MinActionPath: maximum likelihood trajectory for large-scale structural transitions in a coarse-grained locally harmonic energy landscape

Nucleic Acids Res. 2007 Jul;35(Web Server issue):W477-82. doi: 10.1093/nar/gkm342. Epub 2007 Jun 1.

Abstract

The non-linear problem of simulating the structural transition between two known forms of a macromolecule still remains a challenge in structural biology. The problem is usually addressed in an approximate way using 'morphing' techniques, which are linear interpolations of either the Cartesian or the internal coordinates between the initial and end states, followed by energy minimization. Here we describe a web tool that implements a new method to calculate the most probable trajectory that is exact for harmonic potentials; as an illustration of the method, the classical Calpha-based Elastic Network Model (ENM) is used both for the initial and the final states but other variants of the ENM are also possible. The Langevin equation under this potential is solved analytically using the Onsager and Machlup action minimization formalism on each side of the transition, thus replacing the original non-linear problem by a pair of linear differential equations joined by a non-linear boundary matching condition. The crossover between the two multidimensional energy curves around each state is found numerically using an iterative approach, producing the most probable trajectory and fully characterizing the transition state and its energy. Jobs calculating such trajectories can be submitted on-line at: http://lorentz.dynstr.pasteur.fr/joel/index.php.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Amino Acid Sequence
  • Computational Biology / methods*
  • Computer Simulation
  • Energy Transfer*
  • Models, Biological
  • Models, Chemical*
  • Models, Molecular*
  • Models, Theoretical
  • Molecular Sequence Data
  • Protein Conformation
  • Protein Structure, Tertiary
  • Proteins / chemistry*
  • Software
  • Thermodynamics

Substances

  • Proteins