title: Design of an activity landscape view taking compound-based feature probabilities into account.
abstract: Activity landscapes (ALs) of compound data sets are rationalized as graphical representations that integrate similarity and potency relationships between active compounds. ALs enable the visualization of structure-activity relationship (SAR) information and are thus computational tools of interest for medicinal chemistry. For AL generation, similarity and potency relationships are typically evaluated in a pairwise manner and major AL features are assessed at the level of compound pairs. In this study, we add a conditional probability formalism to AL design that makes it possible to quantify the probability of individual compounds to contribute to characteristic AL features. Making this information graphically accessible in a molecular network-based AL representation is shown to further increase AL information content and helps to quickly focus on SAR-informative compound subsets. This feature probability-based AL variant extends the current spectrum of AL representations for medicinal chemistry 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: Bijun
authors.initials: B
authors.lastname: Zhang
authors.forename: Martin
authors.initials: M
authors.lastname: Vogt
authors.forename: Jürgen
authors.initials: J
authors.lastname: Bajorath
mesh_terms: D002626:Chemistry, Pharmaceutical / Q000379:methods; D003196:Computer Graphics; D017076:Computer-Aided Design; D066264:Datasets as Topic; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D011336:Probability; D013329:Structure-Activity Relationship