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A Web Tool for Generating High Quality Machine-readable Biological Pathways
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Computing atom mappings for biochemical reactions without subgraph isomorphism.

Markus Heinonen1, Sampsa Lappalainen, Taneli Mielikäinen

  • 1Department of Computer Science, University of Helsinki, Helsinki, Finland. markus.heinonen@cs.helsinki.fi

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|January 8, 2011
PubMed
Summary
This summary is machine-generated.

Tracing atoms in metabolic pathways is crucial for systems biology and drug discovery. Our new A* search algorithm efficiently solves the atom mapping problem, finding exact minimum edge edit distance mappings with less manual curation.

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Area of Science:

  • Biochemistry
  • Systems Biology
  • Computational Biology

Background:

  • Tracing individual atoms through metabolic pathways is essential for systems biology and drug discovery.
  • Current metabolome studies do not directly provide atom fate information, necessitating separate acquisition.
  • The automatic discovery of atom correspondences in biochemical reactions is known as the atom mapping problem.

Purpose of the Study:

  • To develop an efficient and exact algorithm for solving the atom mapping problem.
  • To find atom mappings with minimum edge edit distance.
  • To offer an alternative to heuristic methods that may require more manual curation.

Main Methods:

  • An algorithm based on A* search with advanced heuristics for search space pruning.
  • Exact minimization of an objective function (minimum edge edit distance).
  • Comparison against greedy search, bipartite graph matching, and iterative maximum common subgraph (MCS) algorithms.

Main Results:

  • The proposed A* search algorithm efficiently finds exact atom mappings with minimum edge edit distance.
  • The new approach requires less manual curation compared to the commonly used MCS heuristic.
  • Experiments on KEGG LIGAND and RPAIR databases show that alternative methods often fail to find minimum edit distance mappings.

Conclusions:

  • The A* search-based algorithm provides an exact and efficient solution to the atom mapping problem.
  • This method offers advantages in accuracy and reduced manual effort over heuristic approaches.
  • The findings are significant for advancing systems biology and drug discovery through precise metabolic pathway analysis.