High Affinity Binding Research Articles

Hydroxyl functionalized hexagonal boron nitride quantum dots as nanozyme for pesticides sensing through dual colorimetric and fluorometric platform: A combined experimental and theoretical study

The Hydroxyl-functionalized hexagonal boron nitride quantum dots (h-BN QDs) were synthesized using a hydrothermal technique in a water medium, exhibiting stability in water for over 90 days. The present study demonstrates two simple fluorescence and colorimetric techniques for sensing organophosphorus (OP) and organochloride (OC) pesticides (atrazine, simazine and chlorpyrifos) in an aqueous medium using hydroxyl-functionalized h-BN QDs. The sensing capability of h-BN QDs for these pesticides was determined to be in the range of 5–10 µM using both techniques. The hydroxyl groups on the surface of the QDs enhanced dispersibility and enabled peroxidase-like catalytic activity in acidic conditions. The radical generation using hydroxyl-functionalized h-BN QDs in the presence of H2O2 upon 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) oxidation plays a significant role in the peroxidase reaction. The hydrogen bonding and π-π interactions between the pesticide molecules and ABTS can enhance the pesticide sensing performance. The limit of detection (LOD) using ABTS for atrazine, simazine, and chlorpyrifos was 6.11, 6.56, and 2.47 µM, respectively. Fluorescence sensing, based on a turn ON/OFF mechanism, demonstrated high specificity and sensitivity with LODs of 5.59, 6.45, and 8.08 µM for the same pesticides. The DFT studies revealed non-covalent bonding, such as hydrogen bonding, π-π interactions between the pesticides and the h-BN QDs, indicating binding affinities and stabilization energies of the complexes which can detect pesticides effectively. Atrazine exhibited higher binding affinity towards h-BN QDs, followed by simazine and chlorpyrifos. The h-BN QDs provide a new insight into bonding with pesticides, enhancing the peroxidase mimetic and fluorescence activity.

TC-DTA: Predicting Drug-Target Binding Affinity With Transformer and Convolutional Neural Networks.

Bioinformatics is a rapidly evolving field that applies computational methods to analyze and interpret biological data. A key task in bioinformatics is identifying novel drug-target interactions (DTIs), which plays a crucial role in drug discovery. Most computational approaches treat DTI prediction as a binary classification problem, determining whether drug-target pairs interact. However, with the growing availability of drug-target binding affinity data, this binary task can be reframed as a regression problem focused on drug-target affinity (DTA). DTA quantifies the strength of drug-target binding, offering more detailed insights than DTI and serving as a valuable tool for virtual screening in drug discovery. Accurately predicting compound interactions with targets can accelerate the drug development process. In this study, we introduce a deep learning model named TC-DTA for DTA prediction, leveraging convolutional neural networks (CNN) and the encoder module of the transformer architecture. We begin by extracting raw drug SMILES strings and protein amino acid sequences from the dataset, which are then represented using various encoding methods. Subsequently, we employ CNN and the transformer's encoder module to extract features from the drug SMILES strings and protein sequences, respectively. Finally, the feature information is concatenated and input into a multi-layer perceptron to predict binding affinity scores. We evaluated our model on two benchmark DTA datasets, Davis and KIBA, comparing it with methods such as KronRLS, SimBoost, and DeepDTA. Our model, TC-DTA, outperformed these baseline methods based on evaluation metrics like Mean Squared Error (MSE), Concordance Index (CI), and Regression towards the Mean Index ( rm2 ). These results highlight the effectiveness of the Transformer's encoder and CNN in extracting meaningful representations from sequences, thereby enhancing DTA prediction accuracy. This deep learning model can accelerate drug discovery by identifying drug candidates with high binding affinity to specific targets. Compared to traditional methods, machine learning technology offers a more effective and efficient approach to drug discovery.

Anti-quorum sensing and anti-biofilm activities of Pasteurella multocida strains.

A total of 52 Pasteurella multocida strains of capsular serogroups (A, B and D) were screened for anti-quorum sensing activity against Chromobacterium violaceum. Of which, 12 strains of serogroups A were found to possess anti-quorum sensing activity. Inhibition activity was highest for strain NIVEDIPm9 and lowest for strain NIVEDIPm30 based on zone of pigment inhibition. Further, cell free extract of NIVEDIPm9 strain showed highest anti-biofilm activity in reference E. coli strain and concentration dependent degradation activity of C6-AHL molecule. In whole genome sequence annotation of NIVEDIPm9 strain predicted the presence of four metallo-β-lactamases (MBL) fold metallo-hydrolase proteins. In docking studies, MBL1 and MBL3 proteins showed high binding affinity with autoinduce signalling molecules AHL compound of OH-C10, binding energy value were -6.3 and -6.2kcal/mol. Interaction study of VAF and quorum sensing molecules showed that OmpA and HgbA proteins were stimulated by all the ten molecules (C4-AHLs, C6-AHLs, C10-AHLs, C14-AHLs, 3-oxo-C10-AHLs, 3OH-C10-HSL, C8-HSL, C10-HSL, C12-HSL, C14-HSL), while toxA gene was stimulated by OH-C10-AHL molecule, sodC gene was stimulated by none. In conclusion, we described the anti-quorum sensing activities of diverse P. multocida strains causing Pasteurellosis in livestock.

ANTIPASTI: Interpretable prediction of antibody binding affinity exploiting normal modes and deep learning.

The high binding affinity of antibodies toward their cognate targets is key to eliciting effective immune responses, as well as to the use of antibodies as research and therapeutic tools. Here, we propose ANTIPASTI, a convolutional neural network model that achieves state-of-the-art performance in the prediction of antibody binding affinity using as input a representation of antibody-antigen structures in terms of normal mode correlation maps derived from elastic network models. This representation captures not only structural features but energetic patterns of local and global residue fluctuations. The learnt representations are interpretable: they reveal similarities of binding patterns among antibodies targeting the same antigen type, and can be used to quantify the importance of antibody regions contributing to binding affinity. Our results show the importance of the antigen imprint in the normal mode landscape, and the dominance of cooperative effects and long-range correlations between antibody regions to determine binding affinity.

Design, synthesis, and pharmacological characterization of sulfonylurea-based NLRP3 inhibitors: Towards an effective therapeutic strategy for Alzheimer's disease

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that severely diminishes the quality of life for millions. The NLRP3 inflammasome, a critical mediator of inflammation, has emerged as a promising therapeutic target for AD. In this study, we report the development and optimization of a novel series of sulfonylurea-based NLRP3 inhibitors, with a focus on compound MC1 for the treatment of AD. Utilizing the co-crystal structure of MCC950 in complex with NLRP3 as a guide, we employed a hybrid approach of computer-aided drug design and traditional medicinal chemistry to perform two iterative optimization cycles. This strategy led to the synthesis and evaluation of 40 sulfonylurea derivatives, culminating in the identification of MC1 as the lead candidate. MC1 exhibited enhanced NLRP3 inhibitory activity and demonstrated high binding affinity to NLRP3, effectively blocking NLRP3 activation induced by diverse stimuli such as ATP and Nigericin, without perturbing upstream processes like reactive oxygen species (ROS) generation. In vivo experiments in AD mouse models revealed that MC1 significantly ameliorated cognitive deficits, surpassing the performance of MCC950. Importantly, MC1 showed no signs of hepatotoxicity or adverse effects on the central nervous system. These findings suggest that MC1 holds strong potential as a lead compound for further development in AD therapy, providing a new scaffold for NLRP3 inhibition with improved safety and efficacy profiles.

Effects of Laurus extract against cadmium-induced neurotoxicity in rats

Cadmium (Cd) is a hazardous heavy metal with widespread environmental presence, posing significant threats to human and animal health. This study investigates the neurotoxic effects of Cd exposure and explores the therapeutic efficacy of Laurus nobilis L. in counteracting these adverse effects. Cd exposure induces oxidative stress and neurotoxicity, leading to neuronal damage and histopathological alterations. Laurus, known for its antioxidant properties, is assessed for its potential in mitigating Cd-induced neurotoxicity through in vitro antioxidant assays, GC–MS analysis, HPLC profiling, and experimental animal models. Results demonstrate that Laurus ethanolic extract exhibits significant antioxidant activity, attributed to its phenolic and flavonoid constituents. GC–MS analysis reveals various bioactive compounds in the extract, including Hexadecanoic acid methyl ester and (Z)-13-Docosenamide, which posses neuroprotective properties. HPLC analysis identifies phenolic compounds such as ellagic acid and flavonoids like rutin and kaempferol in the extract. In vivo studies in rats exposed to Cd demonstrate that Laurus extract administration mitigates Cd-induced alterations in body and brain weight, hematological parameters, liver and kidney function, oxidative stress markers, and acetylcholinesterase (AchE) activity. Histopathological examination confirms the protective effects of Laurus against Cd-induced neuronal damage. The SOD model, validated with high resolution (2.05 Å) and strong R values (work: 0.192, free: 0.236, observed: 0.194), shows strong structural stability (C-score: 0.30). Docking studies reveal high binding affinities of kaempferol (−8.1 kcal/mol) and rutin (−8.7 kcal/mol) with SOD with kaempferol demonstrating superior solubility, lipophilicity, and drug-likenessSimulation analysis confirms the protein’s flexibility and adaptability, highlighting its therapeutic potential, especially with kaempferol. These findings suggest the therapeutic potential of Laurus. as a natural remedy for Cd-induced neurotoxicity, highlighting its antioxidant and neuroprotective properties.

Diosgenin Alleviates Obesity-Induced Insulin Resistance by Modulating PI3K/Akt Signaling Pathway in Mice Fed a High-Fat Diet.

Obesity is a global medical issue that can be effectively treated by relieving adipose inflammation and subsequent insulin resistance. Diosgenin (DIOS) has various effects as a steroidal saponin in inflammatory disorders. This study explored the effects and mechanism of DIOS on adipose inflammation and insulin sensitivity, both in silico and in vivo. The high-fat diet-induced obesity model in C57BL/6 mice was divided into five groups: normal chow (NC), high-fat diet (HFD), HFD with atorvastatin 10 mg/kg (AT), HFD with DIOS 100 mg/kg (DIOS 100), and HFD with DIOS 200 mg/kg (DIOS 200). Each group underwent an oral intervention for seven weeks. DIOS significantly suppressed weight gain in the body, liver, and epididymal fat pads. Additionally, it significantly improved fasting glucose and insulin levels, homeostatic model assessment of insulin resistance (HOMA-IR), and oral glucose tolerance test results, and reduced the proportion of total and M1 adipose tissue macrophages. Significant changes were shown in mRNA expression of janus kinase 2 (JAK2), insulin receptor (INRS), insulin receptor substrate 1 (IRS-1), phosphatidylinositol 3-kinase (PI3K), and protein kinase B (Akt), all of which exhibited high binding affinity in the in silico. Safety indices, including aspartate aminotransferase (AST), alanine transaminase (ALT), and creatinine level indicated the preventive effects of DIOS. In conclusion, DIOS improves insulin resistance and obesity-associated inflammation via the PI3K/Akt signaling pathway.

1,3,4-oxadiazoles as inhibitors of the atypical member of the BET family bromodomain factor 3 from Trypanosoma cruzi (TcBDF3).

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, affects millions globally, with increasing urban cases outside of Latin America. Treatment is based on two compounds, namely, benznidazole (BZ) and nifurtimox, but chronic cases pose several challenges. Targeting lysine acetylation, particularly bromodomain-containing proteins, shows promise as a novel antiparasitic target. Our research focuses on TcBDF3, a cytoplasmic protein, which is crucial for parasite differentiation that recognizes acetylated alpha-tubulin. In our previous study, A1B4 was identified as a high-affinity binder of TcBDF3, showing significant trypanocidal activity with low host toxicity in vitro. In this report, the binding of TcBDF3 to A1B4 was validated using differential scanning fluorescence, fluorescence polarization, and molecular modeling, confirming its specific interaction. Additionally, two new 1,3,4-oxadiazoles derived from A1B4 were identified, which exhibited improved trypanocide activity and cytotoxicity profiles. Furthermore, TcBDF3 was classified for the first time as an atypical divergent member of the bromodomain extraterminal family found in protists and plants. These results make TcBDF3 a unique target due to its localization and known functions not shared with higher eukaryotes, which holds promise for Chagas disease treatment.

Quercetin Attenuates MRGPRX2-Mediated Mast Cell Degranulation via the MyD88/IKK/NF-κB and PI3K/AKT/ Rac1/Cdc42 Pathway.

CMRF35-like molecule-1 (CLM-1) is a receptor of the CD300 family that inhibits MRGPRX2-mediated mast cell degranulation. Understanding the role and mechanism of CLM-1 agonist has significant implications for the treatment of allergic disease. Quercetin is a natural small molecule compound derived from plants and vegetables that has been shown to prevent histamine release by immune cells. This study aims to examine the inhibitory effects of quercetin on MRGPRX2-mediated mast cell degranulation via CLM-1. We found that C48/80 stimulation resulted in significantly increased release of β-hexosaminidase, histamine and Ca2+ in CLM-1-knockdown LAD2 cells than in NC-LAD2 cells. Surface plasmon resonance (SPR) and molecular docking analyses revealed high-affinity binding between quercetin and CLM-1 (K D = 2.962×10-5 mol/L) mediated by the formation of hydrogen bonds. In addition, quercetin can selectively bind to CLM-1 on mast cells, leading to SHP-1 phosphorylation and subsequent inhibition of downstream MyD88/IKK/NF-κB signaling. Furthermore, activation of CLM-1 modulated the surface expression of MRGPRX2 by inhibiting F-actin, leading to internalization of the MRGPRX2 receptor via the PI3K/AKT/ Rac1/Cdc42 pathway. Quercetin is a promising treatment for allergic diseases by acting as a CLM-1 agonist that inhibits MRGPRX2-mediated mast cell degranulation.

Gamma Irradiation and Exogenous Proline Enhanced the Growth, 2AP Content, and Inhibitory Effects of Selected Bioactive Compounds against α-Glucosidase and α-Amylase in Thai Rice.

Exogenous proline can improve the growth, aroma intensities, and bioactive compounds of rice. This study evaluated the effects of gamma irradiation under proline conditions on the 2-acetyl-1-pyrroline (2AP), phenolic, and flavonoid contents of rice. Moreover, the bioactive compounds of gamma-irradiated rice under proline conditions that inhibited α-glucosidase and α-amylase were evaluated by in silico study. A low gamma dose (40 Gy) induced the highest rice growth under 5 mM proline concentration. The highest 2AP content was stimulated at a gamma dose of 5－100 Gy under 10 mM proline concentration. At 500 and 1,000 Gy gamma dose, the highest flavonoid and phenolic contents of rice were stimulated. 1-(2-Hydroxy-5-methylphenyl)-ethanone, which had the highest binding affinity (-7.9 kcal/mol) against α-glucosidase, was obtained at 500 and 1,000 Gy gamma dose under 5 and 10 mM proline concentrations. Meanwhile, 6-amino-1,3,5-triazine-2,4(1H,3H)-dione, which had the highest binding affinity (-6.3 kcal/mol) against α-amylase, was obtained under 10 mM proline concentration in non-gamma-irradiated rice. The results indicate that using a combination of gamma irradiation and exogenous proline is suitable for producing new rice varieties. Moreover, the bioactive compounds that were obtained in new rice varieties exhibited health benefits, especially for diabetes mellitus treatment (inhibition of α-glucosidase and α-amylase).

Identification of steroidal cardenolides from Calotropis procera as novel HIV-1 PR inhibitors: A molecular docking & molecular dynamics simulation study.

Background & objectives Despite advancements in antiretroviral therapy, drug-resistant strains of HIV (human immunodeficiency virus) remain a global health concern. Natural compounds from medicinal plants offer a promising avenue for developing new HIV-1 PR (protease) inhibitors. This study aimed to explore the potential of compounds derived from Calotropis procera, a medicinal plant, as inhibitors of HIV-1 PR. Methods This in silico study utilized natural compound information and the crystal structure of HIV-1 PR. Molecular docking of 17 steroidal cardenolides from Calotropis procera against HIV-1 PR was performed using AutoDock 4.2 to identify compounds with higher antiviral potential. A dynamic simulation study was performed to provide insights into the stability, binding dynamics, and potential efficacy of the top potential antiviral compound as an HIV-1 therapeutic. Results We found that all tested cardenolides had higher binding affinities than Amprenavir, indicating their potential as potent HIV-1 PR inhibitors. Voruscharin and uscharidin displayed the strongest interactions, forming hydrogen bonds and hydrophobic interactions with HIV-1 PR. Voruscharin showed improved stability with lower RMSD (Root Mean Square Deviation) values and reduced fluctuations in binding site residues but increased flexibility in certain regions. The radius of gyration analysis confirmed a stable binding pose between HIV-1 PR and Voruscharin. Interpretation & conclusions These findings suggest that Calotropis procera could potentially be a source of compounds for developing novel HIV-1 PR inhibitors, contributing to the efforts to combat HIV. Further studies and clinical trials are needed to evaluate the safety and efficacy of these compounds as potential drug candidates for the treatment of HIV-1 infection.

Assessing the Inhibitory Potential of Pregnenolone Sulfate on Pentraxin 3 in Diabetic Kidney Disease: A Molecular Docking and Simulation Study.

Diabetic Kidney Disease (DKD), a frequent consequence of diabetes, has substantial implications for both morbidity and mortality rates, prompting the exploration of new metabolic biomarkers due to limitations in current methods like creatinine and albumin measurements. Pentraxin 3 (PTX3) shows promise for assessing renal inflammation in DKD. This study investigates how DKD metabolites could influence PTX3 expression through molecular docking, ADMET profiling, and dynamic simulation. Network and pathway analyses were conducted to explore metabolite interactions with DKD genes and their contributions to DKD pathogenesis. Thirty-three DKD-associated metabolites were screened, using pentoxifylline (PEN) as a reference. The pharmacokinetic properties of these compounds were evaluated through molecular docking and ADMET profiling. Molecular dynamics simulations over 200 ns assessed the stability of PTX3 (apo), the PRE-PTX3 complex, and PEN-PTX3 across multiple parameters. Cytoscape identified 1082 nodes and 1381 edges linking metabolites with DKD genes. KEGG pathway analysis underscored PTX3's role in inflammation. Molecular docking revealed pregnenolone sulfate (PRE) with the highest binding affinity (-6.25 kcal/mol), followed by hydrocortisone (-6.03 kcal/mol) and 2-arachidonoylglycerol (-5.92 kcal/mol), compared to PEN (-5.35 kcal/mol). ADMET profiling selected PRE for dynamic simulation alongside PEN. Analysis of RMSD, RMSF, RG, SASA, H-bond, PCA, FEL, and MM-PBSA indicated stable complex behavior over time. Our findings suggest that increasing PRE levels could be beneficial in managing DKD, potentially through isolating PRE from fungal sources, synthesizing it as dietary supplements, or enhancing endogenous PRE synthesis within the body.

Identification of Novel Compounds Targeting the Liver X Receptor (LXR): In-silico Studies, Screening, Molecular Docking, and Chemico-pharmacokinetic Analysis

Studies have demonstrated the association between LXR activity dysregulation with many diseases, including atherosclerosis, diabetes and cancer. In recent years, several LXR agonists have surfaced, but none have been approved for human use due to adverse effects or unforeseen reasons. In this study, we first analysed the mRNA and protein expression of LXRs across tissues, network and pathway analysis, and reinterpreted their physiological function and disease association by utilizing multiple biological data repositories, including RNA-seq human protein atlas, DisGeNET, etc. Then, we performed ligand-based virtual screening, chemico-pharmacokinetic analysis, docking and simulation to identify potential new compounds. Our findings of mRNA, protein expression, network and disease enrichment analysis reveal diverse physiological functions of LXRs addressing the possibility of pharmacological manipulation with small molecules would provide therapeutic strategies for disease management. Evaluation of the docking and chemico-pharmacokinetic properties directed to the selection of LXR-623 and AZ876 as promising candidates for LXR-α and LXR-β for further in-silico investigation. Comprehensive screening for new ligands targeting LXRs based on the chemical structures of LXR-623 and AZ876, identified ZINC000005399501 and ZINC000021912941 with the highest binding affinity (−9.8 and −10.7 kcal/mol) for LXRα and LXRβ, respectively. Our results also supported in simulation study, along with favorable chemico-pharmacokinetic features.

Molecular Docking, Pharmacophore Modeling, and ADMET Prediction of Novel Heterocyclic Leads as Glucokinase Activators.

A pivotal impetus has driven the development of numerous small molecules aiming to improve therapeutic strategies for type 2 diabetes. Glucokinase (GK) activation has been offered a new realm of therapeutic antidiabetic activity with novel heter-ocyclic derivatives. In the context of antidiabetic drug design, GK is an interesting and newly validated target. A key enzyme needed for blood glucose homeostasis is Glucokinase, which is dysfunctional in individuals with type 2 diabetes. Heterocyclic derivatives are utilized in this innovative approach to activate GK enzymes as medicinal agents that will significantly improve type 2 diabetes management. To address type 2 diabetes, as well as minimize unwanted side effects, this research endeavor aimed to develop activators of glucokinase. A rigorous scrutiny was conducted of the Maybridge online repository, which houses a formidable collection of 53,000 lead compounds. A collection of 125 compounds that contain the thiazolidinedione core was selected from this extensive collection. The struc-tures were generated using ChemDraw 2D, stabilized conformation with ChemBioDraw Ul-tra, and docked using Auto Dock Vina 1.5.6 in this methodology. In addition, log P was pre-dicted online using the Swiss ADME algorithm. The PKCSM software was used to predict the toxicity of the leading compounds. The highest binding affinity was found for AS72 and AS108 to GK receptors. GI absorption and excretion of these compounds were efficient due to Lipinski's Rule of Five compliance. When compared with the standard drugs Dorzagliatin (GKA) and MRK (co-crys-tallized ligand), these substances demonstrated a notable lack of AMES toxicity, skin sensiti-zation, and hepatotoxicity. In recent studies, lead molecules that possess enhanced pharmacokinetic profiles, increased binding affinity, and lower toxicity were developed to act as glucokinase activators.

AI-driven antibody design with generative diffusion models: current insights and future directions.

Therapeutic antibodies are at the forefront of biotherapeutics, valued for their high target specificity and binding affinity. Despite their potential, optimizing antibodies for superior efficacy presents significant challenges in both monetary and time costs. Recent strides in computational and artificial intelligence (AI), especially generative diffusion models, have begun to address these challenges, offering novel approaches for antibody design. This review delves into specific diffusion-based generative methodologies tailored for antibody design tasks, de novo antibody design, and optimization of complementarity-determining region (CDR) loops, along with their evaluation metrics. We aim to provide an exhaustive overview of this burgeoning field, making it an essential resource for leveraging diffusion-based generative models in antibody design endeavors.

A suboptimal OCT4-SOX2 binding site facilitates the naïve-state specific function of a Klf4 enhancer.

Enhancers have critical functions in the precise, spatiotemporal control of transcription during development. It is thought that enhancer grammar, or the characteristics and arrangements of transcription factor binding sites, underlie the specific functions of developmental enhancers. In this study, we sought to identify grammatical constraints that direct enhancer activity in the naïve state of pluripotency, focusing on the enhancers for the naïve-state specific gene, Klf4. Using a combination of biochemical tests, reporter assays, and endogenous mutations in mouse embryonic stem cells, we have studied the binding sites for the transcription factors OCT4 and SOX2. We have found that the three Klf4 enhancers contain suboptimal OCT4-SOX2 composite binding sites. Substitution with a high-affinity OCT4-SOX2 binding site in Klf4 enhancer E2 rescued enhancer function and Klf4 expression upon loss of the ESRRB and STAT3 binding sites. We also observed that the low-affinity of the OCT4-SOX2 binding site is crucial to drive the naïve-state specific activities of Klf4 enhancer E2. Altogether, our work suggests that the affinity of OCT4-SOX2 binding sites could facilitate enhancer functions in specific states of pluripotency.

Molecular Docking Insights into Gatifloxacin Derivatives as Prospective Antidepressant Agents

ABSTRACT: The current focus in drug discovery aims to identify promising therapeutic candidates for further research. Depression, a significant public health issue, is closely linked to low serotonin levels. Researchers are investigating novel antidepressant agents through chemical modifications and protein analysis. The various derivatives are assessed for their antidepressant activity through in silico molecular docking simulations by using AutoDock and ADME analysis. Autodock includes formation of PDBQT files, docking of converted ligands and protein forms, formation of 9 different positions of docked molecules results into binding score, 2D image and 3D images of same one. Docking studies reveal molecular interactions between biological macromolecules (8FSB) and ligands, with strong protein-ligand interactions potentially inhibiting the reuptake of serotonin at the post-synaptic nerve, thereby increasing serotonin availability and exerting antidepressant effects. Gatifloxacin derivatives demonstrated higher binding affinities with 8FSB, Gati I (-11.4 kcal/mol), Gati II (-11.1 kcal/mol), Gati III (-8.2 kcal/mol), Gati IV (-7.9 kcal/mol), Gati V (-9.5 kcal/mol), and Gati VI (-9.7 kcal/mol), all exceeding gatifloxacin (-6.9 kcal/mol). These findings suggest that gatifloxacin derivatives may serve as potent antidepressants of drug discovery lies in the synergistic use of in vitro and in vivo studies, leveraging technological advancements to develop safer and more effective therapies. The findings related to gatifloxacin derivatives highlight the potential of these approaches in identifying novel antidepressants, paving the way for further research and clinical trials.

In silico and in vitro evaluation of compounds from Methanol whole extracts of Solanum aculeastrum Dunal berries against benign prostatic hyperplasia and prostate cancer

Background: This study evaluated anti-prostate potentials of compounds from methanol extract of Solanum aculeastrum Dunal berries (MESADB) against benign prostatic hyperplasia (BPH) and prostate cancer (PC). Methods: We used Swiss ADME and pKCSM tools to select drug-like candidates from MESADB. DisGeNET and related databases were used to identify targets for compounds of MESADB, BPH and PC. Molecular roles, biological processes, cellular components involved, and crucial pathways associated with biological processes of gene enrichment were obtained using Gene Ontology (GO) & Kyoto Encyclopedia of Genes and Genomes (KEGG), respectively. Docking was achieved using VINA tool. Antiproliferative and gene expression profiling were determined using 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) bioassay, and RT-qPCR respectively, and data analyzed using Graph Pad Prism (version 8.4). Results: Three ideal drug-like candidates [Undecane; D-Arabinitol; and 9-Oxabicyclo [3.3.1] nonan-2-one,6-hydroxy-] were identified. Key targets included TLR4, PTGS2, STAT3, ESR1, MTOR, SRC, MMP9, HDAC1, AKT1 and EGFR. GO analysis revealed key targets were mainly enriched in 601 biological processes (BP), 53 molecular function (MF) and 24 cellular components (CC) terms (p < 0.05). KEGG analysis presented pathways for cancer, pathway of proteoglycans in cancer, amongst others. Docking revealed [D-Arabinitol; and 9-Oxabicyclo [3.3.1] nonan-2-one,6-hydroxy-] demonstrated high binding affinity with PTGS2 and EGFR. MESADB significantly (p < 0.0001) inhibited growth of DU-145 cells with IC50 value and selectivity index of 5.11μg/ml and 14.84, respectively, while sparing Vero CCL-81 cells. There were significant (p < 0.0001) downregulations of EGFR, PTGS2 and BCL-2, in treated DU-145 cells compared to control. Conclusion: MESADB possesses antiprostate potentials.

THIOSTREPTON MODULATES TLR4 EXPRESSION AND INDUCES APOPTOSIS IN MDA MB 231 CELLS: AN IN VITRO AND IN SILICO ANALYSIS

Objective: Toll-like receptors (TLRs) are key pattern recognition receptors involved in tumorigenesis, apoptosis, and metastasis. Triple-negative breast cancer (TNBC) is a highly aggressive malignancy with a poor prognosis. Although the role of TLRs in breast cancer remains underexplored, recent studies suggest targeting TLRs in TNBC could be beneficial. In this study Thiostrepton, an antibiotic and novel inhibitor of TLR7-9 in psoriatic inflammation, was investigated for its effects on TLR3, TLR4, and TLR9 expression in TNBC cells (MDA-MB-231). Materials and Methods: The cytotoxicity of thiostrepton was assessed using the MTT assay. RT-PCR was used to measure gene expression levels of TLR3, TLR4, TLR9, Bax, Bcl-2, Nf-κB, and E-cadherin. Cell morphology changes were analyzed with Acridine Orange/Ethidium Bromide (AO/EtBr) staining. Molecular docking and dynamics simulations examined interactions between thiostrepton and the TLR4-MD-2 complex. Results: Thiostrepton led to a concentration- and time-dependent decrease in cell viability. It significantly inhibited TLR4, Bcl-2 gene expression and increased TLR3, Bax, and Nf-κB levels. The changes in Bax and Bcl-2 gene expression, along with alterations in cell morphology, demonstrated that thiostrepton promoted apoptosis in MDA-MB-231 cells. While TLR9 expression reduction was not significant, thiostrepton notably increased TLR3 expression and decreased TLR4 expression. The three independent molecular dynamics simulations demonstrated that thiostrepton binds stably to the TLR4-MD2 domain, exhibiting a high binding affinity as indicated by the binding free energy calculations. Conclusion: Thiostrepton effectively induces apoptosis and reduces cell viability in TNBC cells. In silico analysis suggest thiostrepton could modulate TLR4, highlighting its potential as a candidate for further research and therapeutic development.

Differential expression of ST6GALNAC1 and ST6GALNAC2 and their clinical relevance to colorectal cancer progression.

Colorectal cancer (CRC) has become a significant global health concern and ranks among the leading causes of morbidity and mortality worldwide. Due to its malignant nature, current immunotherapeutic treatments are used to tackle this issue. However, not all patients respond positively to treatment, thereby limiting clinical effectiveness and requiring the identification of novel therapeutic targets to optimise current strategies. The putative ligand of Siglec-15, Sialyl-Tn (STn), is associated with tumour progression and is synthesised by the sialyltransferases ST6GALNAC1 and ST6GALNAC2. However, the deregulation of both sialyltransferases within the literature remain limited, and the involvement of microRNAs (miRNAs) in STn production require further elucidation. Here, we identified miRNAs involved in the regulation of ST6GALNAC1 via a computational approach and further analysis of miRNA binding sites were determined. In silico tools predicted miR-21, miR-30e and miR-26b to regulate the ST6GALNAC1 gene, all of which had shown significant upregulated expression in the tumour cohort. Moreover, each miRNA displayed a high binding affinity towards the seed region of ST6GALNAC1. Additionally, enrichment analysis outlined pathways associated with several cancer hallmarks, including epithelial to mesenchymal transition (EMT) and MYC targets associated with tumour progression. Furthermore, our in silico findings demonstrated that the ST6GALNAC1 expression profile was significantly downregulated in CRC tumours, and its low expression correlated with poor survival outcomes when compared with patient survival data. In comparison to its counterpart, there were no significant differences in the expression of ST6GALNAC2 between normal and malignant tissues, which was further evidenced in our immunohistochemistry analysis. Immunohistochemistry staining highlighted significantly higher expression was more prevalent in normal human tissues with regard to ST6GALNAC1. In conclusion, the integrated in silico analysis highlighted that STn production is not reliant on deregulated sialyltransferase expression in CRC, and ST6GALNAC1 expression is regulated by several oncomirs. We proposed the involvement of other sialyltransferases in the production of the STn antigen and CRC progression via the Siglec-15/Sia axis.