Install#
System Requirements#
Installation Instructions#
Step 1: Download and install Anaconda (https://www.anaconda.com/products/individual) or Miniconda (https://docs.conda.io/en/latest/miniconda.html) Python distribution.
Step 2: Create the conda environment with MD DaVis dependencies. Open a Terminal or Anaconda prompt (on Windows) and issue the following command:
conda env create djmaity/md-davis
This creates a conda environment called md-davis
with all
required dependencies.
Step 3: Activate the md-davis
environment with:
conda activate md-davis
Step 4: Install MD DaVis in this environment with pip:
pip install md-davis
Step 5: Obtain the external dependencies as stated below.
Installation for Development#
Step 1: Download and install Anaconda (https://www.anaconda.com/products/individual) or Miniconda (https://docs.conda.io/en/latest/miniconda.html) Python distribution.
Step 2: Create the conda environment with MD DaVis dependencies. In this case, you should use:
conda env create djmaity/md-davis-dev
This would create a conda environment called md-davis-env
with
the core dependencies and install additional libraries for packaging,
documentation, and linting. You can also change the name of the conda
environment by modifying the command above:
conda env create djmaity/md-davis-dev --name my_env
This will name the conda environment to my_env
. Make sure that
there are no other conda environments with the same name.
The djmaity/md-davis-dev
in the above commands uses the environment files
uploaded to https://anaconda.org/djmaity/environments. These are the same files
environment.yml
and dev_environment.yml
in the source code, which may also be used to create the conda environment and
install the dependencies:
conda env create --file dev_environment.yml
See https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html to learn more about conda environments.
Note
We recommend using the environment files over installing the dependencies individually because installing all the dependencies together allows conda to resolve the appropriate version of packages to install and avoid package conflicts.
Step 3: Activate the conda environment with:
conda activate md-davis-dev
Remember to change md-davis-dev
to the appropriate environment name if
you modify it.
Step 4: Obtain a copy of the source code by cloning the public repository:
git clone git@github.com:djmaity/md-davis.git
Or, download the tarball:
curl -OL https://github.com/djmaity/md-davis/tarball/master
Step 5: Once you have a copy of the source, it can be installed with:
pip install path/to/source/code
The path to the directory containing the setup.py
file has to be provided in
the command above. You may want to install it as an editable package with:
pip install -e path/to/source/code
This will allow changes to the source code to be immediately reflected in the installed package.
Or, go to the directory containing the setup.py
file and use:
python setup.py install
You can also install the development version directly with:
pip install https://github.com/djmaity/md-davis/archive/master.zip
Step 6: Obtain the external dependencies as stated below.
External Dependencies#
GROMACS#
Currently, most analyses have to be performed with GROMACS, and the output is provided to MD DaVis for visualization. We have successfully used MD DaVis on simulations and analysis performed with various GROMACS versions from 5.1.4 to 2021.3. Other analysis tools may be used as long as the input to MD DaVis can be appropriately formatted. See Interfacing MD DaVis to Other Analysis Tools.
DSSP#
The secondary structure of a trajectory is calculated by the GROMACS tool
do_dssp
, which requires DSSP.
The latest and only available version of
DSSP is 2.3.0.
The executable is called mkdssp
now. Help GROMACS find it by any of the
following means:
Rename
mkdssp
todssp
Make a symlink called
dssp
tomkdssp
Set the
DSSP
environment
PyMOL#
You do not need to obtain PyMOL separately if you use the installation methods
outlined above using conda
. Unfortunately, PyMOL is not available in the
python package index. Therefore, it cannot be
automatically installed with pip
. However, Open-Source PyMOL and
Commercial/Educational PyMOL are available in conda channels
conda-forge
and schrodinger, respectively.
Open-Source PyMOL#
The command in Step 2 automatically installs Open-Source PyMOL available from conda-forge. It can also be installed with:
conda install -c conda-forge pymol-open-source=2.5.0
Warning
Open-Source PyMOL 2.4.0 has a bug where it cannot open Gaussian cube files. DelPhi to output phimap volumetric data is in this format, which is used in the electrostatics calculations.
Alternatively, on Linux, PyMOL can be installed with the system package
manager, e.g., apt
in Ubuntu or dnf
in Fedora. However, it is not
possible to install PyMOL into a virtual environment using this method.
Therefore, MD DaVis must be installed in the system python, which may
create conflicts with existing python packages on which many system programs
may depend.
On Windows, if you are not using conda
, then pre-built Open-Source PyMOL
can be downloaded from
Christoph Gohlke’s page
distributing unofficial windows binaries for python extension packages.
However, we have faced issues with using this package with other dependencies
of MD DaVis.
Commercial/Educational PyMOL#
The Commercial/Educational PyMOL can be used instead of Open-Source PyMOL by installing the md-davis-pymol or md-davis-pymol-dev environment in Step 2 of the above-mentioned installation methods:
conda env create djmaity/md-davis-pymol
Alternatively, it can be installed with:
conda install -c schrodinger pymol-bundle
DelPhi and MSMS#
Python dependencies are automatically installed. However, the electrostatics calculation requires the following two programs, which must be obtained separately.
Delphi C++ version greater than or equal to 8.1
Uninstall#
MD DaVis can be easily uninstalled like any other python package, with:
pip uninstall md-davis
As with any python package, this does not remove the dependencies installed by MD DaVis. That is why installing MD DaVis in a conda environment is recommended. Then, the whole conda environment may be entirely removed without affecting other python packages on the system.
conda env remove --name md-davis
where md-davis
is the name of the conda environment. Modify the command
to provide the appropriate name for the conda environment if you change it.
Note
On Linux, if MD DaVis was installed as root or with sudo
(highly
discouraged), the uninstall command should also be run with sudo
.