title: Lessons learned from the design of chemical space networks and opportunities for new applications.
abstract: The concept of chemical space is of fundamental relevance in chemical informatics and computer-aided drug discovery. In a series of articles published in the Journal of Computer-Aided Molecular Design, principles of chemical space design were evaluated, molecular networks proposed as an alternative to conventional coordinate-based chemical reference spaces, and different types of chemical space networks (CSNs) constructed and analyzed. Central to the generation of CSNs was the way in which molecular similarity relationships were assessed and a primary focal point was the network-based representation of biologically relevant chemical space. The design and comparison of CSNs based upon alternative similarity measures can be viewed as an evolutionary path with interesting lessons learned along the way. CSN design has matured to the point that such chemical space representations can be used in practice. In this contribution, highlights from the sequence of CSN design efforts are discussed in context, providing a perspective for future practical applications.
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: 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: Dagmar
authors.initials: D
authors.lastname: Stumpfe
authors.affiliation: BIO5 Institute, University of Arizona, 1657 East Helen Street, Tucson, AZ, 85721, 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: D000465:Algorithms; D017076:Computer-Aided Design; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D013329:Structure-Activity Relationship
keywords: Biologically relevant chemical space; Chemical space networks; Chemical space representation; Coordinate-free chemical space; Molecular similarity measures; Network science; Network topology; Structure–activity relationships; Substructure relationship