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

Ruslan Tazhigulov acknowledges support from the Molecular Sciences Software Institute under National Science Foundation grant ACI-1547580.
Ruslan Tazhigulov would like to thank Dr. Doaa Altarawy for valuable discussions during the development of eMap application.
Melissa Wei was supported under Boston University RISE Internship Program.

The website is hosted on Massachusetts Open Cloud with support from Rafik B. Hariri Institute for Computing and Computational Science & Engineering.

Third-Party Applications, Components, and Frameworks used:
PDB parser
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Bootstrap, Flask, Flask Table, jQuery, NumPy, PyGraphviz, RDKit, SciPy, Select2, ViewerJS