About Normal Modes Calculations and Analysis at bioinfo.no

The server is meant to provide users with simple and automated computation and analysis of low-frequency normal modes for proteins. The computation performed through our server should help users understand whether their proteins undergo large amplitude movements, and thus decide if it is worthwhile performing a complete study with more thorough analysis. Analysis tools provided here have been described and successfully applied in Reuter et al., Biophys.J., 2003.

The force field used for computing the normal modes is the C-alpha force field (Hinsen et al.,Chem.Phys., 2000). It uses only the C-alpha atoms of the protein which are assigned the masses of the whole residue they represent. Since a coarse-grained model is employed, we find it appropriate to interpret frequencies and energies on relative scales and therefore report them normalized and without units.

Analysis tools available are: deformation energies of each mode, eigenvalues, calculation of normalized squared atomic displacements (results are provided for each low frequency mode, either as raw data or as plots with displacement vs. residue number), calculation of normalized squared fluctuations (results are provided for all non-trivial modes, either as raw data or as plots with fluctuations vs. residue number), interactive visualization of the modes using vector field representation or vibrations, the correlation matrix (results are provided for all non-trivial modes, either as raw data or a plot the correlated motion of each residue vs. every other residue in the system and a script to visualise some of the correlations on the input structure).

For comparing the intrinsic dynamics of related proteins, the web server also offers comparative analyses of protein structures. Analyses available for this purpose are: comparisons of fluctuation profiles and deformation energy profiles of two or more proteins, and quantification of the similarity of the low-energy coof the proteins by the following similarity measures, Root Mean Squared Inner Product and the Bhattacharyya Coefficient ( Fuglebakk et al., Bioinformatics, 2012).

If you use WEBnm@ in your research, please do cite the following publication:
Tiwari SP, Fuglebakk E, Hollup SM, Skjærven L, Cragnolini T, Grindhaug SH, Tekle KM, Reuter N. WEBnm@ v2.0: Web server and services for comparing protein flexibility. BMC Bioinformatics. 2014; 15:427

WEBnm@ v. 1.0 was first reported in the following publication:
Hollup SM, Sælensminde G, Reuter N. WEBnm@: a web application for normal mode analysis of proteins BMC Bioinformatics. 2005 Mar 11; 6:52