WaterNetworkAnalysis

.. image:: https://readthedocs.org/projects/waternetworkanalysis/badge/?version=latest :target: https://waternetworkanalysis.readthedocs.io/en/latest/?badge=latest .. image:: https://badge.fury.io/py/WaterNetworkAnalysis.svg :target: https://badge.fury.io/py/WaterNetworkAnalysis .. image:: https://img.shields.io/conda/vn/conda-forge/waternetworkanalysis.svg :target: https://anaconda.org/conda-forge/waternetworkanalysis

The WaterNetworkAnalysis (WNA) Python package serves as a set of tools for input preparation and further analysis for ConservedWaterSearch <https://conservedwatersearch.readthedocs.io/en/latest/>__ (CWS) python package which identifies conserved water molecules from Molecular Dynamics (MD) trajectories.

.. image:: https://raw.githubusercontent.com/JecaTosovic/WaterNetworkAnalysis/master/docs/source/figs/Scheme.png :width: 600

Important links

- `Documentation <https://waternetworkanalysis.readthedocs.io/en/latest/>`_: hosted on Read The Docs
- `GitHub repository <https://github.com/JecaTosovic/WaterNetworkAnalysis>`_: source code/contribute code
- `Issue tracker <https://github.com/JecaTosovic/WaterNetworkAnalysis/issues>`_: Report issues/ request features

Related Tools

- `ConservedWaterSearch <https://github.com/JecaTosovic/ConservedWaterSearch>`__: Analysis of conserved waters from simulation trajectories. For docs see `here <https://conservedwatersearch.readthedocs.io/en/latest/>`__.

Citation

For citations and more infromation see ConservedWaterSearch citation <https://conservedwatersearch.readthedocs.io/en/latest/citing.html>_.

Installation of the Python package

The easiest ways to install WaterNetworkAnalysis is using :code:conda from conda-forge:

.. code:: bash

conda install -c conda-forge WaterNetworkAnalysis

Alternatively, WNA is also available on PyPi via :code:pip:

.. code:: bash

pip install WaterNetworkAnalysis

Pymol <https://pymol.org/2/>__ is an optional dependency for visualisation and is not present on PyPi, however WNA can be installed and used without it (bar pymol visualisation features). Pymol can be installed using :code:conda:

.. code:: bash

conda install -c conda-forge pymol-open-source

For more information on CWS dependencies also see CWS installation guide <https://conservedwatersearch.readthedocs.io/en/latest/installation.html>__.

Installation of the PyMOL plugin

See documentation for detailed instructions <https://waternetworkanalysis.readthedocs.io/en/latest/quickstart.html#installation-of-the-pymol-plugin>__.

Known Issues with dependencies

:code:AttributeError: 'super' object has no attribute '_ipython_display_' Some versions of Jupyter notebook are incpompatible with ipython (see here <https://stackoverflow.com/questions/74279848/nglview-installed-but-will-not-import-inside-juypter-notebook-via-anaconda-navig>__). To resolve install version of :code:ipywidgets<8 using :code:conda:

.. code:: bash

conda install "ipywidgets <8" -c conda-forge

or :code:pip:

.. code:: bash

pip install ipywidgets==7.6.0

Example

The following example shows how to use WaterNetworkAnalysis to prepare a MD trajectory and analyse the results for determination of conserved water networks.

.. code:: python

from WaterNetworkAnalysis import align_trajectory from WaterNetworkAnalysis import get_center_of_selection from WaterNetworkAnalysis import get_selection_string_from_resnums from WaterNetworkAnalysis import extract_waters_from_trajectory from ConservedWaterSearch.water_clustering import WaterClustering from ConservedWaterSearch.utils import get_orientations_from_positions

MD trajectory filename

trajectory="md.xtc"

topology filename

topology="md.gro"

aligned trajectory filename

alignedtrj = "aligned_trj.xtc"

aligned snapshot filename

aligned_snap = "aligned.pdb"

distance to select water molecules around

distance = 12.0

align the trajectory and save the alignment reference configuration

align_trajectory( trajectory=trajectory, topology=topology, align_target_file_name=aligned_snap, output_trj_file=alignedtrj, )

define active site by aminoacid residue numbers

active_site_resnums = [111, 112, 113, 122, 133, 138, 139, 142, 143, 157, 166, 167, 169, 170, 203, 231, 232, 238]

find centre of the active site in aligned trajectory

selection_centre = get_center_of_selection( get_selection_string_from_resnums(active_site_resnums), trajectory=alignedtrj, topology=topology, )

extract water coordinates of interest around selection centre

coordO, coordH = extract_waters_from_trajectory( trajectory=alignedtrj, topology=topology, selection_center=selection_centre, dist=distance )

start the clustering procedure

Nsnaps = 200 WC=WaterClustering(nsnaps=Nsnaps)

perform multi stage reclustering

WC.multi_stage_reclustering(*get_orientations_from_positions(coordO,coordH))

visualise results with pymol

WC.visualise_pymol(aligned_snap, active_site_ids=active_site_resnums, dist=distance)

.. image:: https://raw.githubusercontent.com/JecaTosovic/WaterNetworkAnalysis/master/docs/source/figs/Results.png :width: 600