In Silico Selection of GAT-1 Inhibitors.

The primary control mechanism for synaptic uptake of GABA is through γ-aminobutyric acid transporter 1 (GAT-1, SLC6A1), a known target for anti-epileptic drugs. Although there is a clinically used GAT-1 inhibitor, tiagabine, the development of a new ligand with an advanced pharmacological profile is desirable. For this purpose, a multi-tiered virtual approach to screening has been created, involving pharmacophore-based search; application of the Informational Spectrum Method for Small Molecules, followed by EIIP/AQVN filtering (ISM-SM); molecular docking using an ensemble of several experimentally obtained structures of GAT-1; and ADMET predictions. Pharmacophore-based screening of the ZINC database of natural products, combined with ISM-SM/EIIP filtering, yielded 237 candidate compounds. Structural separation analysis discriminated between the positives and negatives, enabling enrichment-based prioritization. The use of a composite normalized rank score based on docking affinity and structural similarity allowed for the identification of the top candidates: ZINC03643214 and ZINC67840571. Collectively, these refinements establish a more sophisticated computational model for identifying novel GAT-1 inhibitors and highlight promising candidates for future experimental evaluation.