Targeting glucosyltransferases to combat dental caries: Current perspectives and future prospects.

The emergence of antimicrobial resistance within bacterial communities poses formidable challenges to existing therapeutic strategies aimed at mitigating biofilm-mediated infections. Recent advancements in this domain have spurred the development of targeted antimicrobial agents, designed to selectively eradicate the primary etiological agents while preserving the beneficial microbial diversity of the oral cavity. Targeting glucosyltransferases (GTFs), which play crucial roles in dental biofilm formation, offers a precise strategy to inhibit extracellular polysaccharide synthesis without compromising oral microbiota. This review article delves into the intricate mechanisms underlying dental caries, with a specific focus on the role of GTFs, enzymes produced by S. mutans. It further provides an overview of current research on GTF inhibitors, exploring their mechanisms of action, efficacy, and potential applications in clinical practice. Furthermore, it discusses the challenges and opportunities in the development of novel GTF inhibitors, emphasizing the need for innovative approaches to combat biofilm-mediated oral diseases effectively.

Mechanistic insight into the mode of inhibition of dietary flavonoids; targeting macrophage migration inhibitory factor.

Introduction: The Macrophage Migration Inhibitory Factor (MIF), a key pro-inflammatory mediator, is responsible for modulating immune responses. An array of inflammatory and autoimmune diseases has been linked to the dysregulated activity of MIF. The significance in physiological as well as pathophysiological phenomena underscores the potential of MIF as an attractive target with pharmacological relevance. Extensive research in past has uncovered a number of inhibitors, while the ISO-1, or (S, R)-3-(4-hydroxyphenyl)-4,5-dihydro-5-isoxazole acetic acid methyl ester being recognized as a benchmark standard so far. Recent work by Yang and coworkers identified five promising dietary flavonoids, with superior activity compared to the standard ISO-1. Nevertheless, the exact atomic-level inhibitory mechanism is still elusive. Methods: To improve the dynamic research, and rigorously characterize, and compare molecular signatures of MIF complexes with ISO-1 and flavonoids, principal component analysis (PCA) was linked with molecular dynamics (MD) simulations and binding free energy calculations. Results: The results suggest that by blocking the tautomerase site these small molecule inhibitors could modify the MIF activity by disrupting the intrinsic dynamics in particular functional areas. The stability matrices revealed the average deviation values ranging from 0.27-0.32 nm while the residue level fluctuations indicated that binding of the selected flavonoids confer enhanced stability relative to the ISO-1. Furthermore, the gyration values extracted from the simulated trajectories were found in the range of 1.80-1.83 nm. Discussion: Although all the tested flavonoids demonstrated remarkable results, the one obtained for the potent inhibitors, particularly Morin and Amentoflavone exhibited a good correlation with biological activity. The PCA results featured relatively less variance and constricted conformational landscape than others. The stable ensembles and reduced variation in turns might be the possible reasons for their outstanding performance documented previously. The results from the present exploration provide a comprehensive understanding of the molecular complexes formed by flavonoids and MIF, shedding light on their potential roles and impacts. Future studies on MIF inhibitors may benefit from the knowledge gathered from this investigation.

Impact of mutations in SARS-CoV-2 recombinant sub-variant XBB.1.16 on the binding affinity with human ACE2 receptor.

Despite the waning threat of the COVID-19 pandemic, its detrimental impact on global health persists. Regardless of natural immunity or immunity obtained through vaccination, emerging variants of the virus continue to undergo mutations and propagate globally. The persistent mutations in SARS-CoV-2, along with the subsequent formation of recombinant sub-variants has become a challenge for researchers and health professionals, raising concerns about the efficacy of current vaccines. Gaining a better understanding of the biochemical interactions between the Spike Protein (RBD) of SARS-CoV-2 variants and the human ACE2 receptor can prove to be beneficial in designing and developing antiviral therapeutics that are equally effective against all strains and emerging variants. Our objective in this study was to investigate the interfacial binding pattern of the SARS-CoV-2 RBD-ACE2 complex of the Wild Type (WT), Omicron, and the Omicron recombinant sub-variant XBB.1.16. We aimed to examine the atomic level factors and observe how mutations influence the interaction between the virus and its host using Molecular Dynamics simulation, MM/GBSA energy calculations, and Principal Component Analysis. Our findings reveal a higher degree of structural deviation and flexibility in XBB.1.16 compared to WT and Omicron. PCA indicated a wider cluster and significant flexibility in the movements of XBB.1.16 which can also be observed in free energy landscapes, while the normal mode analysis revealed converging motions within the RBD-ACE2 complexes which can facilitate the interaction between them. A pattern of decreased binding affinity was observed in case of XBB.1.16 when compared to the WT and Omicron. These observed deviations in XBB.1.16 when compared to its parent lineage Omicron, and WT can be attributed to the mutations specific to it. Collectively, these results enhance our understanding of the impact of mutations on the interaction between this strain and the host, taking us one step closer to designing effective antiviral therapeutics against the continually mutating strains.

Exploring the mechanism of action of spirooxindoles as a class of CDK2 inhibitors: a structure-based computational approach.

Cyclin-dependent kinase 2 (CDK2) regulates cell cycle checkpoints in the synthesis and mitosis phases and plays a pivotal role in cancerous cell proliferation. The activation of CDK2, influenced by various protein signaling pathways, initiates the phosphorylation process. Due to its crucial role in carcinogenesis, CDK2 is a druggable hotspot target to suppress cancer cell proliferation. In this context, several studies have identified spirooxindoles as an effective class of CDK2 inhibitors. In the present study, three spirooxindoles (SOI1, SOI2, and SOI3) were studied to understand their inhibitory mechanism against CDK2 through a structure-based approach. Molecular docking and molecular dynamics (MD) simulations were performed to explore their interactions with CDK2 at the molecular level. The calculated binding free energy for the spirooxindole-based CDK2 inhibitors aligned well with experimental results regarding CDK2 inhibition. Energy decomposition (ED) analysis identified key binding residues, including I10, G11, T14, R36, F82, K89, L134, P155, T158, Y159, and T160, in the CDK2 active site and T-loop phosphorylation. Molecular mechanics (MM) energy was identified as the primary contributor to stabilizing inhibitor binding in the CDK2 protein structure. Furthermore, the analysis of binding affinity revealed that the inhibitor SOI1 binds more strongly to CDK2 compared to the other inhibitors under investigation. It demonstrated a robust interaction with the crucial residue T160 in the T-loop phosphorylation site, responsible for kinase activation. These insights into the inhibitory mechanism are anticipated to contribute to the development of potential CDK2 inhibitors using the spirooxindole scaffold.

Predicting FFAR4 agonists using structure-based machine learning approach based on molecular fingerprints.

Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intracellular signaling pathways that regulate various physiological processes. FFAR4 agonists are associated with enhancing insulin release and mitigating the atherogenic, obesogenic, pro-carcinogenic, and pro-diabetogenic effects, normally associated with the free fatty acids bound to FFAR4. In this research, molecular structure-based machine-learning techniques were employed to evaluate compounds as potential agonists for FFAR4. Molecular structures were encoded into bit arrays, serving as molecular fingerprints, which were subsequently analyzed using the Bayesian network algorithm to identify patterns for screening the data. The shortlisted hits obtained via machine learning protocols were further validated by Molecular Docking and via ADME and Toxicity predictions. The shortlisted compounds were then subjected to MD Simulations of the membrane-bound FFAR4-ligand complexes for 100 ns each. Molecular analyses, encompassing binding interactions, RMSD, RMSF, RoG, PCA, and FEL, were conducted to scrutinize the protein-ligand complexes at the inter-atomic level. The analyses revealed significant interactions of the shortlisted compounds with the crucial residues of FFAR4 previously documented. FFAR4 as part of the complexes demonstrated consistent RMSDs, ranging from 3.57 to 3.64, with minimal residue fluctuations 5.27 to 6.03 nm, suggesting stable complexes. The gyration values fluctuated between 22.8 to 23.5 nm, indicating structural compactness and orderliness across the studied systems. Additionally, distinct conformational motions were observed in each complex, with energy contours shifting to broader energy basins throughout the simulation, suggesting thermodynamically stable protein-ligand complexes. The two compounds CHEMBL2012662 and CHEMBL64616 are presented as potential FFAR4 agonists, based on these insights and in-depth analyses. Collectively, these findings advance our comprehension of FFAR4's functions and mechanisms, highlighting these compounds as potential FFAR4 agonists worthy of further exploration as innovative treatments for metabolic and immune-related conditions.

Exploring pyrrolidinyl-spirooxindole natural products as promising platforms for the synthesis of novel spirooxindoles as EGFR/CDK2 inhibitors for halting breast cancer cells.

Cancer represents a global challenge, and the pursuit of developing new cancer treatments that are potent, safe, less prone to drug resistance, and associated with fewer side effects poses a significant challenge in cancer research and drug discovery. Drawing inspiration from pyrrolidinyl-spirooxindole natural products, a novel series of spirooxindoles has been synthesized through a one-pot three-component reaction, involving a [3 + 2] cycloaddition reaction. The cytotoxicity against breast cancer cells (MCF-7 and MDA-MB-231) and safety profile against WISH cells of the newly developed library were assessed using the MTT assay. Compounds 5l and 5o exhibited notable cytotoxicity against MCF-7 cells (IC50 = 3.4 and 4.12 µM, respectively) and MDA-MB-231 cells (IC50 = 8.45 and 4.32 µM, respectively) compared to Erlotinib. Conversely, compounds 5a-f displayed promising cytotoxicity against MCF-7 cells with IC50 values range (IC50 = 5.87-18.5 µM) with selective activity against MDA-MB-231 cancer cells. Compound 5g demonstrated the highest cytotoxicity (IC50 = 2.8 µM) among the tested compounds. Additionally, compounds 5g, 5l, and 5n were found to be safe (non-cytotoxic) against WISH cells with higher IC50 values ranging from 39.33 to 47.2 µM. Compounds 5g, 5l, and 5n underwent testing for their inhibitory effects against EGFR and CDK-2. Remarkably, they demonstrated potent EGFR inhibition, with IC50 values of 0.026, 0.067, and 0.04 µM and inhibition percentages of 92.6%, 89.8%, and 91.2%, respectively, when compared to Erlotinib (IC50 = 0.03 µM, 95.4%). Furthermore, these compounds exhibited potent CDK-2 inhibition, with IC50 values of 0.301, 0.345, and 0.557 µM and inhibition percentages of 91.9%, 89.4%, and 88.7%, respectively, in contrast to Roscovitine (IC50 = 0.556 µM, 92.1%). RT-PCR analysis was performed on both untreated and 5g-treated MCF-7 cells to confirm apoptotic cell death. Treatment with 5g increased the gene expression of pro-apoptotic genes P53, Bax, caspases 3, 8, and 9 with notable fold changes while decreasing the expression of the anti-apoptotic gene Bcl-2. Molecular docking and dynamic simulations (100 ns simulation using AMBER22) were conducted to investigate the binding mode of the most potent candidates, namely, 5g, 5l, and 5n, within the active sites of EGFR and CDK-2.

Evaluation of chalcones as new glycogen phosphorylase inhibitors - an in-vitro and in-silico approach.

Diabetes mellitus (DM) remains one of the pivotal diseases that have drawn the attention of researchers recently and during the last few decades. Due to its devastating symptoms, attempts to develop new drugs with mild side effects have resulted in a number of drugs that are functioning through various mechanisms. Among these, Glycogen phosphorylase (GP) inhibitors emerged as a new strategy for combating DM. GP is an enzyme that regulates blood glucose levels; it catalyses the breakdown of glycogen to glucose-1-phosphate in the liver and tissues with high and fluctuating energy demands. In the present research, we evaluate the possibility of type 2 diabetes therapy with the help of chalcones which are known to have antidiabetic activities. For this purpose, 29 chalcones were modelled, synthesised and investigated for their inhibitory activity against GP using in-vitro methods. Compounds 1, 2, and 3 were found to be the most potent compounds with IC50 values 26.6, 57.1 and 75.6 µM respectively. The observed results were further validated using in-silico methods. Molecular docking simulation revealed interaction patterns that explain the structure-activity relationships of the compounds with GP. Molecular dynamic (MD) simulation demonstrated a stable complex formation between compound 1 and GP through lower value and uniformity in root mean square deviation (RMSD) of the complex and root mean square fluctuation (RMSF) of the protein Cα.

Rhodanine-benzamides as potential hits for α-amylase enzyme inhibitors and radical (DPPH and ABTS) scavengers.

A series of 3-substituted and 3,5-disubstituted rhodanine-based derivatives were synthesized from 3-aminorhodanine and examined for α-amylase inhibitory, DPPH (1,1-diphenyl-2-picrylhydrazyl) and ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical scavenging activities in vitro. These derivatives displayed significant α-amylase inhibitory potential with IC50 values of 11.01-56.04 µM in comparison to standard acarbose (IC50 = 9.08 ± 0.07 µM). Especially, compounds 7 (IC50 = 11.01 ± 0.07 µM) and 8 (IC50 = 12.01 ± 0.07 µM) showed highest α-amylase inhibitory activities among the whole series. In addition to α-amylase inhibitory activity, all compounds also demonstrated significant scavenging activities against DPPH and ABTS radicals, with IC50 values ranging from 12.24 to 57.33 and 13.29-59.09 µM, respectively, as compared to the standard ascorbic acid (IC50 = 15.08 ± 0.03 µM for DPPH; IC50 = 16.09 ± 0.17 µM for ABTS). These findings reveal that the nature and position of the substituents on the phenyl ring(s) are crucial for variation in the activities. The structure-activity relationship (SAR) revealed that the compounds bearing an electron-withdrawing group (EWG) at para substitution possessed the highest activity. In kinetic studies, only the km value was changed, with no observed changes in Vmax, indicating a competitive inhibition. Molecular docking studies revealed important interactions between compounds and the α-amylase active pocket. Further advanced research needs to perform on the identified compounds in order to obtain potential antidiabetic agents.

A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors.

Phosphoinositide 3-kinase alpha (PI3Kα) is one of the most frequently dysregulated kinases known for their pivotal role in many oncogenic diseases. While the side effects linked to existing drugs against PI3Kα-induced cancers provide an avenue for further research, the significant structural conservation among PI3Ks makes it extremely difficult to develop new isoform-selective PI3Kα inhibitors. Embracing this challenge, we herein designed a hybrid protocol by integrating machine learning (ML) with in silico drug-designing strategies. A deep learning classification model was developed and trained on the physicochemical descriptors data of known PI3Kα inhibitors and used as a screening filter for a database of small molecules. This approach led us to the prediction of 662 compounds showcasing appropriate features to be considered as PI3Kα inhibitors. Subsequently, a multiphase molecular docking was applied to further characterize the predicted hits in terms of their binding affinities and binding modes in the targeted cavity of the PI3Kα. As a result, a total of 12 compounds were identified whereas the best poses highlighted the efficiency of these ligands in maintaining interactions with the crucial residues of the protein to be targeted for the inhibition of associated activity. Notably, potential activity of compound 12 in counteracting PI3Kα function was found in a previous in vitro study. Following the drug-likeness and pharmacokinetic characterizations, six compounds (compounds 1, 2, 3, 6, 7, and 11) with suitable ADME-T profiles and promising bioavailability were selected. The mechanistic studies in dynamic mode further endorsed the potential of identified hits in blocking the ATP-binding site of the receptor with higher binding affinities than the native inhibitor, alpelisib (BYL-719), particularly the compounds 1, 2, and 11. These outcomes support the reliability of the developed classification model and the devised computational strategy for identifying new isoform-selective drug candidates for PI3Kα inhibition.

Uncovering PPAR-γ agonists: An integrated computational approach driven by machine learning.

Peroxisome proliferator-activated receptor gamma (PPAR-γ) serves as a nuclear receptor with a pivotal function in governing diverse facets of metabolic processes. In diabetes, the prime physiological role of PPAR-γ is to enhance insulin sensitivity and regulate glucose metabolism. Although PPAR-γ agonists such as Thiazolidinediones are effective in addressing diabetes complications, it is vital to be mindful that they are associated with substantial side effects that could potentially give rise to health challenges. The recent surge in the discovery of selective modulators of PPAR-γ inspired us to formulate an integrated computational strategy by leveraging the promising capabilities of both machine learning and in silico drug design approaches. In pursuit of our objectives, the initial stage of our work involved constructing an advanced machine learning classification model, which was trained utilizing chemical information and physicochemical descriptors obtained from known PPAR-γ modulators. The subsequent application of machine learning-based virtual screening, using a library of 31,750 compounds, allowed us to identify 68 compounds having suitable characteristics for further investigation. A total of four compounds were identified and the most favorable configurations were complemented with docking scores ranging from -8.0 to -9.1 kcal/mol. Additionally, the compounds engaged in hydrogen bond interactions with essential conserved residues including His323, Leu330, Phe363, His449 and Tyr473 that describe the ligand binding site. The stability indices investigated herein for instance root-mean-square fluctuations in the backbone atoms indicated higher mobility in the region of orthosteric site in the presence of agonist with the deviation peaks in the range of 0.07-0.69 nm, signifying moderate conformational changes. The deviations at global level revealed that the average values lie in the range of 0.25-0.32 nm. In conclusion, our identified hits particularly, CHEMBL-3185642 and CHEMBL-3554847 presented outstanding results and highlighted the stable conformation within the orthosteric site of PPAR-γ to positively modulate the activity.

Taming the cytokine storm: small molecule inhibitors targeting IL-6/IL-6α receptor.

Given the increasing effectiveness of immune-based therapies, management of their associated toxicities is of utmost importance. Cytokine release syndrome (CRS), characterized by elevated levels of cytokine, poses a significant challenge following the administration of antibodies and CAR-T cell therapies. CRS also contributes to multiple organ dysfunction in severe viral infections, notably in COVID-19. Given the pivotal role of IL-6 cytokine in initiating CRS, it has been considered a most potential therapeutic target to mitigate hyperactivated immune responses. While monoclonal antibodies of IL-6 show promise in mitigating cytokine storm, concerns about immunotoxicity persist, and small molecule IL-6 antagonists remain unavailable. The present study employed sophisticated computational techniques to identify potential hit compounds as IL-6 inhibitors, with the aim of inhibiting IL-6/IL-6R protein-protein interactions. Through ligand-based pharmacophore mapping and shape similarity in combination with docking-based screening, we identified nine hit compounds with diverse chemical scaffolds as potential binders of IL-6. Further, the MD simulation of 300 ns of five virtual hits in a complex with IL-6 was employed to study the dynamic behavior. To provide a more precise prediction, binding free energy was also estimated. The identified compounds persistently interacted with the residues lining the binding site of the IL-6 protein. These compounds displayed low binding energy during MMPBSA calculations, substantiating their strong association with IL-6. This study suggests promising scaffolds as potential inhibitors of IL-6/IL-6R protein-protein interactions and provides direction for lead optimization.

Indenoquinoxaline-phenylacrylohydrazide hybrids as promising drug candidates for the treatment of type 2 diabetes: In vitro and in silico evaluation of enzyme inhibition and antioxidant activity.

Existing drugs that are being used to treat type-2 diabetes mellitus are associated with several side effects; thus, exploring potential drug candidates is still an utter need these days. Hybrids of indenoquinoxaline and hydrazide have never been explored as antidiabetic agents. In this study, a series of new indenoquinoxaline-phenylacrylohydrazide hybrids (1-30) were synthesized, structurally characterized, and evaluated for α-amylase and α-glucosidase inhibitory activities, as well as for their antioxidant properties. All scaffolds exhibited varying degrees of inhibitory activity against both enzymes, with IC50 values ranging from 2.34 to 61.12 µM for α-amylase and 0.42 to 54.72 µM for α-glucosidase. Particularly, compounds 10, 16, 17, 18, 24, and 25 demonstrated the highest efficacy in inhibiting α-amylase, while compounds 6, 7, 8, 10, 12, 14, 13, 16, 17, 18, 24, and 25 were the most effective α-glucosidase inhibitors, compared to standard acarbose. Moreover, most of these compounds displayed substantial antioxidant potential compared to standard butylated hydroxytoluene (BHT). Kinetics studies revealed competitive inhibition modes by compounds. Furthermore, a comprehensive in silico study and toxicity prediction were also conducted, further validating these analogs as potential drug candidates. The structured compounds demonstrated enhanced profiles, underscoring their potential as primary candidates in drug discovery.

In vitro-in silico pharmacology and chemistry of Stercularin, isolated from Sterculia diversifolia.

Stercularin is a coumarin, isolated from the ethyl acetate fraction of stem bark and leaves of S. diversifolia. Pharmacologically it is active against cancer, diabetes, and inflammation etc. The molecule is further screened for in vitro pharmacological activities. In addition, a detailed description on its drug likeness and pharmacokinetic profile has been established to further explore its fate as a drug candidate. Stercularin exhibited antiglycation, immunomodulatory, and leishmanicidal activity in three different in vitro models. The IC50 values obtained in these three assays were 80.22 ± 0.46 mg/ml, 12.8 ± 1.6 µg/ml, and 8.32 ± 0.42 µg/ml, respectively. In case of drug likeness evaluation, Stercularin has acceptable physicochemical properties and compliant with major drug likeness descriptors i.e., Lipinski rule, Pfizer rule, GSK rule, and "golden triangle". Accepting Lipinski rule implies the oral drug development of Stercularin. Pharmacokinetically, Stercularin is permeable to Caco-2 and MDCK cell lines. 'Boiled-egg' plot suggest intestinal route of absorption, blood brain barrier nonpermeating, and not affected by p-glycoprotein. Stercularin has high plasma protein binding with low free fraction circulating in the plasma. Stercularin proved to be the substrate and/or inhibitor of CYP 450 system with a moderate half-life and clearance rate to allow flexible dosing regimen. Finally, slight risk of toxicity exists for Stercularin, but not being limiting factors of drug knock out. A nature isolated Stercularin possess pharmacological activities and is predicted to have acceptable pharmacokinetic profile. Further drug development and in vivo studies are desirable for optimization.

Oxadiazole Derivatives of Diclofenac as an Anti-proliferative Agent for B-cell Non-Hodgkin Lymphoma: An In vitro and In Silico Studies.

BACKGROUND: Non-Hodgkin lymphoma of B cell origin is the common type of lymphoma- related malignancy with poor response rate with conventional front-line therapies. AIM: The aim of the present study was to investigate the potential of new anti-inflammatory oxadiazole derivatives of Diclofenac as an anti-lymphoma agent through in vitro and in silico approaches. METHODS: Anti-lymphoma potential was evaluated by alamar blue technique. MTT assay employed for cytotoxicity. Gene and protein expression studies was performed by qRT-PCR and ELISA respectively. Docking studies was performed by using MOE program. RESULTS: Among five diclofenac derivatives, (II) showed promising anti-lymphoma effects, where it inhibited the expression of BCL-2, p-38 MAPK and TGF-ß in both follicular and Burkitt's lymphoma cells and was non-toxic against normal human fibroblast cells. The in silico studies against BCL-2 revealed that the unsubstituted Sulphur group in (II) is involved in the crucial interactions with the binding site residue. CONCLUSION: The compound (II) can be a potential therapeutic candidate for B-cell non-Hodgkin lymphoma and deserves further development as a novel anti-lymphoma agent.

Unraveling the versatility of human serum albumin - A comprehensive review of its biological significance and therapeutic potential.

Human serum albumin (HSA) is a multi-domain macromolecule with diverse ligand binding capability because of its ability to allow allosteric modulation despite being a monomeric protein. Physiologically, HSA act as the primary carrier for various exogenous and endogenous compounds and fatty acids, and alter the pharmacokinetic properties of several drugs. It has antioxidant properties and is utilized therapeutically to improve the drug delivery of pharmacological agents for the treatment of several disorders. The flexibility of albumin in holding various types of drugs coupled with a variety of modifications makes this protein a versatile drug carrier with incalculable potential in therapeutics. This review provides a brief outline of the different structural properties of HSA, and its various binding sites, moreover, an overview of the genetic, biomedical, and allosteric modulation of drugs and drug delivery aspects of HSA is also included, which may be helpful in guiding advanced clinical applications and further research on the therapeutic potential of this extraordinary protein.

Levetiracetam ameliorates epileptogenesis by modulating the adenosinergic pathway in a kindling model of epilepsy in mice.

Background: Levetiracetam (LEV) has been found to have an antihyperalgesic effect via acting on the adenosine system. However, the effects of LEV on the modulation of the adenosine system in the brain have not been elucidated in the prevention of seizures and epilepsy. The present study aimed to explore the possible LEV mechanisms of action in the adenosine signaling systems in an animal model of epilepsy. Methodology: A docking study was initially performed to determine the possible interaction of LEV with adenosine A1 receptors (A1Rs) and equilibrative nucleoside transporters-1 (ENT1). The experimental study was divided into an acute seizure test (32 mice distributed into 4 groups) and a chronic kindling model study (40 mice distributed into 5 groups), followed by gene expression analysis and immunohistochemistry. The kindling model lasted 26 days and took 13 subconvulsive doses of pentylenetetrazole (PTZ) to completely kindle the mice in the PTZ control group. Gene expression changes in the A1Rs, potassium inwardly-rectifying channel 3.2 (Kir3.2), and ENT1 in the brain tissue samples of the mice following treatment with LEV were analyzed using reverse transcription-quantitative polymerase chain reaction, and immunohistochemistry was performed for the A1R protein expression. Results: Docking studies predicted a significant interaction of LEV with A1Rs and ENT1 proteins. Results from the acute testing revealed that caffeine (100 mg/kg) and 8-cyclopentyl-1,3-dipropylxanthine (25 mg/kg) significantly reversed the antiseizure effects of LEV by reversing the percent protection and shortening the onset of the first myoclonic jerk (FMJ) and generalized clonic seizures (GCSs). In the PTZ-induced kindling, LEV demonstrated an increased gene expression of A1Rs and Kir3.2 in the brain. LEV also significantly reduced the gene expression of ENT1. Furthermore, the immunohistochemical analysis showed that LEV increased the protein expression of A1Rs in the brain. Conclusion: Based on these results, it can be concluded that LEV modulates epileptogenesis by acting on the adenosine pathway in the central nervous system.

Phytochemical characterization and anti-arthritic potential of Croton bonplandianus leaves extract: In-vivo and in-silico approach.

Croton bonplandianus, a natural source traditionally used for treating various illnesses, including rheumatoid arthritis, was evaluated in this study. The effects of ethanolic extracts (CBEE) and aqueous fractions (CBAF) of C. bonplandianus leaves on arthritis-induced inflammation were studied using an albino rat model of inflammation induced by Freund's complete adjuvant. Eight test groups (n = 5 per group) and one vehicle control were used to evaluate the antiarthritic effects of different doses of CBEE and CBAF (125 mg.kg-1, 250 mg.kg-1, and 500 mg.kg-1) on days 5, 10, 15, and 20 compared to arthritic and vehicle controls. Arthritis severity was assessed using macroscopic arthritis grading, histological analysis, body weights, and paw thickness. CBEE and CBAF were found to reduce the prevalence of arthritis, increase body weight, and decrease paw inflammation compared to the vehicle control group by the 23rd day. In addition, they showed no effect on biochemical parameters, but a significant difference (p < 0.05) in hematological parameters compared to the arthritic control group. The study identified Hentriacontane compound as a potential contributor to the anti-inflammatory effect of C. bonplandianus, as it showed the lowest dock score for IL-1ß and IL-6. Palmitoylethanol amide was identified as a potential contributor to the anti-inflammatory effect of TNF-α. Gene expression of IL-6, IL-1ß, and TNF-α was down-regulated significantly (p < 0.05) in a dose-dependent manner in all treatment groups compared to the arthritic control group. In conclusion, this study validated the anti-arthritic and anti-inflammatory properties of CBEE and CBAF in a time and dose-dependent manner.