Search Results (1,644)

The genus Tamarix L. includes several species widely used in traditional medicine for their therapeutic properties. This study aims to evaluate the bioactive potential of Tamarix gallica extracts from Western Algeria using an integrated in vitro and in silico approach. GC–MS analysis with BSTFA derivatization was performed to characterize the chemical profile of the methanolic fraction. In addition, total phenolic, flavonoid, and tannin contents were determined in methanolic extracts of leaves and stems. The biological activities were assessed using antioxidant (DPPH, ABTS, β-carotene, FRAP, O-phenanthroline, and cupric reducing assays), antimicrobial, antidiabetic, and anti-Alzheimer in vitro assays. Molecular docking was conducted to evaluate the inhibitory potential of selected flavonoids against α-amylase, acetylcholinesterase, and butyrylcholinesterase. Results revealed a rich metabolite profile dominated by long-chain aliphatic alcohols (including hentriacontan-12-ol), phytosterols (β-sitosterol), fatty acids, phenolic derivatives, and sugar alcohols. The extracts exhibited strong antioxidant activity (IC₅₀ = 1.34 ± 0.43 and 12.32 ± 0.36 μg·mL⁻¹), significant antimicrobial effects against the tested pathogens, and notable antidiabetic and anticholinesterase activities (IC₅₀ = 78.65 ± 1.43 and 98.37 ± 1.07 μg·mL⁻¹). Molecular docking analysis supported these findings, showing strong binding affinities of quercetin and rhamnetin toward the target enzymes. Overall, T. gallica exhibits promising multifunctional bioactivities with potential pharmaceutical relevance. Full article

Skin aging is associated with oxidative stress, extracellular matrix degradation, and dysregulation of melanogenesis, leading to wrinkles, loss of elasticity, and hyperpigmentation. Natural plant-derived compounds have attracted increasing interest as multifunctional cosmetic ingredients due to their antioxidant and anti-aging properties. Mai-Kae-Den-Klong (MKDK), a traditional Thai longevity herbal formula composed of Albizia procera (Roxb.) Benth., Cyperus rotundus L., Diospyros rhodocalyx Kurz, Piper nigrum L., Streblus asper Lour., and Tinospora crispa (L.) Hook.f. & Thomson, has historically been used to promote vitality and healthy aging; however, its potential application as a cosmetic anti-aging ingredient remains scientifically unexplored. Therefore, this study investigated the anti-aging potential of MKDK extract using integrated enzyme-based bioassays and in silico approaches. Phytochemical profiling of the ethanolic extract was performed using LC-MS analysis, revealing diverse bioactive constituents, including flavonoids, phenolic glycosides, alkaloids, and terpenoids, with (−)-epicatechin, procyanidin B1, and piperine identified as major metabolites. Antioxidant activity was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging assays, while inhibitory activities against tyrosinase, collagenase, elastase, and hyaluronidase were assessed to determine skin anti-aging potential. The extract exhibited strong antioxidant activity, with IC₅₀ values of 17.23 ± 2.11 µg/mL for DPPH and 11.87 ± 1.77 µg/mL for ABTS assays. In addition, the extract demonstrated inhibitory effects against tyrosinase (IC₅₀ = 41.25 ± 1.56 µg/mL), elastase (IC₅₀ = 49.51 ± 3.69 µg/mL), collagenase (IC₅₀ = 61.54 ± 2.88 µg/mL), and hyaluronidase (IC₅₀ = 63.74 ± 6.32 µg/mL), suggesting multifunctional anti-aging properties associated with skin brightening and extracellular matrix preservation. Network pharmacology analysis predicted multiple aging-related signaling pathways, particularly the FoxO signaling pathway, which is associated with oxidative stress regulation and longevity. Molecular docking analysis further demonstrated favorable binding affinities of procyanidin B1, epicatechin, and piperine toward skin-aging-related enzymes, supporting their potential contribution to the observed bioactivities. Overall, these findings suggest that MKDK possesses promising cosmeceutical potential as a natural multifunctional anti-aging ingredient and provides scientific support for the application of traditional Thai herbal formulations in cosmetic and skin health products. Full article

This study presents a novel approach for the development of biofunctional and skin-comfortable cotton textiles through the integration of blackcurrant water/ethanol pomace extract into polysaccharide-based fabric coating. Extraction of bioactive compounds from blackcurrant pomace was optimized using response surface methodology, yielding a total phenolic content of 36.04 mg GAE/g DW, along with significant contents of flavonoids (5.28 mg QE/g DW) and anthocyanins (5.18 mg/g DW). The cotton fabric was biofunctionalized using the layer-by-layer (LbL) deposition technique, incorporating blackcurrant pomace extract within four, eight, or twelve chitosan/pectin bilayers. The biofunctionalized fabrics exhibited no cytotoxic effect and demonstrated nearly 100% antioxidant and antibacterial activity against E. coli and S. aureus. Additionally, the LbL coating enabled tunable extract adsorption (0.09–2.70%) and stabilization of bioactive compounds on the cotton surface, resulting in adjustable fabric coloration and moisture management properties (assessed using the Moisture Management Tester). Molecular docking analysis provided insight into the interactions between HPLC-detected anthocyanins (cyanidin-3-O-glucoside, cyanidin-3-O-rutinoside, delphinidin-3-O-glucoside, and delphinidin-3-O-rutinoside) and polysaccharides, revealing an increase in binding affinity from cellulose to chitosan and pectin. The transition from comfort-oriented fabric to a material featuring integrated moisture management and enhanced biofunctionality, achieved by coating cotton with eight chitosan/pectin bilayers incorporating blackcurrant pomace extract, renders the textile suited for medical, protective, and high-comfort applications. Full article

This study evaluated the structural, electronic, pharmacokinetic, and receptor-binding properties of three bisphosphonate derivatives, alendronate, risedronate, and zoledronate, to investigate their therapeutic relevance in osteoporosis and breast cancer. Density Functional Theory (DFT) calculations at the B3LYP/6-31G(d,p) level showed that risedronate exhibited the highest kinetic stability (ΔE = 6.7468 eV), whereas zoledronate displayed greater chemical reactivity (ΔE = 2.9669 eV) and the strongest nonlinear optical response (β = 1.20 × 10⁻³⁰ esu). ADMET analysis indicated acceptable safety profiles for all compounds, although high polarity and low lipophilicity may limit oral bioavailability. Molecular docking against 11 breast cancer- and bone metabolism-related targets revealed favorable binding affinities, particularly for zoledronate and risedronate. Zoledronate showed strong interactions with ESR2, VEGFR/KDR, GGPS1, and FPPS, whereas risedronate exhibited notable affinity for BRCA2 and MMP9. Bioinformatics analyses identified significant dysregulation of GGPS1, FDPS, TNFSF11, ESR1, MMP9, and BRCA2 in breast cancer tissues, while survival analysis linked elevated FDPS, MMP9, and BRCA2 expression to poor prognosis. Network analyses highlighted pathways related to mevalonate metabolism, hormone signaling, angiogenesis, extracellular matrix remodeling, and the RANK/RANKL/OPG axis. These findings support the potential repurposing of bisphosphonates, particularly zoledronate, for breast cancer-associated bone disease. Full article

Ninhydrins represent a promising chemical space for the search for new biologically active molecules with antimicrobial, antiprotease, and antitumor properties. In the present work, new ninhydrin derivatives were synthesized, and for the first time, a systematic in silico study of ninhydrins as multitarget ligands for five pharmacologically significant targets (HER1/HER4, HER2/HER3, Trk-B, PPAR-α, and LTβR) was conducted, whose amplification or overexpression plays a key role in the pathogenesis and progression of certain aggressive cancer types. Among the studied ninhydrin derivatives, compound 1 (2,2-dihydroxy-5,6-dimethoxy-1H-indene-1,3(2H)-dione) stands out as the most potentially active molecule. It exhibits high affinity for HER1/HER4, Trk-B, and PPAR-α, opening up potential applications in oncology (HER family and Trk-B inhibition during BDNF overexpression), neurodegenerative diseases (Trk-B modulation), and metabolic disorders (PPAR-α activation). Compound 4 (2,2-Dihydroxy-5-trifluoromethylindane-1,3-dione) is a leader in LTβR binding and also holds promise for immuno-oncology and anti-inflammatory strategies. Full article

Background/Objectives: Betanin (Bet), a natural compound, exhibits potent antioxidant and metabolic regulatory properties, yet its effect on cellular glucose utilization remains unclear. This study investigated, for the first time, the impact of Bet on glucose consumption and the activation of key carbohydrate–catabolic pathways in human erythrocytes. Methods: In vitro assays were performed to evaluate enzyme inhibition and activation. Human erythrocytes were incubated with Bet to assess glucose consumption. Enzyme activities were measured spectrophotometrically, and molecular docking was used to analyze binding interactions. Results: Our results demonstrate that Bet inhibits digestive enzymes in a dose-dependent manner, with maximal inhibition at 90 µg/mL for pancreatic lipase and 70 µg/mL for α-amylase, showing IC₅₀ values of 48.8 and 31.9 µg/mL, respectively, supported by strong binding affinities of −9.3 and −8.9 Kcal/mol. These interactions are stronger than those of orlistat (−6.9 Kcal/mol) and acarbose (−7.7 Kcal/mol). Bet also induced the activity of AMPK with an IC₅₀ of 1.83 µg/mL and a BE of −7.90 Kcal/mol, compared to the specific AMPK activator A-769662, which had an IC₅₀ of 1.29 µg/mL and a binding energy of −10.0 Kcal/mol. Consequently, Bet stimulated key glycolytic enzymes, reaching maximal activation (~62%) at 1.4 µg/mL for hexokinase (HK) and glucose-6-phosphate dehydrogenase (G6PD), and at 1.6 µg/mL for pyruvate kinase (PK), supported by binding energies of −7.2, −7.5, and −9.0 Kcal/mol and AC₅₀ values of 0.87, 0.98, and 0.91 µg/mL, respectively. Moreover, Bet enhanced key Krebs cycle enzymes (IDH, SDH, MDH, LDH) in a dose-dependent manner, with AC₅₀ values of 0.76, 0.80, 0.72, and 0.52 µg/mL and strong binding energies (−7.8, −7.8, and −8.4 Kcal/mol), reaching maximal activation near 1.4 µg/mL. Bet also increased glucose consumption by human erythrocytes. Conclusions: Bet enhances glucose utilization by inhibiting digestive enzymes and activating intracellular metabolic pathways, suggest potential metabolic regulatory effects. Full article

Syzygium polycephalum (Miq.) Merr. & L.M. Perry is an underexplored species within the Syzygium genus, traditionally consumed for its edible fruit. However, the potential of its non-edible biomass as a source of bioactive metabolites remains poorly investigated. This study evaluated the antioxidant and α-glucosidase inhibitory activities of different parts of S. polycephalum and identified the metabolites associated with these activities using an LC-HRMS-guided approach. The ethanolic leaf extract demonstrated superior phenolic (457.89 ± 12.10 mg GAE/g) and flavonoid (11.08 ± 1.10 mg QE/g) contents with strong antioxidant (DPPH: 683.21 ± 24.54; FRAP: 1338.37 ± 7.04; CUPRAC: 771.91 ± 8.78 mg AEAC/g) and alpha-glucosidase inhibitory activities (52,145.16 ± 801.54 mg AEAGIC/g). LC–HRMS/MS identified four compounds, including chrysin and formononetin. Integrated in silico analyses revealed that chrysin consistently outperformed other metabolites, exhibiting optimal docking scores, favorable absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, and superior dynamic stability and binding affinity in molecular dynamics simulations. Collectively, these results position chrysin as the dominant bioactive driver and establish S. polycephalum leaf as a promising and sustainable source of dual-acting antioxidant and antidiabetic agents. Full article

Herpes simplex virus type 1 (HSV-1) remains a significant pathogen, particularly in immunocompromised patients. The emergence of drug-resistant strains necessitates alternative therapeutic agents. Lentinula edodes (LE), Hypsizygus marmoreus, and Pleurotus eryngii are edible mushrooms with recognized medicinal properties. However, their effects on drug-resistant HSV-1 remain unclear. This study characterized metabolites from high-temperature/high-pressure (121 °C) water extracts of fresh and dried fruiting bodies and evaluated anti-HSV-1 activities using in vitro and in silico approaches. Metabolic profiles were analyzed by electrospray ionization–quadrupole time-of-flight mass spectrometry. Antiviral activity against HSV-1 KOS (wild-type) and HSV-1 dxpiii (drug-resistant) strains was assessed by plaque assays and qPCR. Molecular docking and network pharmacology were performed on candidate compounds. LE extract from dried mushroom tended to show the highest levels of selected major bioactive constituents, along with greater antioxidant activities. All extracts significantly inhibited viral infection and gene expression in both strains. LE extract from dried mushroom modulated the expression of NFKB1 and IL6. Molecular docking analysis revealed that eritanidine showed a predicted binding affinity to HSV-1 DNA polymerase (−7.95 kcal/mol). Additionally, eritanidine, 5′-methylthioadenosine, and 3-indoleacrylic acid were predicted to interact with TNF and MAPK1. Several compounds also demonstrated favorable drug-likeness properties. Overall, these mushroom extracts are promising natural sources of antiviral agents against HSV-1, including drug-resistant variants. Full article

Shuanghuanglian oral liquid (SHL) is widely used in companion animals and poultry, but its molecular mechanism in pneumonia–myocarditis comorbidity and heart–lung inflammatory crosstalk remains largely unclear. This computational study investigated the conserved AKT1/HIF1A-mediated immunoregulatory mechanism of SHL and its cross-species translational potential in veterinary medicine. Network pharmacology was integrated with GO, KEGG, and Reactome enrichment analyses, protein–protein interaction network construction, ADMET evaluation, cross-species sequence homology analysis (human, dog, cattle, and pig), molecular docking, and molecular dynamics simulation. A total of 61 active compounds, 251 putative targets, and 52 common targets associated with pneumonia and myocarditis were identified. These targets were mainly enriched in inflammation- and immune-related pathways, including TNF, IL-17, AGE–RAGE, and PPAR signaling. AKT1 and HIF1A showed high sequence conservation across species (85–98%). Key compounds exhibited favorable binding affinity to AKT1, and molecular dynamics simulation suggested the stability of the Baicalein–AKT1 complex. ADMET analysis suggested favorable pharmacokinetic properties and low predicted toxicity. These findings suggest that SHL may potentially alleviate pneumonia and myocarditis through modulation of the conserved AKT1/HIF1A axis and support its potential as a complementary therapeutic approach for managing heart–lung inflammatory diseases in multiple livestock species. This entirely computational study highlights promising mechanisms that should be further validated in vivo. Full article

Marburg virus (MARV), a highly pathogenic member of the Filoviridae family, causes severe hemorrhagic fever with a high case fatality rate and currently lacks effective therapeutics. The viral entry process, mediated by the interaction between the MARV glycoprotein (GP) and host receptor C-type lectin domain family 4 member M (CLEC4M) (L-SIGN), represents a critical target for early-stage intervention. The active compounds from BindingDB and the decoy from DUDE were used. The RDKit was used for feature engineering. Machine learning models were trained on an initial dataset consisting of 56 active chemicals and 1232 decoys. Among the tested algorithms, the Random Forest model demonstrated superior performance, achieving the highest discriminative ability (AUC = 0.93, MCC = 0.88) on the test set. Virtual screening of 11,032 phytochemicals resulted in 120 predicted actives, of which 42 compounds satisfied drug-likeness criteria. Subsequent molecular docking identified three lead compounds (PubChem IDs: 42608095, 5281601, and 11243993) with moderate-to-promising binding affinities (−6.3 to −6.5 kcal/mol) toward the CLEC4M binding site. ADMET analysis revealed favorable pharmacokinetic and toxicity profiles for the selected lead compounds. DFT calculations of the three compounds highlighted their electronic stability and reactive nature, indicating that PubChem IDs 42608095 and 5281601 possess particularly stable electronic properties conducive to favorable target interactions. Combining machine learning models with molecular docking and Molecular Dynamics (MD) simulations worked well in finding promising phytochemical inhibitors. The MM/GBSA binding free energy calculations further confirmed binding affinities, with values of −10.83 and −11.08 kcal/mol, respectively, suggesting favorable complex stability. These findings provide a pathway for developing new antiviral agents against MARV, pending further experimental validation and optimization. Full article

Alzheimer’s disease (AD) and type 2 diabetes mellitus (T2DM) are major global health burdens that share interconnected pathological mechanisms involving impaired insulin signaling, metabolic stress, and chronic neuroinflammation. This study applied an integrative systems biology and atomistic simulation framework to investigate bioactive compounds from Caesalpinia sappan L. targeting shared molecular regulators linking AD and T2DM. Network topology analysis identified four central hub genes, STAT3, SRC, HSP90AA1, and TP53, representing key regulatory nodes involved in inflammatory signaling, kinase regulation, proteostasis, and cellular stress responses. Compound-specific interaction analysis revealed distinct target preferences among phytochemical subclasses. Protosappanin B showed strong binding toward both STAT3 and HSP90α, whereas flavonols including quercetin and rhamnetin exhibited high affinity for SRC, and the chalcone derivative sappanchalcone preferentially interacted with TP53. Atomistic molecular dynamics simulations and MM-PBSA calculations supported stable protein ligand interactions and favorable binding energetics, while density functional theory analysis indicated electronic properties consistent with sustained intermolecular interactions. Collectively, these findings suggest that structurally distinct subclasses of C. sappan phytochemicals converge on complementary regulatory hubs within the shared AD and T2DM molecular network, supporting coordinated multi-target modulation of interconnected inflammatory, kinase signaling, proteostasis, and cellular stress pathways underlying AD–T2DM comorbidity. Full article

The purpose of this study was to use data mining and network pharmacology to determine drug patterns for bovine viral diarrhea (BVD). The frequency, properties, tastes, meridian tropism, and functions of prescription data were gathered and examined from four literature databases (2004–2024). Cluster analysis was used to find prescription patterns, and the Apriori algorithm (SPSS Modeler 18) was used to find associations. A total of 391 literature-derived prescription records were included in the analysis, involving 189 distinct herbal medicines and a cumulative herb-use frequency of 2031 occurrences. These herbs primarily enter the liver meridian and were categorized as cold, warm, or neutral. The predominant tastes were bitter, pungent, and sweet. Five frequently recorded herbs and 14 co-occurrence patterns among herbs were extracted. According to traditional Chinese medicine (TCM), spleen–stomach deficiencies and damp-heat pathogens are linked to BVD. These medication patterns were mainly associated with heat-clearing, detoxification, spleen-strengthening, and Qi-regulating strategies in TCVM theory. Targets were screened, PPI networks were constructed, and enrichment studies for core herbs (Baitouweng, Huangbo, Huangqin, Qinpi, and Zhizi) were performed using network pharmacology. The binding affinities between disease targets and active components were further assessed using molecular docking. The findings provide a descriptive summary of medication patterns and generate preliminary hypotheses regarding potential compound–target–pathway associations involved in the symptomatic and supportive use of TCM for BVD. Full article

Binding affinity prediction is about estimating the degree to which a drug binds to a protein. Predicting the binding affinity between a drug and a protein in a computational process helps researchers filter huge libraries of compounds before performing expensive biochemical lab experiments. Currently, there is interest in predicting binding affinity through computational pattern recognition or machine learning methods instead of the classical physics-inspired methods, which are computationally intractable except for tiny chemical compounds. In the last five years, several machine learning-based methods have been presented, whose experimental validations have achieved increasing Pearson coefficients while trained and tested in the PDBBind 2016 and CASF 2016 databases, respectively. These methods have an important diversity of architectures that provide different properties. The aim of this paper is to discern which binary properties (existence or absence) of these methods make them return higher Pearson coefficients. Basically, the properties introduced are related to the level of structural knowledge, the presence of 3D information, and the introduction of the relationship between the drug and the protein in the input of the model. The t-test confirms that the important binary properties for having a high Pearson coefficient are the protein (or part of the protein) being represented and introduced into the computational model as a graph, the pocket and the drug–protein interaction being part of the input, and incorporating the distance between atoms and the type of chemical bonds into the model. Full article

Background/Objectives: Poly (ADP-ribose) polymerase (PARP1) has emerged as a promising therapeutic target in human breast cancer particularly in BRCA1/2 mutation carriers where a synthetic lethal interaction leads to massive tumor cell death upon specific inhibitors’ administration. Current clinically approved PARP inhibitors (Talazoparib and Olaparib) show outstanding therapeutic capabilities but suffer from severe side effects. Most importantly, some of them can cause life-threatening cardiotoxicity through hERG off-target effects. Here, we performed an extensive study to identify lead compounds with improved binding modes and favorable predicted pharmacokinetics using an integrated computational strategy. Methods: An artificial intelligence-driven drug design (AIDDISON™ v2023) workflow was employed to search ultra-large chemical space libraries for active compounds, which were then optimized via computer-aided methods to form a PARP-Tailored Database (PTD). This database was then analyzed through a virtual screening workflow, molecular docking studies, molecular dynamics (MD) simulations, MM/GBSA binding free energy calculations, DFT analysis and ADME/Tox predictions using the Schrödinger suite (v2023-2), MobaXterm v25.2, Gaussian 16.0, ProTox-3 and Pred-hERG v5.0 respectively. Results: Three compounds (1a–1c) were identified as promising candidates. Among them 1a appeared to be the most active compound with a favorable docking score (−9.488 kcal/mol) that is not only higher than 1b and 1c but also higher than that of Talazoparib (−6.778 kcal/mol). MD simulations of 1a–1c in the active site revealed an average RMSD of ~2.5–3.6 Å which is better compared to the parent Talazoparib (5.6 Å). Interestingly, on the 250 ns extended MD study, 1a exhibited a slightly reduced RMSD between 2.4 and 3.2 Å, whereas Talazoparib retained higher fluctuations of ~5 Å to 6 Å. MM/GBSA binding energy analysis indicated 1a to have better predicted binding affinity (−67.820 kcal/mol), which is also better than Talazoparib (−63.734 kcal/mol). DFT calculations showed good electronic properties and in silico ADMET studies also indicated 1a to have good drug-likeness and lower predicted hepatotoxicity and cardiotoxicity risk. Conclusions: These findings identify compound 1a as a promising lead, while compounds 1b and 1c remain viable candidates for further optimization. However, experimental validation is critical to confirm the predicted biological activity and safety profiles. Full article

Harmful algal blooms pose a persistent threat to the integrity of freshwater ecosystems and public health. However, there are no selective chemical control agents available to suppress cyanobacterial growth without damaging beneficial phytoplankton. In this study, ten structurally diverse monoterpenes were assessed in vitro for their differential activity against the potent toxin-producing cyanobacterium Microcystis aeruginosa and the ecologically valuable microalga Chlorella sorokiniana using disc diffusion (DDM) and minimum inhibitory concentration (MIC) assays. Inhibition zones against M. aeruginosa ranged from 6.9 to 43.6 mm, with thymol recording the largest zone (43.6 mm). MIC values ranged from 0.25 to >1 mg/mL for both organisms, and selectivity indices identified camphor and carvone as the most cyanobacterium-preferential compounds, while carene and α-pinene showed the inverse selectivity pattern. Molecular docking against six AlphaFold2-predicted target proteins, photosynthetic complexes, Adenosine Triphosphate (ATP) synthase subunits, and superoxide dismutase (SOD) from both organisms, revealed binding affinities between −3.9 and −6.2 kcal/mol. Phenolic monoterpenes consistently engaged active-site glutamate and aspartate residues via hydrogen bonds and Pi–Anion interactions, most strikingly in the M. aeruginosa ATP synthase, whereas the M. aeruginosa SOD represented the least amenable target for all compounds. Computational ADMET profiling confirmed favorable pharmacokinetic properties and low predicted toxicity for the full panel. Full article