Authors :
Presenting Author: David Kokel, PhD – BioSymetrics
Stacie Calad-Thomson, PhD – BioSymetrics; victoria Catterson, PhD – BioSymetrics; Simon Eng, MA – BioSymetrics; Stephny Geread, MA – BioSymetrics; Kevin Ha, MA – BioSymetrics; gabe Musso, PhD – Biosymetrics; Jonathan Volpatti, BS – Biosymetrics
Rationale:
Drug Resistant Epilepsies (DREs) account for a staggering 30% of all cases. DREs do not respond to known anti-epileptic drugs (AEDs) so treatments will require new therapeutic compounds and targets. Historically, most AEDs were originally discovered via their behavioral phenotypes - most of which were unexpected. If less serendipitous and more systematic phenotype-based screening models for DRE could be developed, then they would likely lead to improved therapeutics.
The problem is that for DRE systematic screening remains a difficult challenge. Phenotype-based screening approaches are severely limited by traditional rodent models that are prohibitively low-throughput. Similarly, target-based approaches are severely limited by incomplete understanding of the molecular mechanisms of DRE so appropriate therapeutic targets remain unclear.
Methods:
To address these shortcomings and apply the power of large-scale chemical screening to DRE, we have developed a phenotype-based drug discovery platform that combines the following: 1) a robotic platform for large-scale chemical screening in zebrafish, 2) a computer vision pipeline for systematic behavioral profiling, 3) software for ligand-based target-prediction, and 4) tools for AI-assisted analysis of multi-dimensional phenotypic data.
Results:
Using this platform, we found that genes related to DRE in humans, like KCC2, caused robust epilepsy-related hyperactivity behaviors in zebrafish. These epilepsy-related zebrafish behaviors were rescued with known AEDs at therapeutically relevant concentrations. We screened 2,000 novel compounds against zebrafish behavioral assays in 96-well format and found that epilepsy-related phenotypes were reproducibly rescued by 12 hit compounds. Analysis of these hit compounds predicted that a subset acted on multiple first-in-class epilepsy targets. Modulating these targets with probe compounds successfully rescued the epilepsy-related phenotypes, suggesting that these targets may have potential as therapeutic targets for DRE.
Conclusions:
Overall, these studies describe a systematic large-scale phenotype-based screening approach in zebrafish to evaluate any gene or drug with potential activity in the intact vertebrate nervous system. This approach rapidly identified novel compounds and new targets that impact DRE-related phenotypes in vivo. Together, these studies suggest that integrated technologies for phenotype-based chemical screening may accelerate the pace of therapeutic drug discovery for CNS disorders including drug-resistant epilepsies.
Funding: BioSymetrics