Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein’s ligand binding site. We explored the relevance of PeptoGrid ranking with a virtual screening of peptide libraries using angiotensin-converting enzyme and GABAB receptor as targets. A reasonable agreement between the computational and experimental data suggests that PeptoGrid is suitable for discovering functional leads.
The aim of the study was to develop better anxiolytics and antidepressants. We focused on GABAA receptors and the α2δ auxiliary subunit of V-gated Ca2+ channels as putative targets because they are established as mediators of efficacious anxiolytics, antidepressants, and anticonvulsants. We further focused on short peptides as candidate ligands because of their high safety and tolerability profiles. We employed a structural bioinformatics approach to develop novel tetrapeptides with predicted affinity to GABAA receptors and α2δ. In silico docking studies of one of these peptides, LCGA-17, showed a high binding score for both GABAA receptors and α2δ, combined with anxiolytic-like properties in a Danio rerio behavioral screen. LCGA-17 showed anxiolytic-like effects in the novel tank test, the light–dark box, and the social preference test, with efficacy comparable to fluvoxamine and diazepam. In binding assays using rat brain membranes, [3H]-LCGA-17 was competed more effectively by gabapentinoid ligands of α2δ than ligands of GABAA receptors, suggesting that α2δ represents a likely target for LCGA-17. [3H]-LCGA-17 binding to brain lysates was unaffected by competition with ligands for GABAB, glutamate, dopamine, serotonin, and other receptors, suggesting specific interaction with α2δ. Dose-finding studies in mice using acute administration of LCGA-17 (i.p.) demonstrated anxiolytic-like effects in the open field test, elevated plus maze, and marble burying tests, as well as antidepressant-like properties in the forced swim test. The anxiolytic effects were effectively blocked by bicuculline. Therefore, LCGA-17 is a novel candidate anxiolytic and antidepressant that may act through α2δ, with possible synergism by GABAA receptors.
BackgroundXenon (Xe) is a noble gas that has been used for the last several decades as an anesthetic during surgery. Its antagonistic effect on glutamate subtype of NMDA (N-methyl-d-aspartate) receptors resulted in evaluation of this gas for treatment of CNS pathologies, including psychoemotional disorders. The aim of this study was to assess the behavioral effects of acute inhalation of subanesthetic concentrations of Xe and to study the outcomes of Xe exposure in valproic acid (VPA)-induced rodent model of autism.MethodsWe have conducted two series of experiments with a battery of behavioral tests aimed to evaluate locomotion, anxiety- and depression-like behavior, and social behavior in healthy, VPA-treated and Xe-exposed young rats.ResultsWe have shown that in healthy animals Xe exposure resulted in acute and delayed decrease of exploratory motivation, partial decrease in risk-taking and depressive-like behavior as well as improved sensorimotor integration during the negative geotaxis test. Acute inhalations of Xe in VPA-exposed animals led to improvement in social behavior, decrease in exploratory motivation, and normalization of behavior in forced-swim test.ConclusionBehavioral modulatory effects of Xe are probably related to its generalized action on excitatory/inhibitory balance within the CNS. Our data suggest that subanesthetic short-term exposures to Xe have beneficial effect on several behavioral modalities and deserves further investigation.
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