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Overview of PyeMap
=========================================================
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PyeMap is a python package aimed at automatic identification of electron and hole transfer
pathways in proteins. The analysis is based on a coarse-grained version of Beratan and
Onuchic’s Pathway model, and only accounts for through-space hopping between
aromatic residues side chains [Beratan1992]_. Side chains of aromatic residues and non-protein electron
transfer active moieties are modeled as vertices in a weighted graph, where the edge
weights are modified distance dependent penalty functions. 

For single proteins, PyeMap identifies the shortest pathways between a specified donor to the surface, or to 
a specified acceptor. For groups of proteins, PyeMap identifies shared pathways/motifs using graph 
mining techniques.

.. _RCSB: http://www.rcsb.org/

PyeMap serves as the backend for the web application eMap_, 
and can also be used as a fully functional Python package.

.. _eMap: http://emap.bu.edu/

Current Features
----------------

**Single protein**
   * Identification of most probable electron/hole transfer pathways from a specified donor to the protein surface or a specified electron/hole acceptor
   * Accepts valid .pdb or .cif structures provided by the user or fetched from RCSB_ database
   * Automatic detection of non-protein aromatic moieties such as porphyrins, nucleobases, and other aromatic cofactors
   * Automatic detection of 60+ inorganic clusters such as iron-sulfur clusters and others
   * Automatic detection of redox-active metal ions
   * User specified custom fragments
   * Visualization of chemical structures and graphs
   * Automatic identification of surface exposed residues using residue depth or solvent accessibility criteria
   * Control over various parameters which determine connectivity of graph theory model
   * Tested on structures as large as 5350 residues (51599 atoms)

**Graph Mining**
   * Mining families of protein graphs for all patterns up to a given support threshold
   * Mining families of protein graphs for specific patterns
   * Classification of protein subgraphs based on similarity


In Development
----------------
* Improving the physical model of electron transfer by incorporating information on geometry-dependent electronic couplings and site sensitive energetics
* Generalization to DNA, protein-DNA complexes etc.


.. toctree::
   :maxdepth: 1
   :caption: Contents:

   install
   tutorial/single_protein
   tutorial/mining
   reference
   bibliography
   cite
   credits


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`