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GABA A receptor-mediated seizure liabilities: a mixed-methods screening approach.

Konstantina BampaliFilip KoniuszewskiFlorian D VogelJure FabjanChristos AndronisEftychia LekkaVassilis VirvillisThomas SeidelAnnie DelaunoisLeandro RoyerMichael G RolfChiara GiulianoMartin TraebertGautier RoussignolMagali Fric-BordatLudmilla Mazelin-WinumSharon D BryantThierry LangerMargot Ernst
Published in: Cell biology and toxicology (2023)
GABA A 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 GABA A 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 GABA A 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 GABA A 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 GABA A receptor-mediated seizure risks more comprehensively compared to standard displacement screens, as it rests chiefly on functional data.
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