Search Results (1,160)

Background: Avian pathogenic Escherichia coli (APEC) is a leading cause of colibacillosis in poultry. Piper betle L. is a medicinal plant rich in bioactive compounds including hydroxychavicol that possess potent antibacterial activity. This study aimed to investigate the efficacy of a P. betle L. leaf nanoemulsion (NEPE) and hydroxychavicol against multidrug-resistant APEC isolates. Methods: In vitro and in silico analysis of NEPE and hydroxychavicol against APEC were determined. Results: The nanoemulsion exhibited potent antibacterial activity, with MIC and MBC values of 0.06–0.25% v/v and 0.125–0.25% v/v, respectively. The MIC and MBC values of hydroxychavicol against isolates ranged from 0.25 to 1.0 mg/mL. A time–kill assays revealed rapid bactericidal effects of both compounds, achieving a ≥3-log reduction within 4 h at 4 × MIC. Scanning electron microscopy demonstrated that APEC cells treated with hydroxychavicol exhibited filamentous cells with incomplete septa. Molecular docking and dynamics simulations of hydroxychavicol against APEC cell division proteins were investigated. According to the binding energy, hydroxychavicol exhibited the highest affinity with ZapE, FtsW, FtsX, FtsZ, and FtsA, respectively. However, the FtsA protein showed the least protein conformational change throughout the 5000 ns simulation, reflecting a highly stable conformation. Conclusions: These confirm the potential stability of protein and ligand, as supported by molecular dynamics simulation. The results suggested the potential of NEPE and hydroxychavicol, which may have promising antibacterial potential that can be used to inhibit APEC growth. Full article

Organic acids, as natural metabolites, play crucial roles in human metabolism and health. Tumor Necrosis Factor (TNF), a pivotal mediator in immune regulation and inflammation, is a key therapeutic target. We evaluated ten organic acids as TNF modulators using in silico molecular docking, followed by detailed ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling and molecular dynamics (MD) simulations for three lead candidates: gallic, aconitic, and crocetin acids. Their effects on TNF gene expression were then assessed in vivo using a mouse leukocyte model. The in silico results indicated that crocetin had the highest TNF binding affinity (−5.6 to −4.6 kcal/mol), while gallic acid formed the most stable protein-ligand complex during MD simulations, and aconitic acid established hydrogen bond interactions. ADMET analysis suggested potential pharmacokinetic limitations, including low permeability. Contrasting its high predicted binding affinity, in vivo gene expression analysis revealed that crocetin stimulated TNF synthesis, whereas gallic and aconitic acids acted as inhibitors. This research explores organic acids as potential TNF modulators, highlighting their complex interactions and providing a foundation for developing these compounds as anti-inflammatory agents targeting TNF-mediated diseases. Full article

Icariin (ICA) is widely recognized for its health benefits. In this work, we examined the intermolecular interactions between ICA and proteinase K (PK) via multi-spectroscopic techniques and molecular simulations. The experimental findings revealed that ICA quenched the fluorescence emission of PK by forming a noncovalent complex. Both hydrogen bonding and van der Waals interactions are essential for the complex’s formation. Then Förster resonance energy transfer (FRET), competitive experiments, and synchronous fluorescence spectroscopy were adopted to verify the formation of the complex. Molecular docking studies demonstrated that ICA could spontaneously bind to PK by hydrogen bonding and hydrophobic interactions, which is consistent with the spectroscopic results. The PK-ICA complex’s dynamic stability was evaluated using a 50 ns molecular dynamics (MD) simulation. The simulation results revealed no significant structural deformation or positional changes throughout the entire simulation period. The complex appears to be rather stable, as seen by the average root-mean-square deviation (RMSD) fluctuations for the host protein in the PK-ICA complex of 1.08 Å and 3.09 Å. These outcomes of molecular simulations suggest that ICA interacts spontaneously and tightly with PK, consistent with the spectroscopic findings. The approach employed in this research presents a pragmatic and advantageous method for examining protein–ligand interactions, as evidenced by the concordance between empirical and theoretical findings. Full article

Metastatic breast cancer (BC) spread underscores the need for novel prognostic biomarkers. This study investigated CCR4-NOT Transcription Complex Subunit 7 (CNOT7) and leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1) in BC progression and natural killer (NK) cell resistance. In the current study, 90 female BC patients (46 non-metastatic, 44 metastatic) were analyzed. CNOT7 and LAIR-1 protein levels were measured in serum via ELISA and CNOT7 expression in tissue by immunohistochemistry (IHC). In silico tools explored related pathways. Computational analyses, including in silico bioinformatics and molecular docking, explored gene functions, interactions, and ligand binding to CNOT7 and LAIR-1. CNOT7 serum levels were significantly elevated in metastatic patients (mean 4.710) versus non-metastatic patients (mean 3.229, p < 0.0001). Conversely, LAIR-1 serum levels were significantly lower in metastatic (mean 56.779) versus non-metastatic patients (mean 67.544, p < 0.0001). High CNOT7 was found in 50% (45/90) of cases, correlating with higher tumor grade, hormone receptor negativity, and increased lymph node involvement. Elevated CNOT7 and lower LAIR-1 levels were associated with worse overall survival. Pathway analysis linked CNOT7 to the PI3K/AKT/mTOR pathway. Computational findings elucidated CNOT7′s cellular roles, gene/protein interaction networks for LAIR-1/CNOT7, and distinct ligand binding profiles. High CNOT7 levels are associated with advanced BC stages and poor clinical outcomes, which suggests its utility as a prognostic biomarker. The inverse relationship between CNOT7 and LAIR-1 provides mechanistic insights into BC progression and immune evasion, further supported by in silico investigations. Full article

A novel ruthenium(II) complex, [RuCl₂(η⁶-p-cymene)(bph-κN)] (1), was synthesized and structurally characterized using FTIR and NMR spectroscopy. Density functional theory (DFT) calculations supported the proposed geometry and allowed for comparative analysis of experimental and theoretical spectroscopic data. The interaction of complex 1 with human serum albumin (HSA) and calf thymus DNA was investigated through fluorescence quenching experiments, revealing spontaneous binding driven primarily by hydrophobic interactions. The thermodynamic parameters indicated mixed quenching mechanisms in both protein and DNA systems. Ethidium bromide displacement assays and molecular docking simulations confirmed DNA intercalation as the dominant binding mode, with a Gibbs free binding energy of −34.1 kJ mol⁻¹. Antioxidant activity, assessed by EPR spectroscopy, demonstrated effective scavenging of hydroxyl and ascorbyl radicals. In vitro cytotoxicity assays against A375, MDA-MB-231, MIA PaCa-2, and SW480 cancer cell lines revealed selective activity, with pancreatic and colorectal cells showing the highest sensitivity. QTAIM analysis provided insight into metal–ligand bonding characteristics and intramolecular stabilization. These findings highlight the potential of 1 as a promising candidate for further development as an anticancer agent, particularly against multidrug-resistant tumors. Full article

Holothuria scabra has long been acknowledged in traditional medicine for its therapeutic properties. The transforming growth factor-beta (TGF-β) superfamily is crucial in regulating cellular processes, including differentiation, proliferation, and immune responses. This study marks the first exploration of the gene expression localization, sequence conservation, and functional roles of H. scabra TGF-β proteins, specifically activin (HolscActivin), inhibin (HolscInhibin), and the TGF-β receptor (HolscTGFBR), across various organs. In situ hybridization indicated that HolscActivin and HolscInhibin are expressed in the intestine, respiratory tree, ovary, testis, and inner body wall. This suggests their roles in nutrient absorption, gas exchange, reproduction, and extracellular matrix remodeling. Notably, HolscTGFBR demonstrated a similar tissue-specific expression pattern, except for its absence in the respiratory tree. Bioinformatics analysis reveals that HolscTGFBR shares significant sequence similarity with HomsaTGFBR, especially in regions essential for signal transduction and inhibition. Molecular docking results indicate that HolscActivin may promote receptor activation, while HolscInhibin functions as a natural antagonist, reflecting the signaling mechanisms of human TGF-β proteins. Interestingly, cross-species ternary complex docking with human TGF-β receptors further supports these findings, showing that HolscActivin moderately engages the receptors, whereas HolscInhibin exhibits strong binding, suggestive of competitive inhibition. These results indicate that H. scabra TGF-β proteins retain the structural and functional features of vertebrate TGF-β ligands, supporting their potential applications as natural modulators in therapeutic and functional food development. Full article

Cancer remains one of the most formidable challenges to human health; hence, developing effective treatments is critical for saving lives. An important strategy involves reactivating tumor suppressor genes, particularly p53, by targeting their negative regulator MDM2, which is essential in promoting cell cycle arrest and apoptosis. Leveraging a drug repurposing approach, we screened over 24,000 clinically tested molecules to identify new MDM2 inhibitors. A key innovation of this work is the development and application of a selective cleaning algorithm that systematically filters assay data to mitigate noise and inconsistencies inherent in large-scale bioactivity datasets. This approach significantly improved the predictive accuracy of our machine learning model for pIC₅₀ values, reducing RMSE by 21.6% and achieving state-of-the-art performance (R² = 0.87)—a substantial improvement over standard data preprocessing pipelines. The optimized model was integrated with structure-based virtual screening via molecular docking to prioritize repurposing candidate compounds. We identified two clinical CB1 antagonists, MePPEP and otenabant, and the statin drug atorvastatin as promising repurposing candidates based on their high predicted potency and binding affinity toward MDM2. Interactions with the related proteins MDM4 and BCL2 suggest these compounds may enhance p53 restoration through multi-target mechanisms. Quantum mechanical (ONIOM) optimizations and molecular dynamics simulations confirmed the stability and favorable interaction profiles of the selected protein–ligand complexes, resembling that of navtemadlin, a known MDM2 inhibitor. This multiscale, accuracy-boosted workflow introduces a novel data-curation strategy that substantially enhances AI model performance and enables efficient drug repurposing against challenging cancer targets. Full article

Coumarins are known for interacting with proteins and exhibiting diverse biological activities. This study investigates the interaction between coumarin-343 (C343) and human (HSA) and bovine (BSA) serum albumins. Fluorescence spectroscopy and theoretical simulations, including density functional theory (DFT) and molecular docking, were used to analyze the ligand–protein complex formation. The fluorescence quenching data revealed that C343 binds to both proteins, with binding constants of 2.1 × 10⁵ mol·L⁻¹ (HSA) and 6.5 × 10⁵ mol·L⁻¹ (BSA), following a 1:1 stoichiometry. Binding site markers identified drug site I (DS1), located in subdomain IIA, as the preferential binding region for both proteins. Computational results supported these findings, showing high affinity for DS1, with binding energies of −69.02 kcal·mol⁻¹ (HSA) and −67.22 kcal·mol⁻¹ (BSA). While complex formation was confirmed for both proteins, differences emerged in the induced circular dichroism (ICD) signals. HSA displayed a distinct ICD profile compared to BSA in both intensity and absorption maximum. Molecular Docking revealed that the C343 conformation differed between HSA and BSA, explaining the variation in ICD signals. These results highlight the importance of protein structure in modulating ligand interactions and spectral responses. Full article

(1) Background: The highly pathogenic avian influenza virus H5N1 clade 2.3.4.4b is an emerging threat that poses a great risk to the poultry industry. A few human cases have been linked to the infection with this clade in many parts of the world, including the USA. Unfortunately, there are no specific vaccines or antiviral drugs that could help prevent and treat the infection caused by this virus in birds. Our major objective is to identify/repurpose some (novel/known) antiviral compounds that may inhibit viral replication by targeting some key viral proteins. (2) Methods: We used state-of-the-art machine learning tools such as molecular docking and MD-simulation methods from Biovia Discovery Studio (v24.1.0.321712). The key target proteins such as hemagglutinin (HA), neuraminidase (NA), Matrix-2 protein (M2), and the cap-binding domain of PB2 (PB2/CBD) homology models were validated through structural assessment via DOPE scores, Ramachandran plots, and Verify-3D metrics, ensuring reliable structural representations, confirming their reliability for subsequent in silico approaches. These approaches include molecular docking followed by molecular dynamics simulation for 50 nanoseconds (ns), highlighting the structural stability and compactness of the docked complexes. (3) Results: Molecular docking revealed strong binding affinities for both sofosbuvir and GS441524, particularly with the NA and PB2/CBD protein targets. Among them, GS441524 exhibited superior interaction scores and a greater number of hydrogen bonds with key functional residues of NA and PB2/CBD. The MM-GBSA binding free energy calculations further supported these findings, as GS441524 displayed more favorable binding energies compared to several known standard inhibitors, including F0045S for HA, Zanamivir for NA, Rimantadine and Amantadine for M2, and PB2-39 for PB2/CBD. Additionally, 50 ns molecular dynamics simulations highlighted the structural stability and compactness of the GS441524-PB2/CBD complex, further supporting its potential as a promising antiviral candidate. Furthermore, hydrogen bond monitor analysis over the 50 ns simulation confirmed persistent and specific interactions between the ligand and proteins, suggesting that GS441524 may effectively inhibit the NA, and PB2/CBD might potentially disrupt PB2-mediated RNA synthesis. (4) Conclusions: Our findings are consistent with previous evidence supporting the antiviral activity of certain nucleoside analog inhibitors, including GS441524, against various coronaviruses. These results further support the potential repurposing of GS441524 as a promising therapeutic candidate against H5N1 avian influenza clade 2.3.4.4b. However, further functional studies are required to validate these in silico predictions and support the inhibitory action of GS441524 against the targeted proteins of H5N1, specifically clade 2.3.4.4b. Full article

Human Interleukin-6 (hIL-6) is a pro inflammatory cytokine that binds to its receptor, IL-6Rα followed by binding to gp130 and subsequent dimerization to form a hexamer signaling complex. As a critical inflammation mediator, hIL-6 is associated with a diverse range of diseases and monoclonal antibodies in clinical use that either target IL-6Rα or hIL-6 to inhibit signaling. Here, we perform high-throughput structure-based computational screening using ensemble docking for small-molecule antagonists for which the target conformations were taken from 600 ns long molecular dynamics simulations of the apo protein. Prior knowledge of the contact sites from binary complex studies and experimental work was incorporated into the docking studies. The top 20 scoring ligands from the in silico studies after post analysis were subjected to in vitro functional assays. Among these compounds, the ligand with the second-highest calculated binding affinity experimentally showed an ~84% inhibitory effect on IL6-induced STAT3 reporter activity at 10 μM concentration. This finding may pave the way for designing small-molecule inhibitors of hIL-6 of therapeutic significance. Full article

G-protein-coupled receptors (GPCRs) are vital transmembrane proteins that regulate a wide range of physiological processes by transmitting extracellular signals into intracellular responses. Among them, the β2-adrenergic receptor (β2-AR) plays a central role in bronchodilation, smooth muscle relaxation, and cardiovascular modulation, making it a key therapeutic target for diseases such as asthma, chronic obstructive pulmonary disease (COPD), and hypertension. This study explores the potential of natural bioactive compounds like ephedrine, quercetin, catechin, and resveratrol as alternative ligands for β2-AR through molecular docking analysis. Using AutoDock 4.6, these compounds were docked with the binding site of the β2-AR (PDB ID: 2RH1), and their binding affinities and interaction map were evaluated. Results showed that all compounds exhibited favorable binding energies and stable interactions with key receptor residues, with quercetin demonstrating the highest affinity. The findings suggest that these natural compounds may serve as promising leads for the development of safer, plant-derived modulators of β2-AR, supporting the role of computational approaches in natural product-based drug discovery. However, as docking cannot determine functional activity, these findings should be interpreted as preliminary and require experimental validation. Full article

Antioxidants derived from plant extracts have attracted considerable attention due to their potential in mitigating oxidative damage through free radical scavenging mechanisms. Although 700 species have been used for centuries in Georgian traditional medicine, the chemical composition and antioxidant and antibacterial properties of Caucasian endemic medicinal plants remain largely unknown. In this study, the antioxidant and antibacterial activities of leaf and root extracts of Caucasian endemic medicinal plants Sempervivum transcaucasicum Muirhead and Paeonia daurica subsp. mlokosewitschii (Lomakin) D. Y. Hong were investigated. The highest antioxidant activity and phenolic and flavonoid content were revealed in Paeonia daurica leaf extract. The analysis of the content of water-soluble antioxidants revealed the highest content of reduced glutathione and ascorbate in Paeonia daurica leaves. Moreover, the antibacterial activity of leaf and root extracts against Escherichia coli ATCC 25922 strain was investigated, and minimal inhibitory concentration (MIC) values were determined. While the antibacterial activity against E. coli ATCC 25922 was not revealed for the Sempervivum transcaucasicum leaf extract, antibacterial properties were detected for the root extract (MIC 5 mg/mL). Collectively, the highest antibacterial activity was revealed for Paeonia daurica leaf and root extracts (MIC 2 mg/mL and 3 mg/mL, respectively). From a molecular perspective, molecular docking simulations were performed using HDOCK software, with reduced glutathione and ascorbic acid as ligands, in order to analyse their potential binding affinity to the OmpX protein. Inhibiting this protein would likely disrupt bacterial function and produce an antibacterial effect. Our results provide a possible mechanism for the antibacterial activity of Paeonia daurica subsp. mlokosewitschii. Overall, the results of the study demonstrate the potential of Caucasian endemic medicinal plants as natural antioxidants and antimicrobial agents. Full article

Background/Objectives: Severe malaria, mainly caused by Plasmodium falciparum, remains a significant therapeutic challenge due to increasing drug resistance and adverse effects. Flavonoids, known for their wide range of bioactivities, offer a promising route for antimalarial drug discovery. The aim of this study was to elucidate key structural features associated with antimalarial activity in flavonoids and to develop accurate, interpretable predictive models. Methods: Curated databases of flavonoid structures and their activity against P. falciparum strains and enzymes were constructed. Molecular fingerprinting and decision tree analyses were used to identify key pharmacophoric groups. Subsequently, molecular descriptors were generated and reduced to build multiple classification and regression models. Results: These models demonstrated high predictive accuracy, with test set accuracies ranging from 92.85% to 100%, and R² values from 0.64 to 0.97. Virtual screening identified novel flavonoid candidates with potential inhibitory activity. These were further evaluated using molecular docking and molecular dynamics simulations to assess binding affinity and stability with Plasmodium proteins (FabG, FabZ, and FabI). The predicted active ligands exhibited stable pharmacophore interactions with key protein residues, providing insights into binding mechanisms. Conclusions: This study provides highly predictive models for antimalarial flavonoids and enhances the understanding of structure–activity relationships, offering a strong foundation for further experimental validation. Full article

This study focuses on exploring potential inhibitors of the Marburg virus interferon inhibitory domain protein (MARV-VP35), which is responsible for immune evasion and immunosuppression during viral manifestation. A combination of in silico techniques was applied, including structure-based pharmacophore virtual screening, molecular docking, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis, molecular dynamics (MD), and molecular stability assessment of the identified hits. The docking scores of the 14 selected ligands ranged between −6.88 kcal/mol and −5.28 kcal/mol, the latter being comparable to the control ligand. ADMET and drug likeness evaluation identified Mol_01 and Mol_09 as the most promising candidates, both demonstrating good predicted antiviral activity against viral targets. Density functional theory (DFT) calculations, along with relevant quantum chemical descriptors, correlated well with the docking score hierarchy, and molecular electrostatic potential (MEP) mapping confirmed favorable electronic distributions supporting the docking orientation. Molecular dynamics simulations further validated complex stability, with consistent root mean square deviation (RMSD), root mean square fluctuation (RMSF), and secondary structure element (SSE) profiles. These findings support Mol_01 and Mol_09 as viable candidates for experimental validation. Full article

Scoring functions are key elements in docking protocols as they approximate the binding affinity of a ligand (usually a small bioactive molecule) by calculating its interaction energy with a biomacromolecule (usually a protein). In this study, we present a pairwise comparison of scoring functions applying a multi-criterion decision-making approach based on InterCriteria analysis (ICrA). As criteria, the five scoring functions implemented in MOE (Molecular Operating Environment) software were selected, and their performance on a set of protein–ligand complexes from the PDBbind database was compared. The following docking outputs were used: the best docking score, the lowest root mean square deviation (RMSD) between the predicted poses and the co-crystallized ligand, the RMSD between the best docking score pose and the co-crystallized ligand, and the docking score of the pose with the lowest RMSD to the co-crystallized ligand. The impact of ICrA thresholds on the relations between the scoring functions was investigated. A correlation analysis was also performed and juxtaposed with the ICrA. Our results reveal the lowest RMSD as the best-performing docking output and two scoring functions (Alpha HB and London dG) as having the highest comparability. The proposed approach can be applied to any other scoring functions and protein–ligand complexes of interest. Full article