title: QSAR modeling and chemical space analysis of antimalarial compounds.
abstract: Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.
authors.affiliation: Laboratoire de Chemoinformatique, UMR7140 CNRS-Université de Strasbourg, 1 rue Blaise Pascal, 67000, Strasbourg, France.|Laboratory of Chemoinfomatics, Butlerov Institute of Chemistry, Kazan Federal University, Kazan, Russia, 420008.
authors.forename: Pavel
authors.initials: P
authors.lastname: Sidorov
authors.affiliation: Institute of Chemistry, University of Tartu, 50411, Tartu, Estonia.
authors.forename: Birgit
authors.initials: B
authors.lastname: Viira
authors.affiliation: Bioorganic and Medicinal Chemistry Team, European School of Chemistry, Polymers and Materials (ECPM), UMR 7509 CNRS-University of Strasbourg, 25, rue Becquerel, 67087, Strasbourg, France.
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Davioud-Charvet
authors.affiliation: Institute of Chemistry, University of Tartu, 50411, Tartu, Estonia.
authors.forename: Uko
authors.initials: U
authors.lastname: Maran
authors.affiliation: Laboratoire de Chemoinformatique, UMR7140 CNRS-Université de Strasbourg, 1 rue Blaise Pascal, 67000, Strasbourg, France.
authors.forename: Gilles
authors.initials: G
authors.lastname: Marcou
authors.affiliation: Laboratoire de Chemoinformatique, UMR7140 CNRS-Université de Strasbourg, 1 rue Blaise Pascal, 67000, Strasbourg, France. dhorvath@unistra.fr.
authors.forename: Dragos
authors.initials: D
authors.lastname: Horvath
authors.affiliation: Laboratoire de Chemoinformatique, UMR7140 CNRS-Université de Strasbourg, 1 rue Blaise Pascal, 67000, Strasbourg, France. varnek@unistra.fr.
authors.forename: Alexandre
authors.identifier: http://orcid.org/0000-0003-1886-925X
authors.initials: A
authors.lastname: Varnek
mesh_terms: D000962:Antimalarials / Q000737:chemistry*; D016208:Databases, Factual; D015195:Drug Design; D006801:Humans; D008958:Models, Molecular; D008968:Molecular Conformation; D015394:Molecular Structure; D021281:Quantitative Structure-Activity Relationship; D013329:Structure-Activity Relationship
chemical_list: D000962:Antimalarials
keywords: Antimalarial compounds; Chemical space; Generative topographic mapping (GTM); Mode of action; Quantitative structure–activity relationships (QSAR)