Mining Molecular Fragments: Finding Relevant Substructures of Molecules

  • Authors:
  • Christian Borgelt;Michael R. Berthold

  • Affiliations:
  • -;-

  • Venue:
  • ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
  • Year:
  • 2002

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Abstract

We present an algorithm to find fragments in a setof molecules that help to discriminate between differentclasses of, for instance, activity in a drug discovery context.Instead of carrying out a brute-force search, our methodgenerates fragments by embedding them in all appropriatemolecules in parallel and prunes the search tree based ona local order of the atoms and bonds, which results in substantiallyfaster search by eliminating the need for frequent,computationally expensive reembeddings and by suppressingredundant search. We prove the usefulness of our algorithmby demonstrating the discovery of activity-relatedgroups of chemical compounds in the well-known NationalCancer Institute's HIV-screening dataset.