIOMOS B.V. Groningen, The Netherland.Google Scholar
  5. 5.
    R. Czerminski and R. Elber, “Self avoiding walk between two fixed points as a tool to calculate reaction paths in large molecular systems”, Int. J. Quant. Chem. andthe Proc. of Sanibel Symposia 24: 167 (1990).CrossRefGoogle Scholar
  6. 6.
    A. Roitberg and R. Elber, “Modeling side chains in peptides and proteins: Application of the Locally Enhanced Sampling (LES) and the simulated annealing methods to find minimum energy conformations”, J. Chem. Phys. 95: 9277 (1991).CrossRefGoogle Scholar
  7. 7.
    W.L. Jorgensen and J. Tirado-Rives, “The OPLS potential function for proteins. Energy minimizations for crystals of cyclic peptides and crambin”, J. Amer. Chem. Soc. 110: 1657 (1988).CrossRefGoogle Scholar
  8. 8.
    E.E. Nikitin, “Theory of elementary atomic and molecular processes in gases”, (Clarendon, Oxford, 1974).Google Scholar
  9. 9.
    H. Li, R. Elber and J.E. Straub, “Molecular dynamics simulation of NO recombination to myoglobin mutants”, J. Biol. Chem., in press.Google Scholar
  10. 10.
    H.C. Anderson, “Rattle: A velocity version of the SHAKE algorithm for molecular dynamics simulations”, J. Comput. Physics, 52: 24 (1983).CrossRefGoogle Scholar
  11. 11.
    A. Ulitsky and R. Elber, “The equilibrium of the time dependent Hartree and the Locally Enhanced Sampling approximations: Formal properties, corrections and computational examples of rare gas clusters”, J. Chem. Phys. 98: 3380 (1993).CrossRefGoogle Scholar
  12. 12.
    R. Elber and M. Karplus, “Enhanced sampling in molecular dynamics: Use of the Time-Dependent Hartree approximation for a simulation of carbon monoxide diffusion through myoglobin”, J. Amer. Chem. Soc., 112: 9161 (1990).CrossRefGoogle Scholar
  13. 13.
    Chen Keaser, unpublished results.Google Scholar
  14. 14.
    R. Czerminski and R. Elber, “Computational studies of ligand diffusion in globins: I. leghemoglobin”, Proteins 10: 70 (1991).PubMedCrossRefGoogle Scholar
  15. 15.
    Q.H. Gibson, R. Regan, R. Elber, J.S. Olson and T.E. Carver, “Distal pocket residues affect picosecond recombination in myoglobin: An experimental and molecular dynamics study of position 29 mutants”, J. Biol. Chem. 267: 22022 (1992).PubMedGoogle Scholar
  16. 16.
    G. Verkhivker, R. Elber and W. Nowak, “Locally enhanced sampling in free energy calculations: Application of mean field approximation to accurate calculations of free energy differences”, J. Chem. Phys. 97: 7838 (1992).CrossRefGoogle Scholar
  17. 17.
    R. Czerminski and R. Elber, “Reaction path study of conformational transitions in flexible systems: Applications to peptides”, J. Chem. Phys. 92: 5580 (1990).CrossRefGoogle Scholar
  18. 18.
    J. Barker, “An algorithm for the location of transition states”, J. Comput. Chem. 7: 385 (1986).CrossRefGoogle Scholar
  19. 19.
    G. Verkhivker, R. Elber and Q.H. Gibson, “Microscopic modeling of ligand diffusion through the protein leghemoglobin: Computer simulations and experiments”, J. Amer. Chem. Soc. 114: 7866 (1992).CrossRefGoogle Scholar
  20. 20.
    R. Elber, “Calculations of the potential of mean force using molecular dynamics with linear constraints: An application to a conformational transition of a solvated dipeptide”, J. Chem. Phys. 93: 4312 (1990).CrossRefGoogle Scholar
  21. 21.
    R.H.J.M. Otten and L.P.P. van Ginneken, “The annealing algorithm”, Kluwer Academic, Boston, 1989.CrossRefGoogle Scholar
  22. 22.
    W. Nowak, R. Czerminski and R. Elber, “Reaction path study of ligand diffusion in proteins: Application of the SPW method to calculate reaction coordinate for the motion of the CO through leghemoglobin”, J. Amer. CHem. Soc. 113: 5627 (1991).CrossRefGoogle Scholar
  23. 23.
    A. Roitberg and R. Elber, “The locally enhanced sampling for side chain modeling”, a chapter in “Protein Structure Determination”, Ed. K. Merz and S. Le Grand, Ed., Springer Verlag, in press.Google Scholar

Copyright information

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Ron Elber
    • 2
  • Adrian Roitberg
    • 1
  • Carlos Simmerling
    • 1
  • Robert Goldstein
    • 1
  • Gennady Verkhivker
    • 1
  • Haiying Li
    • 1
  • Alex Ulitsky
    • 1
  1. 1.Dept. of ChemistryUniversity of Illinois at ChicagoChicagoUSA
  2. 2.Dept. of Physical ChemistryThe Fritz Haber Research Center and the Institute of Life Sciences, The Hebrew Univ. of JerusalemGivat Ram, JerusalemIsrael

Personalised recommendations