4.7.1. Elastic network analysis of MD trajectories — MDAnalysis.analysis.gnm

Author

Benjamin Hall <benjamin.a.hall@ucl.ac.uk>

Year

2011

Copyright

GNU Public License v2 or later

Analyse a trajectory using elastic network models, following the approach of [Hall2007].

An example is provided in the MDAnalysis Cookbook, listed as GNMExample.

The basic approach is to pass a trajectory to GNMAnalysis and then run the analysis:

u = MDAnalysis.Universe(PSF, DCD)
C = MDAnalysis.analysis.gnm.GNMAnalysis(u, ReportVector="output.txt")

C.run()
output = zip(*C.results)

with open("eigenvalues.dat", "w") as outputfile:
    for item in output[1]:
        outputfile.write(item + "\n")

The results are found in GNMAnalysis.results, which can be used for further processing (see [Hall2007]).

References

Hall2007(1,2)

Benjamin A. Hall, Samantha L. Kaye, Andy Pang, Rafael Perera, and Philip C. Biggin. Characterization of Protein Conformational States by Normal-Mode Frequencies. JACS 129 (2007), 11394–11401.

4.7.1.1. Analysis tasks

class MDAnalysis.analysis.gnm.GNMAnalysis(universe, selection='protein and name CA', cutoff=7.0, ReportVector=None, Bonus_groups=None)[source]

Basic tool for GNM analysis.

Each frame is treated as a novel structure and the GNM calculated. By default, this stores the dominant eigenvector and its associated eigenvalue; either can be used to monitor conformational change in a simulation.

Parameters

  • universe (Universe) – Analyze the full trajectory in the universe.

  • selection (str (optional)) – MDAnalysis selection string, default “protein and name CA”

  • cutoff (float (optional)) – Consider selected atoms within the cutoff as neighbors for the Gaussian network model.

  • ReportVector (str (optional)) – filename to write eigenvectors to, by default no output is written (None)

  • Bonus_groups (tuple) – This is a tuple of selection strings that identify additional groups (such as ligands). The center of mass of each group will be added as a single point in the ENM (it is a popular way of treating small ligands such as drugs). You need to ensure that none of the atoms in Bonus_groups is contained in selection as this could lead to double counting. No checks are applied. Default is None.

See also

closeContactGNMAnalysis

Changed in version 0.16.0: Made generate_output() a private method _generate_output().

generate_kirchoff()[source]

Generate the Kirchhoff matrix of contacts.

This generates the neighbour matrix by generating a grid of near-neighbours and then calculating which are are within the cutoff.

Returns

the resulting Kirchhoff matrix

Return type

array

run(start=None, stop=None, step=None)[source]

Analyze trajectory and produce timeseries.

Parameters

  • start (int (optional)) –

  • stop (int (optional)) –

  • step (int (optional)) –

Returns

  • results (list) –

    GNM results per frame:

    results = [(time,eigenvalues[1],eigenvectors[1]),(time,eigenvalues[1],eigenvectors[1])... ]

  • .. versionchanged:: 0.16.0 – use start, stop, step instead of skip

class MDAnalysis.analysis.gnm.closeContactGNMAnalysis(universe, selection='protein', cutoff=4.5, ReportVector=None, weights='size', MassWeight=None)[source]

GNMAnalysis only using close contacts.

This is a version of the GNM where the Kirchoff matrix is constructed from the close contacts between individual atoms in different residues.

Parameters

  • universe (Universe) – Analyze the full trajectory in the universe.

  • selection (str (optional)) – MDAnalysis selection string, default “protein”

  • cutoff (float (optional)) – Consider selected atoms within the cutoff as neighbors for the Gaussian network model [4.5 Å].

  • ReportVector (str (optional)) – filename to write eigenvectors to, by default no output is written (None)

  • weights ({"size", None} (optional)) – If set to “size” (the default) then weight the contact by \(1/\sqrt{N_i N_j}\) where \(N_i\) and \(N_j\) are the number of atoms in the residues \(i\) and \(j\) that contain the atoms that form a contact.

  • MassWeight (bool (deprecated, optional)) – if set to True equivalent to weights set to “size”.

Notes

The MassWeight option does not perform a true mass weighting but weighting by the number of atoms in each residue; the name of the parameter exists for historical reasons and will be removed in 0.17.0. Until then, setting MassWeight to anything but None will override weights.

See also

GNMAnalysis

Changed in version 0.16.0: Made generate_output() a private method _generate_output().

Deprecated since version 0.16.0: Instead of MassWeight=True use weights="size".

generate_kirchoff()[source]

Generate the Kirchhoff matrix of contacts.

This generates the neighbour matrix by generating a grid of near-neighbours and then calculating which are are within the cutoff.

Returns

the resulting Kirchhoff matrix

Return type

array

4.7.1.2. Utility functions

The following functions are used internally and are typically not directly needed to perform the analysis.

MDAnalysis.analysis.gnm.generate_grid(positions, cutoff)[source]

Simple grid search.

An alternative to searching the entire list of each atom; divide the structure into cutoff sized boxes This way, for each particle you only need to search the neighbouring boxes to find the particles within the cutoff.

Observed a 6x speed up for a smallish protein with ~300 residues; this should get better with bigger systems.

Parameters

  • positions (array) – coordinates of the atoms

  • cutoff (float) – find particles with distance less than cutoff from each other; the grid will consist of boxes with sides of at least length cutoff

MDAnalysis.analysis.gnm.order_list(w)[source]

Returns a dictionary showing the order of eigenvalues (which are reported scrambled normally)

Changed in version 0.16.0: removed un-unsed function backup_file()