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.
Publication types
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Evaluation Study
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Research Support, Non-U.S. Gov't
MeSH terms
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Biochemical Phenomena
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Cluster Analysis*
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Computational Biology / methods*
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Humans
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Ligands*
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Receptor, Serotonin, 5-HT1A / metabolism*
Substances
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Ligands
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Receptor, Serotonin, 5-HT1A
Grants and funding
The work of first author was supported by Polish Ministry of Science and Higher Education from the budget for science in the years 2013–2015 [IP2012 055972]. The work of second and fourth authors was supported by the Polish-Norwegian Research Programme operated by the National Centre for Research and Development under the Norwegian Financial Mechanism 2009-2014 in the frame of Project PLATFORMex [Pol-Nor/198887/73/2013]. The work of the third author was supported by the National Centre of Science, Poland [2011/01/B/ST6/01887]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.