Functional Mode Analysis

References

[1] J. S. Hub and B. L. de Groot
Detection of Functional Modes in Protein Dynamics
PLoS Comput. Biol. 5 (2009) pp. e1000480 (pdf)

[2] T. Krivobokova, R. Briones, J. S. Hub, A. Munk and B. L. de Groot
Partial Least-Squares Functional Mode Analysis: Application to the Membrane Proteins AQP1, Aqy1, and CLC-ec1
Biophys. J. 103 (2012) pp. 786-796 (pdf)

Description

The software is an implementation of Functional Mode Analysis (FMA) based on Partial least squares (PLS) regression, as described in [2]. For the (older) Principal Component (PCA) based version, please visit this page.

The implementation has also been submitted to the GROMACS repository and should be included in the upcomming 5.1 release version. In that case, please use the version distributed with GROMACS, as it will most likely be newer than the one found on this page.

Downloads

  • Source code (26MB)
  • Installation

    The source code is based on the current (September 2014) master branch of the GROMACS git, and can be build as described here. In most cases, the following sequence of commands (in the directory where g_fma-beta.tar.gz has been downloaded to) should compile the tool:

    tar -xfz g_fma-beta.tar.gz
    cd g_fma-beta
    mkdir build
    cd build
    cmake .. -DGMX_BUILD_OWN_FFTW=ON
    make
    sudo make install

    The binary versions have been compiled from the source on a 64bit SuSE Linux system and might or might not execute correctly on other Linux Systems.

    Usage

    Functional mode analysis is part of the gmx toolkit and can be called using

    gmx fma [options]

    A help page is available using the option -h. fma requires at least a reference structure, a trajectory file and a text file containing a table of target values for each frame in the trajectory in two or three columns. If two columns are given, the first is the time for each value and the second is the target value. If a third column exists, it is used to classify the frames as either ignored (0), part of the training set (1) or part of the validation set (2).

    The output of the tool is similar to the output of the covar module implemented in GROMACS and hence can be interpreted by the anaeig module.

    Disclaimer

    Please note that the software is distributed with NO WARRANTY OF ANY KIND. The author is not responsible for any losses or damages suffered directly or indirectly from the use of the software. Use it at your own risk.

    Please send your bug reports, comments and suggestions to: jpeters@mpibpc.mpg.de.