An online platform for identifying and visualizing electron and hole transfer pathways in proteins.
The software enables automated robust identification of possible electron or hole transfer channels in proteins based on their crystal structures. The model is based on the coarse-grained version of the Pathways model and is aimed at capturing electron/hole hopping between the side chains of aromatic amino acids. A specified protein crystal structure is used to build a pairwise distance map between aromatic residue side chains (nodes). The application searches for the shortest path connecting a user-defined source node to one of the surface-exposed residues or a user-defined target node. For more details, please refer to the manual or the quick start guide.

Primary citation:
R.N. Tazhigulov, J.R. Gayvert, M. Wei, and K.B. Bravaya, eMap: A Web Application for Identifying and Visualizing Electron or Hole Hopping Pathways in Proteins. J. Phys. Chem. B, 2019, 123, 6946

What is going on?
10/01/2019 eMap 1.1 and PyeMap, open-source eMap backend, are both released!
We added long-awaited automatic identification of inorganic clusters (iron-sulfur and others), improved identification and drawing of aromatic moieties, fixed several bugs, and significantly improved eMap performance.

PyeMap is an open-source Python package, available on GitHub. It is intended to serve as a backend for eMap web application, and as a standalone package. Please report any bugs and make feature requests on GitHub. For issues exlcusive to the eMap web application, please click Contact Us.
We also greatly encourage users to contribute by making pull requests on GitHub.

Follow us on Twitter to stay tuned!
07/31/2019 eMap got its paper published in the Journal of Physical Chemistry B!
05/20/2019 Penalty Function Parameters can now be tuned (see "Advanced" tab in the Parameters). In the report, "Distance" has been replaced by the "Score".
10/01/2018 eMap has been officially released!