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Integrated workflow for the identification of new GABA R positive allosteric modulators based on the in silico screening with further in vitro validation. Case study using Enamine's stock chemical space. | LitMetric

AI Article Synopsis

Article Abstract

Numerous studies reported an association between GABA R subunit genes and epilepsy, eating disorders, autism spectrum disorders, neurodevelopmental disorders, and bipolar disorders. This study was aimed to find some potential positive allosteric modulators and was performed by combining the in silico approach with further in vitro evaluation of its real activity. We started from the GABA R-diazepam complexes and assembled a lipid embedded protein ensemble to refine it via molecular dynamics (MD) simulation. Then we focused on the interaction of α1β2γ2 with some Z-drugs (non-benzodiazepine compounds) using an Induced Fit Docking (IFD) into the relaxed binding site to generate a pharmacophore model. The pharmacophore model was validated with a reference set and applied to decrease the pre-filtered Enamine database before the main docking procedure. Finally, we succeeded in identifying a set of compounds, which met all features of the docking model. The aqueous solubility and stability of these compounds in mouse plasma were assessed. Then they were tested for the biological activity using the rat Purkinje neurons and CHO cells with heterologously expressed human α1β2γ2 GABA receptors. Whole-cell patch clamp recordings were used to reveal the GABA induced currents. Our study represents a convenient and tunable model for the discovery of novel positive allosteric modulators of GABA receptors. A High-throughput virtual screening of the largest available database of chemical compounds resulted in the selection of 23 compounds. Further electrophysiological tests allowed us to determine a set of 3 the most outstanding active compounds. Considering the structural features of leader compounds, the study can develop into the MedChem project soon.

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http://dx.doi.org/10.1002/minf.202300156DOI Listing

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