psico.nma

Normal mode calculation using external apps or libraries.

  1. 2011-2012 Thomas Holder, MPI for Developmental Biology

License: BSD-2-Clause

Functions

normalmodes_pdbmat(selection[, cutoff, ...])

PDBMAT and DIAGRTB wrapper

normalmodes_prody(selection[, cutoff, ...])

Anisotropic Network Model (ANM) analysis with ProDy.

parse_eigenfacs([filename, readmax])

psico.nma.normalmodes_pdbmat(selection, cutoff=10.0, force=1.0, mass='COOR', first=7, last=10, choose='LOWE', substruct='RESI', blocksize=4, exe='pdbmat', diag_exe='diagrtb', prefix='mode', states=7, factor=-1, clean=1, quiet=1, async_=-1, *, _self=..., **kwargs)[source]

PDBMAT and DIAGRTB wrapper

Runs “pdbmat” and “diagrtb” and generates perturbed models for modes “first” to “last”. WARNING: May run for a long time.

PDBMAT computes the mass-weighted second derivatives energy matrix, using Tirion’s model, that is, an elastic network model (ENM). In such models, close particles (atoms) are linked by springs.

http://ecole.modelisation.free.fr/modes.html

Notes

Only considers ATOM records, if your model contains MSE residues or ligands that you want to consider, prepare it like this: mse2met (all) # for MSE residues alter (hetatm), type=’ATOM’ # for any hetatm

Arguments

selection = string: atom selection

cutoff = float: interaction distance cutoff in angstroem {default: 10}

force = float: interaction force constant {default: 1.0}

mass = string: origin of mass values {default: COOR}

first = int: first mode to create perturbed model {default: 7}

last = int: last mode to create perturbed model {default: 10}

choose = string: eigenvalues chosen {default: LOWE}

substruct = string: type of substructuring {default: RESI}

blocksize = int: nb of residues per block {default: 4}

psico.nma.normalmodes_prody(selection, cutoff=15, first=7, last=10, guide=1, prefix='prody', states=7, factor=-1, quiet=1, *, _self=...)[source]

Anisotropic Network Model (ANM) analysis with ProDy.

Based on: http://www.csb.pitt.edu/prody/examples/dynamics/enm/anm.html

psico.nma.parse_eigenfacs(filename='diagrtb.eigenfacs', readmax=20)[source]