Deformable Elastic Network (DEN)

At low resolution the number of experimental observables is usually smaller than the number of parameters. Overfitting thus becomes a major issue.

The main of the DEN approach is to refine only those degrees of freedom for wich the data provide information. For those degrees of freedom that are not defined by the data we use prior structural information.

Such prior information could e.g. come from a know X-ray structure in a different conformation or a homology model. This model is referred to here as the 'reference model'.

To balance prior information and data (density map) an elastic network is defined on the reference model, i.e. a number of harmonic restraints are defined between randomly chosen pairs of atoms that are within a distance range of typically 3 to 15 Å.

During the refinement the elastic network is allowed to deform, i.e. the equilibrium distances can (slowly) follow any changes during the refinement. This way the minimum of the elastic network potential moves. However, the equilibrium distances are attached by springs to the corresponding reference distances. The strength of these springs are defined by a parameter γ. A small γ-value keeps the structure close to the reference model and a large γ-value allows largers structural changes.

The figure below demonstrates the principle of the DEN method: ef-1