4.7.1.1. 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 [1].
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 [1]).
References
4.7.1.1.1. Analysis tasks
- class MDAnalysis.analysis.gnm.GNMAnalysis(universe, select='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.
select (str (optional)) – MDAnalysis selection string
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
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.
- results.times
simulation times used in analysis
- Type:
- results.eigenvalues
calculated eigenvalues
- Type:
- results.eigenvectors
calculated eigenvectors
- Type:
See also
Changed in version 0.16.0: Made
generate_output()
a private method_generate_output()
.Changed in version 1.0.0: Changed selection keyword to select
Changed in version 2.0.0: Use
AnalysisBase
as parent class and store results as attributestimes
,eigenvalues
andeigenvectors
of theresults
attribute.
- class MDAnalysis.analysis.gnm.closeContactGNMAnalysis(universe, select='protein', cutoff=4.5, ReportVector=None, weights='size')[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.
select (str (optional)) – MDAnalysis selection string
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
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.
- results.times
simulation times used in analysis
- Type:
- results.eigenvalues
calculated eigenvalues
- Type:
- results.eigenvectors
calculated eigenvectors
- Type:
Notes
The MassWeight option has now been removed.
See also
Changed in version 0.16.0: Made
generate_output()
a private method_generate_output()
.Deprecated since version 0.16.0: Instead of
MassWeight=True
useweights="size"
.Changed in version 1.0.0: MassWeight option (see above deprecation entry). Changed selection keyword to select
Changed in version 2.0.0: Use
AnalysisBase
as parent class and store results as attributestimes
,eigenvalues
andeigenvectors
of the results attribute.
4.7.1.1.2. 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 unused function backup_file()