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Computer simulation of the dynamics of biomolecules by the molecular dynamics (MD) technique yields the possibility of describing and understanding the structure-dynamics-function relationships of molecular processes in terms of interactions at the atomic level. Once the reliability of the molecular models, force fields and computational procedures has been established by comparison of simulated properties with known experimental ones, computer simulation can be a very powerful tool to predict molecular properties that are inaccessible to experimental probes. It provides a microscopic picture which may serve to explain observed behaviour of a molecular system.

Simulation of ligand, inhibitor or coenzyme binding opens the way to calculation and prediction of relative binding constants, which is in turn useful in drug design.

Another application is the simulation of DNA-repressor complexes, which gives insight at the atomic level in the possible mechanisms of protein-DNA recognition.

The prediction of energetic and structural changes caused by modification of amino acids in enzymes is of practical value for the engineering of proteins.

The prediction of the spatial structure of proteins using sequence homology with related proteins of known spatial structure would be very useful. The application of MD simulation to derive spatial structure based on atom-atom distance information obtained by NOE-NMR experiments, or based on structure factor amplitude information obtained by X-ray diffraction experiments has become a standard technique in the area of protein structure refinement.

Finally, Molecular Dynamics makes it possible to simulate biological membranes and the behaviour of proteins that are bound to or embedded in membranes.

The references to publications are coded according to the IGC MD publication list (PDF, 959 KB).

General Algorithmic Contributions

  • Use of constraints in biomolecular simulation [77.01]
  • Constant temperature and pressure MD [84.09]
  • Leap-frog algorithm for stochastic dynamics (SD) simulation [88.02]
  • A fast SHAKE algorithm to impose constraints [01.08]
  • A method to simulate proteins at constant pH [02.20]
  • A technique to impose flexible distance constraints [05.35]
  • Improved leap-frog kinetic energy expression [07.27]
  • A method to enforce bond-angle constraints [A656]
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Fri Jun 23 01:24:35 CEST 2017
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