title: Structuring Chemical Space: Similarity-Based Characterization of the PubChem Database.
abstract: The ensemble of conceivable molecules is referred to as the Chemical Space. In this article we describe a hierarchical version of the Affinity Propagation (AP) clustering algorithm and apply it to analyze the LINGO-based similarity matrix of a 500 000-molecule subset of the PubChem database, which contains more than 19 million compounds. The combination of two highly efficient methods, namely the AP clustering algorithm and LINGO-based molecular similarity calculations, allows the unbiased analysis of large databases. Hierarchical clustering generates a numerical diagonalization of the similarity matrix. The target-independent, intrinsic structure of the database , derived without any previous information on the physical or biological properties of the compounds, maps together molecules experimentally shown to bind the same biological target or to have similar physical properties.
authors.affiliation: Institute for Research in Biomedicine Parc Científic de Barcelona, Baldiri Reixac, 10. 08028-Barcelona, Spain tel: +34 934034683; fax: +34 934039976.|Departament de Química Orgànica, Universitat de Barcelona, Martí i Franquès, 1-11, 08028-Barcelona, Spain.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Cincilla
authors.affiliation: Origenis GmbH, Am Klopferspitz 19a, 82152 Martinsried, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Thormann
authors.affiliation: Institute for Research in Biomedicine Parc Científic de Barcelona, Baldiri Reixac, 10. 08028-Barcelona, Spain tel: +34 934034683; fax: +34 934039976. mpons@ub.edu.|Departament de Química Orgànica, Universitat de Barcelona, Martí i Franquès, 1-11, 08028-Barcelona, Spain. mpons@ub.edu.
authors.forename: Miquel
authors.initials: M
authors.lastname: Pons
keywords: Affinity propagation clustering; Drug design; Eigenmolecules; LINGO; Molecular similarity; Proteins; PubChem