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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.

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

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.

install tutorial/single_protein tutorial/mining reference bibliography cite credits

Indices and tables

  • genindex
  • modindex
  • search