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Visualisation of conformational space restriction by distance restraints

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DisVis

DOI

About DisVis

DisVis is a Python package and command line tool to visualize and quantify the accessible interaction space of distance restrained binary biomolecular complexes. It performs a full and systematic 6 dimensional search of the three translational and rotational degrees of freedom to determine the number of complexes consistent with the restraints. In addition, it outputs the percentage of restraints being violated and a density that represents the center-of-mass position of the scanning chain corresponding to the highest number of consistent restraints at every position in space.

Requirements

  • Python2.7
  • NumPy

Optional for faster CPU version

  • FFTW3
  • pyFFTW

For GPU hardware acceleration the following packages are also required

Recommended for installation

Installation

If the requirements are met, DisVis can be installed by opening a terminal and typing

git clone https://github.com/haddocking/disvis.git
cd disvis
python setup.py install

The last command might require administrator priviliges for system wide installation. After installation, the command line tool disvis should be at your disposal.

If you are starting from a clean system, then read the installation instructions below to prepare your particular operating system. The INSTALLATION.md file contains instructions for accessing GPU acceleration on MacOSX.

Linux

First install git and check whether the Python header files and the Python package manager pip, are available by typing

sudo apt-get install git python-dev python-pip

If you are working on a Fedora system, replace apt-get with yum. The final step to prepare you system is installing the Python dependencies

sudo pip install numpy cython

Wait untill the installation is finished. Your system is now ready. Follow the general instructions above to install DisVis.

MacOSX

First install git for MacOSX (this might already be present on your system) by either installing it from the website or using brew

brew install git

Next, install pip, the official Python package manager. Either follow the link and install pip using their installation instructions or open a terminal and type

sudo easy_install pip

The final step to prepare your system, is installing the Python dependencies. In a terminal, type

sudo pip install numpy cython

Wait till the compilation and installation is finished. Your system is now properly prepared. Follow the general instructions above to install DisVis.

Windows

First install git for Windows, as it also comes with a handy bash shell.

For Windows it easiest to install a Python distribution with NumPy and Cython (and many other) packages included, such as Anaconda. Follow the installation instructions on their website.

Next open a bash shell that was shipped with git. Follow the general instructions above to install DisVis.

Usage

The general pattern to invoke disvis is

disvis <pdb1> <pdb2> <distance-restraints-file>

where <pdb1> is the fixed chain, <pdb2> is the scanning chain and <distance-restraints-file> is a text-file containing the distance restraints in the following format

 <chainid 1> <resid 1> <atomname 1> <chainid 2> <resid 2> <atomname 2> <mindis> <maxdis>

As an example

A 18 CA F 27 CB 10.0 20.0

This puts a distance restraint between the CA-atom of residue 18 of chain A of pdb1 and the CB-atom of residue 27 of chain F of pdb2 that should be longer than or equal to 10A and smaller than or equal to 20A. Comments can be added by starting the line with the pound sign (#) and empty lines are ignored.

Options

To get a help screen with available options and explanation type

disvis --help

Some examples to get you started. To perform a 5.27 degree rotational search and store the results in the directory results/

disvis 1wcm_A.pdb 1wcm_E.pdb restraints.dat -a 5.27 -d results

Note that the directory is created if it doesn't exist.

To perform a 9.72 degree rotational search with 16 processors and a voxel spacing of 2A

disvis O14250.pdb Q9UT97.pdb restraints.dat -a 9.72 -p 16 -vs 2

To offload computations to the GPU (if the requirements are met) and increase the maximum allowed volume of clashes as well as the minimum required volume of interaction, and set the interaction radius to 2A

disvis 1wcm_A.pdb 1wcm_E.pdb restraints.dat -g -cv 6000 -iv 7000 -ir 2

To perform a grid occupancy analysis for complexes consistent with at least N restraints, include the -oa or --occupancy-analysis flag to the command. By default, the analysis is only performed on complexes consistent with either all and all - 1 restraints. If you want to perform an occupancy analysis for complexes consistent with a lower number of restraints, use the -ic or --interaction-restraints-cutoff option, followed by the minimum number of required consistent restraints. Thus the command

disvis 1wcm_A.pdb 1wcm_E.pdb restraints.dat -oa -ic 5

will make an occupancy grid for complexes consistent with at least 5 restraints, and higher.

Finally, to perform an interaction analysis to determine which residues are most likely at the interface, the -is or --interaction-selection options can be used with an additional file giving the residue numbers of the receptor and ligand for which the interaction analysis will be performed. The input file consists of two lines, where the two lines are a space separated sequence of residue numbers for the receptor and ligand, respectively. As the interaction analysis is particularly expensive, only complexes consistent with all, or all - 1 are considered. To lower the barrier, the -ic option can again be used. Also limit the selected residues to only the solvent accessible ones. A simple example for the selection-file

1 2 3 4
101 302 888

This will select residue numbers 1, 2, 3, and 4 for the receptor, and 101, 302, and 888 for the ligand.

Output

Standard disvis outputs 5 files:

  • accessible_complexes.out: a text file containing the number of complexes consistent with a number of restraints.
  • violations.out: a text file showing how often a specific restraint is violated for each number of consistent restraints. This helps in identifying which restraint is most likely a false-positive if any.
  • accessible_interaction_space.mrc: a density file in MRC format. The density represents the center of mass of the scanning chain conforming to the maximum found consistent restraints at every position in space. The density can be inspected by opening it together with the fixed chain in a molecular viewer (UCSF Chimera is recommended for its easier manipulation of density data, but also PyMol works).
  • z-score.out: a text file giving the Z-score for each restraint. The higher the score, the more likely the restraint is a false-positive. Z-scores above 1.0 are explicitly mentioned in the output.
  • disvis.log: a log file showing all the parameters used, together with date and time indications.

If an occupancy and/or interaction analysis was requested, disvis also outputs the following files:

  • occupancy_N.mrc: a volume file giving a normalized indication of how frequent a grid point is occupied by the ligand, where N indicates the minimal required number of consistent restraints that resulted in the occupancy grid.
  • [receptor|ligand]_interactions.txt: a text file containing the average number of interactions per complex each selected residue made, for both the receptor and ligand molecule. Each column denotes the minimal number of consistent restraints of each complex for which interactions were counted.

Licensing

If this software was useful to your research please cite us

Van Zundert, G.C.P. and Bonvin, A.M.J.J. (2015) DisVis: Visualizing and quantifying accessible interaction space of distance restrained biomolecular complexes. Bioinformatics 31, 3222-3224.

Apache License Version 2.0

The elements.py module is licenced under the MIT License, Copyright Christoph Gohlke.

Tested platforms

Operating System CPU single CPU multi GPU
Linux Yes Yes Yes
MacOSX Yes Yes No
Windows Yes Fail No

The GPU version has been tested on: NVIDIA GeForce GTX 680 and AMD Radeon HD 7730M for Linux