Konstantina Bampali, Filip Koniuszewski, Florian D. Vogel, Jure Fabjan, Christos Andronis, Eftychia Lekka, Vassilis Virvillis, Thomas Seidel, Annie Delaunois, Leandro Royer, Michael G. Rolf, Chiara Giuliano, Martin Traebert, Gautier Roussignol, Magali Fric-Bordat, Ludmilla Mazelin-Winum, Sharon D. Bryant, Thierry Langer, Margot Ernst
Abstract
GABAA receptors, members of the pentameric ligand-gated ion channel superfamily, are widely expressed in the central nervous system and mediate a broad range of pharmaco-toxicological effects including bidirectional changes to seizure threshold. Thus, detection of GABAA receptor-mediated seizure liabilities is a big, partly unmet need in early preclinical drug development. This is in part due to the plethora of allosteric binding sites that are present on different subtypes of GABAA receptors and the critical lack of screening methods that detect interactions with any of these sites. To improve in silico screening methods, we assembled an inventory of allosteric binding sites based on structural data. Pharmacophore models representing several of the binding sites were constructed. These models from the NeuroDeRisk IL Profiler were used for in silico screening of a compiled collection of drugs with known GABAA receptor interactions to generate testable hypotheses. Amoxapine was one of the hits identified and subjected to an array of in vitro assays to examine molecular and cellular effects on neuronal excitability and in vivo locomotor pattern changes in zebrafish larvae. An additional level of analysis for our compound collection is provided by pharmacovigilance alerts using FAERS data. Inspired by the Adverse Outcome Pathway framework, we postulate several candidate pathways leading from specific binding sites to acute seizure induction. The whole workflow can be utilized for any compound collection and should inform about GABAA receptor-mediated seizure risks more comprehensively compared to standard displacement screens, as it rests chiefly on functional data.
Pharmacology, Toxicology and Pharmaceutical Science
1
8%
Physics and Astronomy
1
8%
Medicine and Dentistry
1
8%
Neuroscience
1
8%
Other
1
8%
Unknown
6
46%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 April 2023.
All research outputs
#14,548,949
of 25,801,916 outputs
Outputs from Cell Biology and Toxicology
#241
of 531 outputs
Outputs of similar age
#164,179
of 414,984 outputs
Outputs of similar age from Cell Biology and Toxicology
#1
of 4 outputs
Altmetric has tracked 25,801,916 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 531 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 414,984 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them
