title: A KNIME-Based Analysis of the Zebrafish Photomotor Response Clusters the Phenotypes of 14 Classes of Neuroactive Molecules.
abstract: Recently, the photomotor response (PMR) of zebrafish embryos was reported as a robust behavior that is useful for high-throughput neuroactive drug discovery and mechanism prediction. Given the complexity of the PMR, there is a need for rapid and easy analysis of the behavioral data. In this study, we developed an automated analysis workflow using the KNIME Analytics Platform and made it freely accessible. This workflow allows us to simultaneously calculate a behavioral fingerprint for all analyzed compounds and to further process the data. Furthermore, to further characterize the potential of PMR for mechanism prediction, we performed PMR analysis of 767 neuroactive compounds covering 14 different receptor classes using the KNIME workflow. We observed a true positive rate of 25% and a false negative rate of 75% in our screening conditions. Among the true positives, all receptor classes were represented, thereby confirming the utility of the PMR assay to identify a broad range of neuroactive molecules. By hierarchical clustering of the behavioral fingerprints, different phenotypical clusters were observed that suggest the utility of PMR for mechanism prediction for adrenergics, dopaminergics, serotonergics, metabotropic glutamatergics, opioids, and ion channel ligands.
authors.affiliation: Laboratory for Molecular Biodiscovery, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.
authors.forename: Daniëlle
authors.initials: D
authors.lastname: Copmans
authors.affiliation: KNIME.com AG, Zurich, Switzerland.
authors.forename: Thorsten
authors.initials: T
authors.lastname: Meinl
authors.affiliation: Chair for Bioinformatics and Information Mining, Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.
authors.forename: Christian
authors.initials: C
authors.lastname: Dietz
authors.affiliation: Machine Learning Group, Department of Computer Science, KU Leuven, Leuven, Belgium.
authors.forename: Matthijs
authors.initials: M
authors.lastname: van Leeuwen
authors.affiliation: Department of Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research, UFZ, Leipzig, Germany.
authors.forename: Julia
authors.initials: J
authors.lastname: Ortmann
authors.affiliation: Chair for Bioinformatics and Information Mining, Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.
authors.forename: Michael R
authors.initials: MR
authors.lastname: Berthold
authors.affiliation: Laboratory for Molecular Biodiscovery, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium peter.dewitte@pharm.kuleuven.be.
authors.forename: Peter A M
authors.initials: PA
authors.lastname: de Witte
mesh_terms: D000818:Animals; D055808:Drug Discovery / Q000379:methods*; D057166:High-Throughput Screening Assays / Q000379:methods*; D008024:Ligands; D018377:Neurotransmitter Agents / Q000302:isolation & purification* / Q000627:therapeutic use; D010641:Phenotype; D054852:Small Molecule Libraries / Q000302:isolation & purification* / Q000627:therapeutic use; D015027:Zebrafish / Q000196:embryology / Q000502:physiology
chemical_list: D008024:Ligands; D018377:Neurotransmitter Agents; D054852:Small Molecule Libraries
keywords: KNIME; data analysis; neuroactive drug discovery; photomotor response; zebrafish