This is a repository of the MDavocado utility. It is a set of programes written in Python which enable quick visualization of Molecular dynamics trajectories. It can be considerred as an extension for the well known MDanalysis suite of programs.
The name is the acronym for: MD Analysis and Visualization Of Correlated Angular Diagrams.
The methodology behind MDavocado diagrams is explained in more detail in methodology.md. You can watch the presentation of MDavocado program held at PyCon DE & PyData Berlin 2024 here.
Perhaps the easiest way is start using MDavocado is to clone this repository, and then folow these simple steps.
First we make a clean new conda environment (here we have named this conda environment MDavocado, but you can call it anything you like). All the dependences will be installed from the packages file into that newly created conda environment.
# To exactly replicate this conda environment use this command:
conda create --name MDavocado --file packages.txtOnce this is done we activate the new environment.
# Activate new conda environment
conda activate MDavocadoNow that we are in the new environment we execute the command:
./MDavocado.py topology.file trajectory.fileThis will make a number of gif images named A.gif, B.gif ... Each one is a visual representation of the whole trajectory of one chain in your protein. It may take anywhere from few minutes for smaller trajectories, to a few hours for a long trajectories and bigger proteins, for this analysis to finish. That is it!
# Then we have to install [MDAnalysis](https://www.mdanalysis.org/).
conda config --add channels conda-forge
conda install mdanalysis
# List packages installed by MDAnalysis
conda list --export > packages.txt
# To exactly replicate this conda environment use this command:
conda create --name MDavocado --file packages.txtIf you would like to use change point detection then install Ruptures library. Anyway the main command imports this so we need to install it too.
conda install rupturesDatashader we deffinitely need to install as the ploting of avocado diagrams depends on it.
conda install datashaderTrying to import Datashader complains about Dask, so we install Dask too.
conda install daskThe development of this project is financed by Croatian Science Foundation under the project grant IP-2019-04-6764. It is a part of ALOKOMP project.
A detailed description of the methodology and usage of MDavocado has been published in the Journal of Chemical Information and Modeling in the paper titled MDavocado: Analysis and Visualization of Protein Motion by Time-Dependent Angular Diagrams (10.1021/acs.jcim.4c00650).