title: Design of chemical space networks on the basis of Tversky similarity.
abstract: Chemical space networks (CSNs) have been introduced as a coordinate-free representation of chemical space. In CSNs, nodes represent compounds and edges pairwise similarity relationships. These network representations are mostly used to navigate sections of biologically relevant chemical space. Different types of CSNs have been designed on the basis of alternative similarity measures including continuous numerical similarity values or substructure-based similarity criteria. CSNs can be characterized and compared on the basis of statistical concepts from network science. Herein, a new CSN design is introduced that is based upon asymmetric similarity assessment using the Tversky coefficient and termed TV-CSN. Compared to other CSNs, TV-CSNs have unique features. While CSNs typically contain separate compound communities and exhibit small world character, many TV-CSNs are also scale-free in nature and contain hubs, i.e., extensively connected central compounds. Compared to other CSNs, these hubs are a characteristic of TV-CSN topology. Hub-containing compound communities are of particular interest for the exploration of structure-activity relationships.
authors.affiliation: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, 53113, Bonn, Germany.
authors.forename: Mengjun
authors.initials: M
authors.lastname: Wu
authors.affiliation: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, 53113, Bonn, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Vogt
authors.affiliation: University of Arizona BIO5 Institute, 1657 East Helen Street, Tucson, AZ, 85721, USA.|Translational Genomics Research Institute, 445 North Fifth Street, Phoenix, AZ, 85004, USA.
authors.forename: Gerald M
authors.initials: GM
authors.lastname: Maggiora
authors.affiliation: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, 53113, Bonn, Germany. bajorath@bit.uni-bonn.de.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Bajorath
mesh_terms: D016000:Cluster Analysis; D017076:Computer-Aided Design; D015195:Drug Design; D008956:Models, Chemical; D008958:Models, Molecular; D054852:Small Molecule Libraries / Q000737:chemistry* / Q000494:pharmacology; D013329:Structure-Activity Relationship
chemical_list: D054852:Small Molecule Libraries
keywords: Biologically relevant chemical space; Chemical space networks; Network science; Similarity metrics; Structure–activity relationships; Topology; Tversky similarity