Chalcone-Arylpiperazine Hybrids as Potential Antianxiety Agents: Synthesis, Biological Evaluation, Molecular...

Anxiety disorders are among the most prevalent mental health conditions, yet recent drug development has yielded few novel antianxiety agents. This study explores chalcone- arylpiperazine hybrids as potential scaffolds for anxiolytic activity through a combination of synthesis, computational modeling, and preliminary behavioral evaluation.

Five chalcone-arylpiperazine hybrids (m_01 to m_05) were synthesized via condensation of 1-[4-(3-chloropropoxy)-phenyl]-3-phenyl-prop-2-en-1-one with various substituted phenylpiperazines. Molecular docking was performed using AutoDock with the human GABAA receptor (PDB 4COF), followed by molecular dynamics simulations using GROMACS. Anxiolytic activity was assessed using the elevated plus maze (EPM) in animal models. Network pharmacology and ADMET profiling were conducted using publicly available databases and tools.

Docking studies revealed that all compounds exhibited higher binding affinity than diazepam, with m_02 showing the strongest interaction (-10.44 kcal/mol vs. -7.38 kcal/mol for diazepam). Molecular dynamics confirmed the stability of m_02 and m_03 at the receptor binding site. In EPM testing, m_03 demonstrated the most pronounced increase in time spent and entries into open arms, suggesting potential anxiolytic effects. Network pharmacology identified 72 overlapping targets, with KEGG pathway enrichment highlighting neuroactive ligand-receptor interaction and dopaminergic synapse pathways. ADMET analysis indicated favorable drug-like properties.

The chalcone-arylpiperazine hybrids showed promising in silico binding and behavioral effects, particularly m_03. Molecular dynamics and MM-PBSA analyses supported the stability and interaction profiles of key compounds. Network pharmacology suggested plausible mechanisms of action, though these remain speculative without further experimental validation.

Chalcone-arylpiperazine hybrids represent a potentially valuable scaffold for antianxiety drug development. However, the mechanistic insights derived from computational studies require robust in vivo and mechanistic validation to confirm therapeutic relevance.