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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Updated: May 1, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
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eMap 2.0: A Web-Based Platform for Identifying electron Transfer Pathways in Proteins and Protein Families.

James R Gayvert1, Alyssa J Kranc1, Ruslan N Tazhigulov1

  • 1Department of Chemistry Boston University Boston Massachusetts USA.

Wiley Interdisciplinary Reviews. Computational Molecular Science
|April 30, 2026
PubMed
Summary
This summary is machine-generated.

eMap 2.0 predicts electron transfer pathways in proteins using graph theory. This tool identifies conserved pathways in protein families and detects disruptions caused by mutations or conformational changes.

Keywords:
electron transfergraph theoryproteins

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Area of Science:

  • Computational Biochemistry and Biophysics
  • Structural Biology

Background:

  • Predicting electron and hole transfer pathways in proteins is crucial for understanding biological processes.
  • Existing methods like the Pathways approach provide a framework for pathway analysis.

Purpose of the Study:

  • To introduce eMap 2.0, a web-based application for predicting electron/hole transfer pathways in proteins and protein families.
  • To identify conserved pathways within protein sets and detect pathway disruptions.

Main Methods:

  • Utilizes graph-theory algorithms to model proteins and identify shortest paths for electron transfer.
  • Employs frequent subgraph mining (FSM) to find shared pathways across protein sets.
  • Incorporates sequence and structural similarity measures for result analysis and clustering.

Main Results:

  • Demonstrates the ability of eMap 2.0 to rapidly provide insights into conserved electron transfer pathways.
  • Shows successful identification of outliers where pathways are blocked by mutations or conformational changes.
  • Highlights the application of eMap 2.0 in analyzing protein families and individual proteins.

Conclusions:

  • eMap 2.0 offers a robust method for analyzing electron transfer pathways in proteins and protein families.
  • The tool aids in understanding conserved mechanisms and identifying structural or mutational impacts on these pathways.
  • eMap 2.0 advances computational approaches in biochemistry and biophysics for pathway prediction.