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Scripts to create ComDYN 'Common Constrains Dynamics' elastic network for use with the MARTINI coarse-grained forcefield (and any other elastic network application) for when large conformational changes need to be sampled

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    These scripts and datafiles are provided as-is, and come without 
    any warranty whatsoever. If it works for you, great, let me know!
    If it doesn't work for you, we'd be happy to try and help you fix it. 
    If it destroys your universe, too bad (you may still file a bug report).
 
    PLEASE CITE:
    
    Halima Mouhib, Akiko Higuchi, Sanne Abeln, 
    Kei Yura, K. Anton Feenstra. 
    "Showing the impact of pathogenic mutations of the glucose
     transporter (GLUT1) on the channel dynamics using ComDYN"
    F1000, submitted (2019).
    
    :ETIC ESAELP
    

    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with this program.  If not, see <http://www.gnu.org/licenses/>.
    
newest version(s) available from:
https://github.com/ibivu/ComDYN.git 
 
An overview of the simulation setup, data processing and plotting can be found 
in: "Showing the impact of pathogenic mutations of the glucose transporter 
(GLUT1) on the channel dynamics using ComDYN" by Halima Mouhib, Akiko 
Higuchi, Sanne Abeln, Kei Yura, K. Anton Feenstra. F1000, submitted (2019).

A description of specialized scripts used in the simulation setup and 
detailed data processing can be found in the Supporting Methods:
https://github.com/ibivu/ComDYN/blob/master/F1000_Supporting_Methods_Feenstra.pdf


Most scripts depend on a particular organisation and naming of
the input files, which is not described here in detail.
Generally, it on the lines of '1PDB_SIM_MUT_#....'. '1PDB' can be 
either of 4ZW9 or 5EQI. 'SIM' can be 'AT', 'CG' or 'CON', for atomistic, 
coarse-grained, and common constraints cg dynamics, respectively.
'MUT' can be 'WT' or a mutant like 'G91V', and '#' is the index
number of the replicate simulations (here, 2 to 6).

make_d1d2_plots
- uses plot_d1d2.py to create plots for all selected
  TM pairs for WTs and all mutants.

calc_hist_shifts
- uses calc_overap.py to get overlap and shifts for all
  TM pair distances, and summarizes in table

calc_overlap.py
- calculates overlap and shift between distributions 
  (histograms) from two xvg input files (identical bin sets
  are assumed).
  depends on numpy, optparse, vararg (see below)

plot_d1d2.py
- reads pairs of xvg files from 'gmx mindist', for
  the 'in' and 'out' distances of selected TM pairs.
  Plots countours of density using KDE.
  Depends on scipy.stats, matplotlib, optparse, numpy, vararg (see below)

vararg.py
- small package for callback function to be used with OptionParser
  to allow multiple arguments for one option on the commandline.
  Used by calc_overlap.py and plot_d1d2.py

make_plots
- using the output files of run_mindist, creates
  eps and pdf plots using xmgrace

run_mindist
4zw9_mkndx_helix_dists.in
5eqi_mkndx_helix_dists.in
- the run_mindist scripts uses both 'in' files to create sets 
  of atoms corresponding to the residue ranges in the 'in' file, 
  using 'gmx make_ndx'. Residue ranges correspond to first and 
  last 10 residues of the TM helices. 
  For selected pairs, 'gmx mindist' is then used to obtain the 
  shortest distance between those, for each frame of the input 
  trajectories. Then, makes histograms for individual trajectories,
  as well as combining the replicates per WT and mutant.
  All filenames are hardcoded.

cgxlate.sed:
- simple sed script to translate MARTINI bead names in a PDB
  file from the simulation, into regular protein sidechain
  atom names, such as CA, CB, CG, CD. This allows for easy
  visualization in any generic protein viewer.
  
mkhist.py
- creates 1d histograms from input file by simple binning
  (depends on sys and math)

filter_conserved_rubbers.awk
- removes all elastic network interactions from the input
  gromacs topology (.itp) file, that do not correspond to
  the supplied list of residue pairs

get_conserved_rubbers.awk:
- extracts common 'conserved' elastic network constraints 
  interactions that differ less than a set threshold distance 
  (default 1A) between two input gromacs topology (.itp) files 
  with MARTINI moleculetype definitions

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Scripts to create ComDYN 'Common Constrains Dynamics' elastic network for use with the MARTINI coarse-grained forcefield (and any other elastic network application) for when large conformational changes need to be sampled

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