Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.
Languages: English
Types: Article

Classified by OpenAIRE into

arxiv: Quantitative Biology::Biomolecules
The dynamics of peptides and proteins generated by classical molecular dynamics (MD) is described by using a Markov model. The model is built by clustering the trajectory into conformational states and estimating transition probabilities between the states. Assuming that it is possible to influence the dynamics of the system by varying simulation parameters, we show how to use the Markov model to determine the parameter values that preserve the folded state of the protein and at the same time, reduce the folding time in the simulation. We investigate this by applying the method to two systems. The first system is an imaginary peptide described by given transition probabilities with a total folding time of 1 micros. We find that only small changes in the transition probabilities are needed to accelerate (or decelerate) the folding. This implies that folding times for slowly folding peptides and proteins calculated using MD cannot be meaningfully compared to experimental results. The second system is a four residue peptide valine-proline-alanine-leucine in water. We control the dynamics of the transitions by varying the temperature and the atom masses. The simulation results show that it is possible to find the combinations of parameter values that accelerate the dynamics and at the same time preserve the native state of the peptide. A method for accelerating larger systems without performing simulations for the whole folding process is outlined.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] Y. Sugita and Y. Okamoto. Replica-exchange molecular dynamics method for protein folding. Chemical Physics Letters, 314(1-2):141{151, 1999.
    • [2] X. Periole and A. E. Mark. Convergence and sampling e±ciency in replica exchange simulations of peptide folding in explicit solvent. Journal of Chemical Physics, 126(1):11, 2007.
    • [3] A. Baumketner and J. E. Shea. The thermodynamics of folding of a beta hairpin peptide probed through replica exchange molecular dynamics simulations. Theoretical Chemistry Accounts, 116(1-3):262{273, 2006.
    • [4] K. P. Ravindranathan, E. Gallicchio, R. A. Friesner, A. E. McDermott, and R. M. Levy. Conformational equilibrium of cytochrome p450bm-3 complexed with n-palmitoylglycine: A replica exchange molecular dynamics study. Journal of the American Chemical Society, 128(17):5786{5791, 2006.
    • [5] D. Hamelberg, J. Mongan, and J. A. McCammon. Accelerated molecular dynamics: A promising and e±cient simulation method for biomolecules. Journal of Chemical Physics, 120(24):11919{11929, 2004.
    • [6] A. F. Voter. Hyperdynamics: Accelerated molecular dynamics of infrequent events. Physical Review Letters, 78(20):3908{3911, 1997.
    • [7] A. F. Voter. A method for accelerating the molecular dynamics simulation of infrequent events. Journal of Chemical Physics, 106(11):4665{4677, 1997.
    • [8] N. Singhal, C. D. Snow, and V. S. Pande. Using path sampling to build better markovian state models: Predicting the folding rate and mechanism of a tryptophan zipper beta hairpin. Journal of Chemical Physics, 121(1):415{425, 2004.
    • [9] G. Jayachandran, V. Vishal, and V. S. Pande. Using massively parallel simulation and markovian models to study protein folding: Examining the dynamics of the villin headpiece. Journal of Chemical Physics, 124(16), 2006.
    • [10] W. C. Swope, J. W. Pitera, and F. Suits. Describing protein folding kinetics by molecular dynamics simulations. 1. theory. Journal of Physical Chemistry B, 108(21):6571{6581, 2004.
    • [11] C. H. Jensen, D. Nerukh, and R. C. Glen. Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory. Journal of Chemical Physics, 128(11):115107, 2008.
    • [12] D. Van der Spoel, E. Lindahl, B. Hess, G. Groenhof, A. E. Mark, and H. J. C. Berendsen. Gromacs: Fast, °exible, and free. Journal of Computational Chemistry, 26(16):1701{1718, 2005.
    • [13] B. Hess and N. F. A. van der Vegt. Hydration thermodynamic properties of amino acid analogues: A systematic comparison of biomolecular force ¯elds and water models. Journal of Physical Chemistry B, 110(35):17616{17626, 2006.
    • [14] C. Oostenbrink, T. A. Soares, N. F. A. van der Vegt, and W. F. van Gunsteren. Validation of the 53a6 gromos force ¯eld. European Biophysics Journal with Biophysics Letters, 34(4):273{284, 2005.
    • [15] C. Oostenbrink, A. Villa, A. E. Mark, and W. F. Van Gunsteren. A biomolecular force ¯eld based on the free enthalpy of hydration and solvation: The gromos force-¯eld parameter sets 53a5 and 53a6. Journal of Computational Chemistry, 25(13):1656{1676, 2004.
    • [16] H. J. C. Berendsen, J. P. M. Postma, W. F. van Gunsteren, A. DiNola, and J. R. Haak. Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics, 81(8):3684{3690, 1984.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article