Installation

Required Software

`Python`_ 3.10 or later. We recommend using Anaconda, which provides the conda package and environment manager as well as many useful packages.

`NumPy`_ 1.10 or later
SciPy - we recommend that you use the latest version, but all versions should be supported.

Biopython - we recommend that you use the latest version, but all versions should be supported.

When compiling from source, on Linux for example, you will need a C compiler (e.g. gcc) and Python developer libraries (i.e. python.h). If you don’t have Python developer libraries installed on your machine, use your package manager to install python-dev package.

In addition, `matplotlib`_ is required for using plotting functions. ProDy, ProDy Applications, and Evol Applications can be operated without this package.

Quick Install

We officially recommend installing through conda:

conda install -c conda-forge prody

Installing From Source (not recommended)

Linux

Download ProDy-x.y.z.tar.gz. Extract tarball contents and run setup.py as follows:

$ tar -xzf ProDy-x.y.z.tar.gz
$ cd ProDy-x.y.z
$ python setup.py build
$ python setup.py install

If you need root access for installation, try sudo python setup.py install. If you don’t have root access, please consult alternate and custom installation schemes in Installing Python Modules.

Mac OS

For installing ProDy, please follow the Linux installation instructions.

Recommended Software

`IPython`_ is a must have for interactive ProDy sessions.
PyReadline for colorful IPython sessions on Windows.
`MDAnalysis`_ or `MDTraj`_ for reading molecular dynamics trajectories.

Included in ProDy

Following software is included in the ProDy installation packages:

`pyparsing`_ is used to define the atom selection grammar.
Biopython KDTree package and pairwise2 module are used for distance based atom selections and pairwise sequence alignment, respectively.
argparse is used to implement applications and provided for compatibility with Python 2.6.
Scipy, when installed, replaces linear algebra module of Numpy. Scipy linear algebra module is more flexible and can be faster.

Source Code

Source code is available at https://github.com/prody/ProDy.