Welcome to DynaMine!

Try DynaMine out, submit your sequence here!

DynaMine is a fast predictor of protein backbone dynamics using only sequence information as input. Given a protein sequence, DynaMine predicts backbone flexibility at the residue-level in the form of backbone N-H S2 order parameter values. These S2 values represent how restricted the movement of the atomic bond vector is with respect to the molecular reference frame. A value of 1 means complete order (stable conformation), while a value of 0 means fully random bond vector movement (highly dynamic).
DynaMine has been trained on backbone N-H S2 order parameter values that have been directly estimated from experimentally determined NMR chemical shifts. Although it is based on a simple linear regression approach, DynaMine is able to accurately distinguish regions of different structural organization within proteins, such as folded domains and disordered linkers of different sizes. Additionally, it can identify disordered regions within proteins with an accuracy comparable to the most sophisticated existing disorder predictors. Remarkably, DynaMine achieves this high performance without depending on prior disorder knowledge or three-dimensional structural information, which makes it a unique approach on the field as well as providing independent proof of the relationship between dynamics and structural disorder in protein regions.
Finally, the predicted values have a clear physical meaning: they are relevant on an absolute scale and go beyond the binary classification of the predicted residues as ordered or disordered, so allowing for direct dynamics comparisons between protein regions.

How to cite DynaMine

  • The method

    Elisa Cilia, Rita Pancsa, Peter Tompa, Tom Lenaerts, and Wim Vranken
    From protein sequence to dynamics and disorder with DynaMine
    Nature Communications 4:2741 doi: 10.1038/ncomms3741 (2013)

  • The web-server

    Elisa Cilia, Rita Pancsa, Peter Tompa, Tom Lenaerts, and Wim Vranken
    The DynaMine webserver: predicting protein dynamics from sequence
    Nucleic Acid Research doi: 10.1093/nar/gku270 (2014)


Interuniversity Institute of Bioinformatics in Brussels

Interuniversity Institute of Bioinformatics in Brussels

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