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Asymmetric Clustering Index in a Case Study of 5-HT1A Receptor Ligands

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  • Marek Śmieja
  • Dawid Warszycki
  • Jacek Tabor
  • Andrzej J Bojarski

Abstract

The automatic clustering of chemical compounds is an important branch of chemoinformatics. In this paper the Asymmetric Clustering Index (Aci) is proposed to assess how well an automatically created partition reflects the reference. The asymmetry allows for a distinction between the fixed reference and the numerically constructed partition. The introduced index is applied to evaluate the quality of hierarchical clustering procedures for 5-HT1A receptor ligands. We find that the most appropriate combination of parameters for the hierarchical clustering of compounds with a determined activity for this biological target is the Klekota Roth fingerprint combined with the complete linkage function and the Buser similarity metric.

Suggested Citation

  • Marek Śmieja & Dawid Warszycki & Jacek Tabor & Andrzej J Bojarski, 2014. "Asymmetric Clustering Index in a Case Study of 5-HT1A Receptor Ligands," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-7, July.
    • Handle: RePEc:plo:pone00:0102069
    DOI: 10.1371/journal.pone.0102069
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    References listed on IDEAS

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    1. Dawid Warszycki & Stefan Mordalski & Kurt Kristiansen & Rafał Kafel & Ingebrigt Sylte & Zdzisław Chilmonczyk & Andrzej J Bojarski, 2013. "A Linear Combination of Pharmacophore Hypotheses as a New Tool in Search of New Active Compounds – An Application for 5-HT1A Receptor Ligands," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
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    Cited by:

    1. Marek Śmieja & Dawid Warszycki, 2016. "Average Information Content Maximization—A New Approach for Fingerprint Hybridization and Reduction," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-14, January.

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