title: Visualization of multi-property landscapes for compound selection and optimization.
abstract: Compound optimization generally requires considering multiple properties in concert and reaching a balance between them. Computationally, this process can be supported by multi-objective optimization methods that produce numerical solutions to an optimization task. Since a variety of comparable multi-property solutions are usually obtained further prioritization is required. However, the underlying multi-dimensional property spaces are typically complex and difficult to rationalize. Herein, an approach is introduced to visualize multi-property landscapes by adapting the concepts of star and parallel coordinates from computer graphics. The visualization method is designed to complement multi-objective compound optimization. We show that visualization makes it possible to further distinguish between numerically equivalent optimization solutions and helps to select drug-like compounds from multi-dimensional property spaces. The methodology is intuitive, applicable to a wide range of chemical optimization problems, and made freely available to the scientific community.
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: Antonio
authors.initials: A
authors.lastname: de la Vega de León
authors.forename: Shilva
authors.initials: S
authors.lastname: Kayastha
authors.forename: Dilyana
authors.initials: D
authors.lastname: Dimova
authors.forename: Thomas
authors.initials: T
authors.lastname: Schultz
authors.forename: Jürgen
authors.initials: J
authors.lastname: Bajorath
mesh_terms: D003196:Computer Graphics; D062126:Databases, Chemical; D008968:Molecular Conformation; D013329:Structure-Activity Relationship