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Updated: Aug 6, 2026
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A Manual Small Molecule Screen Approaching High-throughput Using Zebrafish Embryos
Published on: November 8, 2014
Prioritizing neuroactive ligands using motif-guided virtual discovery and zebrafish profiling
Ari B Ginsparg1,2, Jaqueline A Martinez2, Ishaan Patel3
1Department of Neurobiology, The University of Alabama at Birmingham, Heersink School of Medicine, Birmingham, AL, USA.
Npj Drug Discovery
|July 21, 2026
Summary
We developed a new computational and biological screening pipeline to discover effective drug candidates. This method successfully identified potent hypocretin receptor antagonists with high accuracy, validating its potential for future drug discovery.
Area of Science:
- Drug Discovery
- Computational Chemistry
- Pharmacology
Background:
- Virtual screening of large chemical libraries is crucial for early-stage ligand discovery.
- In silico methods often produce numerous candidates with inconsistent experimental efficacy and limited in vivo relevance.
- Predicting functional efficacy in complex biological systems remains a challenge.
Purpose of the Study:
- To establish an integrated pipeline combining structure-guided computation and functional profiling for prioritizing drug candidates.
- To introduce and apply the Rosetta Engine for Anchoring Ligands with a Motif (REAL-M) screening algorithm.
- To validate the pipeline's effectiveness using the hypocretin receptor system.
Main Methods:
- Utilized the Rosetta Engine for Anchoring Ligands with a Motif (REAL-M) algorithm, leveraging Protein Data Bank (PDB) structural data.
- Employed cell-based reporter assays to assess the binding inhibition of candidate molecules.
- Conducted functional profiling in larval zebrafish, including experiments with hcrtr2 null mutants, to confirm on-target activity.
Main Results:
- 28 out of 30 predicted hypocretin receptor antagonists significantly blocked agonist binding in cell-based assays.
- Six chemically diverse molecules demonstrated efficacy comparable to existing antagonists.
- Three of these compounds significantly reduced hypocretin-induced hyperactivity in larval zebrafish, with on-target validation.
Conclusions:
- The integrated computational and zebrafish-based pipeline effectively prioritizes drug candidates with high accuracy and in vivo relevance.
- REAL-M and functional profiling offer a robust approach for identifying potent and specific drug leads.
- This adaptable pipeline holds promise for discovering ligands targeting numerous proteins with conserved binding pockets.
