title: Asymmetric clustering index in a case study of 5-HT1A receptor ligands.
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.
authors.affiliation: Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland.
authors.forename: Marek
authors.initials: M
authors.lastname: Śmieja
authors.affiliation: Institute of Pharmacology, Polish Academy of Sciences, Kraków, Poland.
authors.forename: Dawid
authors.initials: D
authors.lastname: Warszycki
authors.affiliation: Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland.
authors.forename: Jacek
authors.initials: J
authors.lastname: Tabor
authors.affiliation: Institute of Pharmacology, Polish Academy of Sciences, Kraków, Poland.
authors.forename: Andrzej J
authors.initials: AJ
authors.lastname: Bojarski
mesh_terms: D001669:Biochemical Phenomena; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D008024:Ligands; D044282:Receptor, Serotonin, 5-HT1A / Q000378:metabolism*
chemical_list: D008024:Ligands; D044282:Receptor, Serotonin, 5-HT1A