Literature DB >> 26637551

A KNIME-Based Analysis of the Zebrafish Photomotor Response Clusters the Phenotypes of 14 Classes of Neuroactive Molecules.

Daniëlle Copmans1, Thorsten Meinl2, Christian Dietz3, Matthijs van Leeuwen4, Julia Ortmann5, Michael R Berthold3, Peter A M de Witte6.   

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.
© 2015 Society for Laboratory Automation and Screening.

Entities:  

Keywords:  KNIME; data analysis; neuroactive drug discovery; photomotor response; zebrafish

Mesh:

Substances:

Year:  2015        PMID: 26637551     DOI: 10.1177/1087057115618348

Source DB:  PubMed          Journal:  J Biomol Screen        ISSN: 1087-0571


  8 in total

Review 1.  Zebrafish Larvae Behavior Models as a Tool for Drug Screenings and Pre-Clinical Trials: A Review.

Authors:  João Gabriel Santos Rosa; Carla Lima; Monica Lopes-Ferreira
Journal:  Int J Mol Sci       Date:  2022-06-14       Impact factor: 6.208

2.  High-throughput Screening in Larval Zebrafish Identifies Novel Potent Sedative-hypnotics.

Authors:  Xiaoxuan Yang; Youssef Jounaidi; Jennifer B Dai; Francisco Marte-Oquendo; Elizabeth S Halpin; Lauren E Brown; Richard Trilles; Wenqing Xu; Renee Daigle; Buwei Yu; Scott E Schaus; John A Porco; Stuart A Forman
Journal:  Anesthesiology       Date:  2018-09       Impact factor: 7.892

3.  Use of Zebrafish Larvae as a Multi-Endpoint Platform to Characterize the Toxicity Profile of Silica Nanoparticles.

Authors:  Duc-Hung Pham; Bert De Roo; Xuan-Bac Nguyen; Mattias Vervaele; Angela Kecskés; Annelii Ny; Daniëlle Copmans; Hanne Vriens; Jean-Pierre Locquet; Peter Hoet; Peter A M de Witte
Journal:  Sci Rep       Date:  2016-11-22       Impact factor: 4.379

4.  Zebrafish-Based Discovery of Antiseizure Compounds from the North Sea: Isoquinoline Alkaloids TMC-120A and TMC-120B.

Authors:  Daniëlle Copmans; Sara Kildgaard; Silas A Rasmussen; Monika Ślęzak; Nina Dirkx; Michèle Partoens; Camila V Esguerra; Alexander D Crawford; Thomas O Larsen; Peter A M de Witte
Journal:  Mar Drugs       Date:  2019-10-25       Impact factor: 5.118

5.  From the North Sea to Drug Repurposing, the Antiseizure Activity of Halimide and Plinabulin.

Authors:  Daniëlle Copmans; Sara Kildgaard; Emma Roux; Michèle Partoens; Gert Steurs; Xinhui Wang; Wim M De Borggraeve; Camila V Esguerra; Alexander D Crawford; Thomas O Larsen; Peter A M de Witte
Journal:  Pharmaceuticals (Basel)       Date:  2022-02-18

6.  Grouping of chemicals into mode of action classes by automated effect pattern analysis using the zebrafish embryo toxicity test.

Authors:  E Teixidó; T R Kieβling; N Klüver; S Scholz
Journal:  Arch Toxicol       Date:  2022-03-07       Impact factor: 6.168

Review 7.  Zebrafish Is a Powerful Tool for Precision Medicine Approaches to Neurological Disorders.

Authors:  Katarzyna Ochenkowska; Aveeva Herold; Éric Samarut
Journal:  Front Mol Neurosci       Date:  2022-07-06       Impact factor: 6.261

8.  Nonlinear mixed-modelling discriminates the effect of chemicals and their mixtures on zebrafish behavior.

Authors:  Patrick T Gauthier; Mathilakath M Vijayan
Journal:  Sci Rep       Date:  2018-01-31       Impact factor: 4.379

  8 in total

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