Multistage Molecular Simulations, Design, Synthesis, and Anticonvulsant Evaluation of 2-(Isoindolin-2-yl) Esters of Aromatic Amino Acids Targeting GABAA Receptors via π-π Stacking

Abstract

Epilepsy remains a widespread neurological disorder, with approximately 30% of patients showing resistance to current antiepileptic therapies. To address this unmet need, a series of 2-(isoindolin-2-yl) esters derived from natural amino acids were designed and evaluated for their potential interaction with the GABA_A receptor. Sixteen derivatives were subjected to in silico assessments, including physicochemical and ADMET profiling, virtual screening-ensemble docking, and enhanced sampling molecular dynamics simulations (metadynamics calculations). Among these, compounds derived from the aromatic amino acids, phenylalanine, tyrosine, tryptophan, and histidine, exhibited superior predicted affinity, attributed to π-π stacking interactions at the benzodiazepine binding site of the GABA_A receptor. Based on computational performance, the tyrosine and tryptophan derivatives were synthesized and further assessed in vivo using the pentylenetetrazole-induced seizure model in zebrafish (Danio rerio). The tryptophan derivative produced comparable behavioral seizure reduction to the reference drug diazepam at the tested concentrations. The results implies that aromatic amino acid-derived isoindoline esters are promising anticonvulsant candidates and support the hypothesis that π-π interactions may play a critical role in modulating GABA_A receptor binding affinity.

Keywords: GABA receptor; anticonvulsant; aromatic amino acid; isoindoline; molecular docking; zebrafish model; π–π interaction.

Figure 1

Radar plot of physicochemical properties for the designed isoindoline esters. Each axis represents a distinct property relevant to drug-likeness. The blue shaded area represents the acceptable range for oral bioavailability according to the SwissADME criteria. The green central region shows the optimal range. The yellow line corresponds to the calculated values for each compound. The four aromatic amino acid derivatives (highlighted) cluster within the optimal range for CNS-active compounds. (a) ETYR; (b) ETRP; (c) EHIS; (d) EPHE.

Figure 2

Predicted binding modes of diazepam, flumazenil, and selected isoindoline esters at the benzodiazepine-binding site of the GABA_A receptor, based on molecular docking. Both 2D (panels a,c,e,g) and 3D (panels b,d,f,h) representations highlight key residues involved in ligand recognition. Aromatic residues from the α1 and γ2 subunits—Phe77 (γ2), Tyr58 (γ2), Tyr160 (α1), and Tyr210 (α1)—are shown interacting via π–π stacking (green) and hydrogen bonding (purple arrows). Residue labels explicitly indicate subunit origin to demonstrate that binding occurs at the extracellular α1/γ2 interface, which defines the canonical benzodiazepine site. Diazepam and flumazenil are shown as reference ligands to validate docking accuracy and site localization. Among all analogs screened, the Tyr- and Trp-derived esters exhibited the most favorable binding energies and are shown as representative low-energy binding poses. Panel keys: (a,b) diazepam; (c,d) ETYR-derived; (e,f) ETRP-derived; (g,h) flumazenil.

Figure 3

(A) Root-mean-square deviation (RMSD) profiles of the GABA_A receptor backbone during 100 ns molecular dynamics simulations in complex with E-HIS, E-TYR, and E-TRP esters, indicating the overall structural stability of the receptor–ligand complexes. (B) Root-mean-square fluctuation (RMSF) analysis per residue, highlighting flexible loop regions and key residues involved in ligand recognition and binding. Regions of elevated fluctuation correlate with sites of dynamic adaptation upon ligand engagement, suggesting potential allosteric effects or conformational plasticity in the binding site.

Scheme 1

General synthetic route for the preparation of 2-(isoindolin-2-yl) esters of tyrosine and tryptophan.

Figure 4

Quantification of latency scores in zebrafish treated with vehicle, diazepam, tyrosine ester, and tryptophan ester following PTZ exposure; n = 6 zebrafish for each group of treatment. (a) PTZ vs. DZP (* p = 0.004); PTZ vs. ETRP 10 µM (* p = 0.02). (b) (* p < 0.001). (c–e) (* p < 0.01). (e) Data are presented as medians ± interquartile ranges. For (a,b), the analysis was performed using ANOVA followed by Dunnet post hoc test, while for (c–e), the Kruskal–Wallis test was used, followed by the Bonferroni correction for the Mann–Whitney U test.