In Silico Screening of Novel α1-GABAA Receptor PAMs towards Schizophrenia Based on Combined Modeling Studies of Imidazo [1,2-a]-Pyridines

Cognitive dysfunction in schizophrenia patients caused by down-regulation of γ-aminobutyric acid receptor subunits

BACKGROUND

The expression pattern of gamma aminobutyric acid (GABA) receptor subunits are commonly altered in patients with schizophrenia, which may lead to nerve excitation/inhibition problems, affecting cognition, emotion, and behavior.

AIM

To explore GABA receptor expression and its relationship with schizophrenia and to provide insights into more effective treatments.

METHODS

This case-control study enrolled 126 patients with schizophrenia treated at our hospital and 126 healthy volunteers who underwent physical examinations at our hospital during the same period. The expression levels of the GABA receptor subunits were detected using 1H-magnetic resonance spectroscopy. The recognized cognitive battery tool, the MATRICS Consensus Cognitive Battery, was used to evaluate the scores for various dimensions of cognitive function. The correlation between GABA receptor subunit downregulation and schizophrenia was also analyzed.

RESULTS

Significant differences in GABA receptor subunit levels were found between the case and control groups (P < 0.05). A significant difference was also found between the case and control groups in terms of cognitive function measures, including attention/alertness and learning ability (P < 0.05). Specifically, as the expression levels of GABRA1 (α1 subunit gene), GABRB2 (β2 subunit gene), GABRD (δ subunit), and GABRE (ε subunit) decreased, the severity of the patients' condition increased gradually, indicating a positive correlation between the downregulation of these 4 receptor subunits and schizophrenia (P < 0.05). However, the expression levels of GABRA5 (α5 subunit gene) and GABRA6 (α6 subunit gene) showed no significant correlation with schizophrenia (P > 0.05).

CONCLUSION

Downregulation of the GABA receptor subunits is positively correlated with schizophrenia. In other words, when GABA receptor subunits are downregulated in patients, cognitive impairment becomes more severe.

Mechanistic insights into the selectivity of bicyclophosphorothionate antagonists for housefly versus rat GABA receptors

BACKGROUND

γ-Aminobutyric acid (GABA) receptors (GABARs) are validated targets of insecticides. Bicyclophosphorothionates are a group of insecticidal compounds that act as noncompetitive antagonists of GABARs. We previously reported that the analogs exhibit various degrees of selectivity for housefly versus rat GABARs, depending on substitutions at the 3- and 4-positions. We here sought to elucidate the unsolved mechanisms of the receptor selectivity using quantitative structure-activity relationship (QSAR), molecular docking, and molecular dynamics approaches.

RESULTS

Three-dimensional (3D)-QSAR studies using Topomer comparative molecular field analysis quantitatively demonstrated how the introduction of a small alkyl group at the 3-position of bicyclophosphorothionates contributes to the housefly versus rat GABAR selectivity. To investigate the molecular mechanisms of the selective action, bicyclophosphorothionates were docked into housefly Resistance to dieldrin (RDL) GABAR and rat α1β2γ2 GABAR homology models built using the published 3D-structures of human GABARs as templates. The results of molecular docking and molecular dynamics simulations revealed that the 2'Ala and 6'Thr residues of the RDL subunit within the channel are the key amino acids for binding to the housefly GABARs, whereas the 2'Ser residue of γ2 subunit plays a crucial role in binding to rat GABARs.

CONCLUSION

We revealed the molecular mechanisms underlying the selective antagonistic action of bicyclophosphorothionates on housefly versus rat GABARs. The information presented should help design and develop novel, safe GABAR-targeting insecticides. © 2023 Society of Chemical Industry.

In silico screening-based discovery of benzamide derivatives as inhibitors of Rho-associated kinase-1 (ROCK1)

As a pivotal node in modulating various cell behaviors, Rho-associated kinase-1 (ROCK1) has attracted significant attention as a promising therapeutic target in a variety of diseases. Benzamide has been widely reported as a ROCK1 inhibitors in recent years. To better understand its pharmacological properties and to explore its potential inhibitors, a series of ROCK1 inhibitors derived from N-methyl-4-(4-pyrazolidinyl) benzamides (MPBs) were investigated by using three-dimensional quantitative structure-activity relationship (3D-QSAR) models, pharmacophore models, molecular docking, and molecular dynamics (MD) simulation. The comparative Molecular Field Analysis (CoMFA) model (q2 = 0.616, R2 = 0.972, ONC = 4, and r2pred = 0.983) and the best Comparative Molecular Similarity Indices Analysis (CoMSIA) model (q2= 0.740, R2 = 0.982, ONC = 6, and r2pred = 0.824) exhibited reliable predictability with satisfactory validation parameters. In the subsequent virtual screening, VS03 and VS05 were identified to have superior predicted activities and higher docking scores, meanwhile they demonstrated to be reasonably stable in the binding pocket through MD simulations. These results provide a significant theoretical direction for the rational design and development of novel ROCK1 inhibitors.Communicated by Ramaswamy H. Sarma.

Bibliometric Analysis on GABA-A Receptors Research Based on CiteSpace and VOSviewer

Background

GABA-A receptors are the primary mediators of brain inhibitory neurotransmission. In the past years, many studies focused on this channel to decipher the pathogenesis of related diseases but lacked bibliometric analysis research. This study aims to explore the research status and identify the research trends of GABA-A receptor channels.

Methods

Publications related to GABA-A receptor channels were retrieved from the Web of Science Core Collection from 2012 to 2022. After screening, the VOSviewer 1.6.18 and Citespace 5.8 R3 were used for bibliometric analysis from journals, countries, institutions, authors, co-cited references and keywords.

Results

We included 12,124 publications in the field of GABA-A receptor channels for analysis. The data shows that although there was a slight decrease in annual publications from 2012 to 2021, it remained at a relatively high level. Most publications were in the domain of neuroscience. Additionally, the United States was the most prolific country, followed by China. Univ Toronto was the most productive institution, and James M Cook led essential findings in this field. Furthermore, brain activation, GABAAR subunits expression, modulation mechanism in pain and anxiety behaviors and GABA and dopamine were paid attention to by researchers. And top research frontiers were molecular docking, autoimmune encephalitic series, obesity, sex difference, diagnosis and management, EEG and KCC2.

Conclusion

Taken together, academic attention on GABA-A receptor channels was never neglected since 2012. Our analysis identified key information, such as core countries, institutions and authors in this field. Molecular docking, autoimmune encephalitic series, obesity, sex difference, diagnosis and management, EEG and KCC2 will be the future research direction.

Development of Novel Therapeutics for Schizophrenia Treatment Based on a Selective Positive Allosteric Modulation of α1-Containing GABAARs-In Silico Approach

For the development of atypical antipsychotics, the selective positive allosteric modulation of the ionotropic GABAA receptor (GABAAR) has emerged as a promising approach. In the presented research, two unrelated methods were used for the development of QSAR models for selective positive allosteric modulation of 1-containing GABAARs with derivatives of imidazo [1,2-a]-pyridine. The development of conformation-independent QSAR models, based on descriptors derived from local molecular graph invariants and SMILES notation, was achieved with the Monte Carlo optimization method. From the vast pool of 0D, 1D, and 2D molecule descriptors, the GA-MLR method developed additional QSAR models. Various statistical methods were utilised for the determination of the developed models’ robustness, predictability, and overall quality, and according to the obtained results, all QSAR models are considered good. The molecular fragments that have a positive or negative impact on the studied activity were obtained from the studied molecules’ SMILES notations, and according to the obtained results, nine novel compounds were designed. The binding affinities to GABAAR of designed compounds were assessed with the application of molecular docking studies and the obtained results showed a high correlation with results obtained from QSAR modeling. To assess all designed molecules’ “drug-likeness”, their physicochemical descriptors were computed and utilised for the prediction of medicinal chemistry friendliness, pharmacokinetic properties, ADME parameters, and druglike nature.

Efficient synthesis of 1,3-naphtoxazine derivatives using reusable magnetic catalyst (GO-Fe3O4-Ti(IV)): anticonvulsant evaluation and computational studies

A series of 2-aryl/alkyl-2,3-dihydro-1H-naphtho[1,2-e][1,3]oxazines (S₁-S₁₁) were synthesized with an eco-friendly and recoverable nanocatalyst (GO-Fe₃O₄-Ti^(IV)) as an efficient magnetic composite. The new nanocatalyst was characterized by FT-IR, XRD and, EDS analysis. A conformable procedure, easy to work up and having a short reaction time with high yields are some advantages of this method. The new catalyst is also thermal-stable, reusable and, environment-friendly. The chemical structures of the synthesized 1,3-oxazine compounds were confirmed by comparing their melting points with those reported in literature. Then, the anticonvulsant activity of these compounds was assessed by the intraperitoneal pentylenetetrazole test (ipPTZ). Compounds S₁₀ and S₁₁ displayed considerable activity against chemically-induced seizure tests. The molecular simulation was also done to achieve their binding affinities as γ-aminobutyric acid A (GABA-A) receptor agonists as an assumptive mechanism of their anticonvulsant action. The result of molecular studies represented strongly matched with biological activity. Molecular docking simulation of the potent compound (S₁₀) and diazepam as the positive control was performed and some critical residues like Thr262, Asn265, Met286, Phe289, and Val290 were identified. Based on the anticonvulsant results and also in silico ADME predictions, S₁₁ can be to become a potential drug candidate as an anticonvulsant agent.

QSAR, ADMET In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Studies of Novel Bicyclo (Aryl Methyl) Benzamides as Potent GlyT1 Inhibitors for the Treatment of Schizophrenia

Forty-four bicyclo ((aryl) methyl) benzamides, acting as glycine transporter type 1 (GlyT1) inhibitors, are developed using molecular modeling techniques. QSAR models generated by multiple linear and non-linear regressions affirm that the biological inhibitory activity against the schizophrenia disease is strongly and significantly correlated with physicochemical, geometrical and topological descriptors, in particular: Hydrogen bond donor, polarizability, surface tension, stretch and torsion energies and topological diameter. According to in silico ADMET properties, the most active ligands (L6, L9, L30, L31 and L37) are the molecules having the highest probability of penetrating the central nervous system (CNS), but the molecule 32 has the highest probability of being absorbed by the gastrointestinal tract. Molecular docking results indicate that Tyr124, Phe43, Phe325, Asp46, Phe319 and Val120 amino acids are the active sites of the dopamine transporter (DAT) membrane protein, in which the most active ligands can inhibit the glycine transporter type 1 (GlyT1). The results of molecular dynamics (MD) simulation revealed that all five inhibitors remained stable in the active sites of the DAT protein during 100 ns, demonstrating their promising role as candidate drugs for the treatment of schizophrenia.