Search Results (115)

Leymus chinensis (Trin.) Tzvel., a vital native forage grass in northern China for ecological restoration and livestock production, faces severe yield losses and grassland degradation due to rust (Puccinia spp.) infection. Current control strategies, reliant on chemical interventions, are limited by evolving resistance risks and environmental concerns, while rust-resistant breeding remains hindered by insufficient molecular insights. To address this, we systematically evaluated rust resistance in 24 L. chinensis germplasms from diverse geographic origins, identifying six highly resistant (HR) and five extremely susceptible (ES) genotypes. Integrating transcriptomics and metabolomics, we dissected molecular responses to Puccinia infection, focusing on contrasting HR (Lc71) and ES (Lc5) germplasms at 48 h post-inoculation. Transcriptomic analysis revealed 1012 differentially expressed genes (DEGs: 247 upregulated, 765 downregulated), with enrichment in cell wall biosynthesis and photosynthesis pathways but suppression of flavonoid synthesis. Metabolomic profiling identified 287 differentially accumulated metabolites (DAMs: 133 upregulated, 188 downregulated), showing significant downregulation of pterocarpans and flavonoids in HR germplasms, alongside upregulated cutin synthesis-related metabolites. Multi-omics integration uncovered 79 co-enriched pathways, pinpointing critical regulatory networks: (1) In the nucleotide metabolism pathway, genes Lc5Ns011910, Lc1Xm057211, and Lc4Xm043884 exhibited negative cor-relations with metabolites Deoxycytidine and Cytosine. (2) In flavonoid biosynthesis, Lc2Xm054924, Lc4Xm044161, novel.8850, Lc2Ns006303, and Lc7Ns021884 were linked to naringenin and naringenin-7-O-glucoside accumulation. These candidate genes likely orchestrate rust resistance mechanisms in L. chinensis. Our findings advance the molecular understanding of rust resistance and provide actionable targets for breeding resilient germplasms. Full article

The design of materials with programmable degradation profiles presents a fundamental challenge in pattern recognition across molecular space, requiring the identification of complex structure–property relationships within an exponentially large chemical domain. This paper introduces a novel physics-informed deep learning framework that integrates multi-scale molecular sensing data with reinforcement learning algorithms to enable intelligent characterization and prediction of polymer degradation dynamics. Our method combines three key innovations: (1) a dual-channel sensing architecture that fuses spectroscopic signatures from Graph Isomorphism Networks with temporal degradation patterns captured by transformer-based models, enabling comprehensive molecular state detection across multiple scales; (2) a physics-constrained policy network that ensures sensor measurements adhere to thermodynamic principles while optimizing the exploration of degradation pathways; and (3) a hierarchical signal processing system that balances multiple sensing modalities through adaptive weighting schemes learned from experimental feedback. The framework employs curriculum-based training that progressively increases molecular complexity, enabling robust detection of degradation markers linking polymer architectures to enzymatic breakdown kinetics. Experimental validation through automated synthesis and in situ characterization of 847 novel polymers demonstrates the framework’s sensing capabilities, achieving a 73.2% synthesis success rate and identifying 42 structures with precisely monitored degradation profiles spanning 6 to 24 months. Learned molecular patterns reveal previously undetected correlations between specific spectroscopic signatures and degradation susceptibility, validated through accelerated aging studies with continuous sensor monitoring. Our results establish that physics-informed constraints significantly improve both the validity (94.7%) and diversity (0.82 Tanimoto distance) of generated molecular structures compared with unconstrained baselines. This work advances the convergence of intelligent sensing technologies and materials science, demonstrating how physics-informed machine learning can enhance real-time monitoring capabilities for next-generation sustainable materials. Full article

The plant Synsepalum dulcificum is notable for its considerable edible and medicinal value, with a longstanding history as a folk remedy for diabetes. Its chemical constituents are rich and structurally diverse. However, there is limited information regarding the metabolic basis of these characteristics, and the biological activities and mechanisms underlying its blood glucose-lowering effects remain incompletely understood. In this study, we conducted a widely targeted metabolomics analysis of the stems, leaves, and fruits of S. dulcificum using UPLC-ESI-MS/MS to compare the differences in metabolite profiles among these three tissue types. Our analysis identified a total of 2544 secondary metabolites, primarily consisting of flavonoids and triterpenes, categorized into thirteen distinct compound classes. We selected differential metabolites through multivariate statistical analysis, revealing significant differences among the metabolite profiles of the three tissue types, with flavonoids being the most abundant compounds. Furthermore, we investigated the anti-diabetic mechanisms and potential pharmacological components of S. dulcificum utilizing network pharmacology and molecular docking techniques. Finally, the α-glucosidase inhibitory activity of the potential active components was evaluated using in vitro experiments. These findings establish a foundation for the future application of S. dulcificum in the prevention and treatment of diabetes. Full article

The current study investigates the chemical profiling, antioxidant activities, and enzyme inhibitory and cytotoxic potential of the water and methanolic extracts of different parts (flower, leaf, and bulb) of Muscari armeniacum. Chemical profiling was performed using UHPLC-MS/MS. At the same time, different in vitro assays were employed to support the results for antioxidant potential, such as DPPH, ABTS, FRAP, CUPRAC, metal chelation, and PBD, along with the measurement of total phenolic and flavonoid contents. Enzyme inhibition was investigated for cholinesterase (AChE and BChE), α-amylase, α-glucosidase, and tyrosinase enzymes. Additionally, the relative expression of NRF2, HMOX1, and YGS was evaluated by qPCR. LC-MS/MS analysis indicated the presence of some significant compounds, including apigenin, muscaroside, hyacinthacine A, B, and C, and luteolin. According to the results, the highest TPC and TFC were obtained with both extracts of the leaves, followed by the water extract (flower) and methanolic extract of the bulb. In contrast, the methanolic extract from the bulb exhibited the highest antioxidant potential using DPPH, ABTS, CUPRAC, and FRAP, followed by the extracts of leaves. In contrast, the leaf extracts had the highest values for the PBD assay and maximum chelation ability compared to other tested extracts. According to the enzyme inhibition studies, the methanolic extract from the bulb appeared to be the most potent inhibitor for all the tested enzymes, with the highest values obtained for AChE (1.96 ± 0.05), BChE (2.19 ± 0.33), α-amylase (0.56 ± 0.02), α-glucosidase (2.32 ± 0.01), and tyrosinase (57.19 ± 0.87). Interestingly, the water extract from the bulb did not inhibit most of the tested enzymes. The relative expression of NRF2 based on qPCR analysis was considerably greater in the flower methanol extract compared to the other extracts (p < 0.05). The relative expression of HMOX1 was stable in all the extracts, whereas YGS expression remained stable in all the treatments and had no statistical differences. The current results indicate that the components of M. armeniacum (leaves, flowers, and bulb) may be a useful source of natural bioactive compounds that are effective against oxidative stress-related conditions, including hyperglycemia, skin disorders, and neurodegenerative diseases. Complementary in silico approaches, including molecular docking, dynamics simulations, and transcription factor (TF) network analysis for NFE2L2, supported the experimental findings and suggested possible multi-target interactions for the selected compounds. Full article

The Iris genus is known for its large blooms and significant conservation value, as well as its horticultural appeal. There are over 300 species of irises, which are widely distributed across the northern temperate zone. Iris palaestina (Baker) Barbey, commonly known as the Lebanese iris, is an endemic species of the Middle East with limited prior phytochemical research. This study was conducted to examine the metabolomic complexity and chemical profile of the flower extract of I. palaestina using advanced analytical tools. Molecular networking was employed to investigate its chemotaxonomy and phytochemical composition. In silico annotation tools—network annotation propagation (NAP), DEREPLICATOR, and MS2LDA—were applied to identify chemical classes and substructures within the extract. The flower extract of I. palaestina was found to contain diverse metabolite classes, including flavonoids, terpenoids, and lipids, with a total of 15 compounds annotated. Subsequent chromatographic separation yielded four major compounds, identified as the isoflavonoid irigenin, the flavonoid embinin, the xanthone mangiferin, and the lipid N-lauryldiethanolamine. Among these, irigenin and mangiferin exhibited significant α-glucosidase inhibitory activity, with IC₅₀ values of 32.1 μM and 36.1 μM, respectively. This study provides the first comprehensive metabolomic characterization of I. palaestina, revealing it as a rich source of bioactive phytochemicals spanning multiple metabolite subclasses. These findings emphasize the possible use of I. palaestina for further pharmaceutical investigation and natural product discovery. Full article

Background/Objectives: This study investigates the phytochemical composition and anticancer activity of Melaleuca quinquenervia leaf essential oil (MQLEO) from Egypt. Methods: Chemical profiling was performed using GC/MS. Anticancer activity was assessed through cytotoxicity screening against multiple cancer cell lines, with a subsequent evaluation of cell migration, apoptosis, and cell cycle analysis on the most sensitive line (A549). Network pharmacology and molecular docking analyses were employed to identify potential molecular targets and pathways. Results: GC/MS analysis revealed a unique profile dominated by 1,8-cineole (31.57%), α-pinene isomers (both 1R and 1S forms, collectively 21.26%), and sesquiterpene alcohols (viridiflorol: 13.65%; ledol: 4.55%). These results diverge from prior studies, showing a 25.63% decrease in 1,8-cineole and no detectable α-terpineol, suggesting environmental, genetic, or methodological impacts on biosynthesis. In vitro tests revealed selective cytotoxicity against A549 lung cancer cells (IC₅₀ = 18.09 μg/mL; selectivity index = 4.30), meeting NCI criteria. Staurosporine was used as a positive control to validate the assays, confirming the reliability of the methods. MQLEO also inhibited cell migration (62–68% wound closure reduction) and induced apoptosis (24.32% vs. 0.7% in controls). Cell cycle arrest at the G₀-G₁ phase implicated cyclin-dependent kinase regulation. Network pharmacology identified ESR1, CASP3, PPARG, and PTGS2 as key targets, with MQLEO components engaging apoptosis, inflammation (TNF, IL-17), and estrogen pathways. Conclusions: MQLEO demonstrates promising anticancer activity through multiple mechanisms including apoptosis induction, cell cycle arrest, and migration inhibition. The multi-target activity profile highlights its potential as a therapeutic candidate for lung cancer, warranting further in vivo validation and pharmacokinetic studies to advance clinical translation. Full article

Conyza sumatrensis is a plant of the Asteraceae family widespread in the tropical and subtropical regions of all continents. The plant is applied in folk medicine to treat malaria and helminth infections as well as other diseases. In Uganda, for example, the plant is traditionally used against ectoparasites and for wound healing. In this work, we describe a comprehensive analytical approach to investigate the metabolic profile of C. sumatrensis supported by database-assisted annotation and in silico techniques. The study aimed to analyze the metabolic profile of C. sumatrensis using multiple analytical techniques due to the complexity of the plant composition. Therefore, we employed a combination of thin-layer chromatography (TLC), high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-tandem mass spectrometry (LC-MS/MS). From the GC-MS experiments, more than 40 compounds could be annotated that had not been found in C. sumatrensis before. A number of these substances are known to possess relevant bioactivities, including antibacterial properties. Indeed, ethanolic extracts demonstrated antimicrobial activity against representative strains of both Gram-positive and Gram-negative bacteria, as shown by agar diffusion and microdilution assays. Using LC-MS/MS data, a feature-based molecular network was constructed to facilitate the comparison of two extraction solvents: water and ethanol. The majority of the features were detected in both of the extracts. However, some features were only detected using one of the extraction solvents. Our work provided valuable insights into the chemical profile of C. sumatrensis and lays the foundation for future research into its medicinal properties. Full article

This study compares the antioxidant properties and phytochemical profiles of three pairs of widely used medicinal plant species to their counterparts from Provence, France: Arnica montana with Pentanema montanum (formerly known as Inula montana), Helichrysum italicum with Helichrysum stoechas, and Satureja hortensis with Satureja montana. Phytochemical composition has been investigated using UHPLC-HRMS/MS and molecular networking, revealing chemical profiles dominated by phenylpropanoids and flavonoids, with lignans, sesquiterpene lactones, or polyketides aside. Well-plate DPPH/ABTS assays were used to evaluate the antioxidant activity of extracts, and post-column assays were used to identify antioxidant compounds. The three Provence species demonstrated comparable or superior antioxidant activities to their counterparts, primarily attributed to phenolic compounds such as mono- and di-caffeoylquinic acids, quercetagetin-7-O-glucoside, and myricetin acetylhexoside. These findings show the potential of Provence species to be substituted for some overharvested medicinal plants. This research supports biodiversity conservation while promoting the integration of these local species into pharmaceutical, nutraceutical, cosmetic, and food industries. Full article

The flowers of Santolina chamaecyparissus have a distinct aroma and taste, with a wide range of applications in medicine, food, and packaging. Its essential oil offers numerous health benefits, including antioxidant, hepatoprotective, anticancer, antidiabetic, spasmolytic, anti-inflammatory, immunomodulatory, antimicrobial, and antiparasitic properties. Additionally, it is used as a flavoring agent in food and beverages and as a natural preservative in edible coatings for food packaging. This study investigates the chemical composition and sensory properties of the S. chamaecyparissus essential oil from Serbia, obtained via hydrodistillation, and includes a literature-based analysis of the existing profiles. Gas Chromatography–Mass Spectrometry (GC–MS) was employed for identifying the essential oil composition, while chemometric techniques like the genetic algorithm (GA), quantitative structure–retention relationship (QSRR) analysis, artificial neural network (ANN), and molecular descriptors were applied to ensure accurate and reliable results for authenticating the oil. Among the 47 identified compounds, oxygenated monoterpenes, especially artemisia ketone (36.11%), and oxygenated sesquiterpenes, notably vulgarone B (22.13%), were the primary constituents. Chemometric analysis proved effective in predicting the oil’s composition, and sensory evaluation revealed a herbal aroma with earthy, woody, and camphoraceous notes. A literature review highlighted the variability in oil composition due to geographical, environmental, and extraction factors, underscoring its chemical diversity, bioactivity, and potential applications. Full article

Background/Objectives: Cancer remains one of the leading causes of mortality globally, underscoring the need for novel therapeutic strategies capable of targeting multiple molecular pathways simultaneously. Natural products, particularly fungal-derived metabolites from the genus Cordyceps, represent promising candidates due to their diverse biological activities. Although previous studies have indicated the anticancer potential of Cordyceps species, systematic characterization of their molecular targets has been limited. This study aimed to comprehensively identify and evaluate Cordyceps metabolites as potential multitarget anticancer agents through a network pharmacology approach. Methods: A total of 129 metabolites previously reported in the literature from polar aqueous, alcoholic, and non-polar extracts of Cordyceps were compiled and chemically classified using ChemMine tools. Structure-based target prediction and pathway enrichment analyses were performed to investigate their potential biological targets. Predicted molecular targets were cross-referenced with differentially expressed genes in breast, colorectal, and lung cancers to identify hub proteins. Molecular docking simulations were conducted to assess binding affinities of metabolites to key oncogenic targets, and SwissADME was utilized for pharmacokinetic profiling. Results: The analysis revealed that Cordyceps metabolites targeted critical oncogenic pathways, including cell cycle regulation, DNA replication, and apoptosis. Hub proteins such as TYMS, AURKA, and CDK1 were identified as primary targets. Docking simulations highlighted metabolites such as cordycepsidone A, jiangxienone, and flazin, demonstrating binding affinities comparable or superior to clinically used inhibitors. Pharmacokinetic profiling identified several metabolites with favorable drug-like properties, supporting their potential as lead compounds. Conclusions:Cordyceps extracts contain structurally diverse metabolites capable of modulating multiple cancer-relevant molecular targets, providing a robust foundation for their development into multitarget anticancer therapies. This integrative network pharmacology approach underscores the potential of fungal metabolites in oncology drug discovery. Full article

Background: Yupingfeng San (YPFS) is a classic formula for treating allergic rhinitis (AR), which is composed of Astragalus mongholicus Bunge (AST), Atractylodes macrocephala Koidz (AMR), and Saposhni-kovia divaricata (Turcz.) Schischk (SR) at a ratio of 3:1:1. However, the potential bioactive components of YPFS relevant to AR treatment are currently unknown. Methods: This study combined in vivo chemical profiling, network pharmacology, and experimental validation to identify the substances in YPFS that are active against AR. Results: Firstly, 98 compounds in YPFS were identified using high-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS/MS) with the assistance of Global Natural Products Social (GNPS) molecular networking. Then, 42 prototype components and 57 metabolites were detected in the plasma, urine, and feces of mice with AR. A network pharmacological analysis based on 42 in vivo prototypical components was also conducted to screen 15 key components and 10 core targets, and 6 key components were further selected through molecular docking. Finally, the four key active components (cimifugin, wogonin, formononetin, and atractylenolide I) were revealed to be the main ingredients of YPFS through validation (in vitro and in vivo). Conclusions: This is the first systematic study of the components of YPFS in AR mice, laying the foundation for elucidating the overall material basis of this formulation. This study provides rich basic data for further pharmacological and mechanistic studies on YPFS. Full article

Theobroma grandiflorum (copoazu) is a plant native to South America, widely cultivated in countries within the Amazon region. Its unique phytochemical composition imparts distinctive organoleptic properties, making it an exotic fruit. In this study, headspace solid-phase microextraction (HS-SPME) combined with gas chromatography–mass spectrometry (GC-MS) was used to identify the volatile organic compounds (VOCs) produced by copoazu. The optimal conditions for sample pretreatment were first determined using a Design of Experiments (DoE) approach. Analysis of the volatile profiles enabled the identification of 96 copoazu VOCs across three ripening stages. Of these, 79 VOCs were classified into chemical compound families using spectral correlation analysis across various libraries and databases, as well as molecular network analysis. Additionally, a volatilomic analysis was conducted to examine the changes in VOCs throughout the ripening process. Molecular network analysis showed that the VOCs emitted by the fruit are linked to the interconversion of compounds, which can be observed through the study of the metabolic pathways. These findings provide a comprehensive analysis of the copoazu volatilome, providing valuable insights into the organoleptic characteristics of this Amazonian fruit. Esters and terpenes such as α-terpineol, trans-4-methoxythujane, linalool, 2-methylbutyl butanoate, 3-methylbut-2-enoic acid, 2-methylpentyl ester, and 2-methylpropyl hexanoate were identified as potential biomarkers associated with the copoazu ripening process. Full article

Background: Centranthera grandiflora Benth is commonly utilized in China to take advantage of its purported health benefits. Methods: Here, the chemical composition, nutritional value, and bioactivity of C. grandiflora Benth extract (CGE) are characterized, and the mechanisms through which it functions were explored. Results: CGE was found to exhibit a favorable nutritional and biosafety profile, especially due to its high amino acid and mineral contents. A UPLC-ESI-Q-TOF/MS approach identified 20 compounds. Through network pharmacology analyses, the antioxidant activity of CGE was found to be mediated through the PI3K/Akt pathway, with molecular docking results providing support for mussaenoside and azafrin as important bioactive compounds. At the cellular level, antioxidant activity of key protective antioxidants including GSH-Px and SOD while suppressing ROS accumulation, levels of damage-related factors (MDA, NO, TNF-α, IL-1β, and IL-6), and iNOS and COX-2 in RAW264.7 cells treated with LPS. These findings offer potential evidence for using CGE to lower oxidative stress and inflammation. Further analyses demonstrated the ability of CGE to promote Nrf2 and HO-1 upregulation, whereas Keap1 levels were suppressed, as were PI3K/Akt/NF-κB proteins. In light of these results, CGE appears to be able to act via simultaneously enhancing Nrf2/HO-1 activity and reducing that of PI3K/Akt/NF-κB. Conclusions: CGE, as a rich source of iridoid glycosides and other nutrients, may thus be a valuable dietary supplement for use in food applications. Full article

Invertase (INV, EC3.2.1.26) is widely recognized as an indispensable enzyme for catalyzing sucrose degradation and plays a central role in plant growth as well as fruit quality improvement. However, no systematic study has been performed in kiwifruit. Here, we identified 102 AaINV genes in the Actinidia arguta “M1” genome. Their physical and chemical properties, subcellular localizations, phylogenetic relationships and expression profiles were characterized. Phylogenetic analysis showed that the INV members were clustered into three groups (vacuole invertases (VINVs) and cell wall invertases (CWINVs) in Group I, alkaline/neutral invertase (NINVs) in Group II and Group III), demonstrating evolutionary conservation in the INV family across Arabidopsis and Actinidia species. Gene replication analysis revealed that many AaINV genes were derived from gene duplication events. Molecular evolution analysis based on Ka/Ks ratios indicated that the INV members have experienced extensive purifying selection during evolution. To explore the potential gene functions, we integrated RNA-seq and metabolomics to analyze AaINV gene expression patterns and sugar accumulation in three A. arguta varieties (“Kukuwa”, “Qinhuang”, “Xianziguang”), respectively. The expression analysis of the 102 genes showed that the expression patterns varied among the three kiwifruit varieties at fruit maturity stage. The expression levels of AaINVs were also investigated via qRT-PCR in these varieties. Specifically, we constructed a complex regulatory network that regulates sugar metabolism in kiwifruit based on the correlation between 42 AaINV genes and 14 sugar metabolites. These findings provide insights into physiological functions of AaINVs in kiwifruit, especially roles in governing sugars accumulation in fruits. Full article

Background: Ischemic heart disease (IHD), a leading cause of cardiovascular morbidity and mortality, continues to challenge modern medicine. Bombyx mori (Abresham), a traditional ingredient in Unani medicine, has shown promise in cardiovascular health, but its molecular mechanisms remain poorly understood. Methods: To explore the therapeutic potential of Bombyx mori for IHD, an integrative molecular simulation approach was applied. Network pharmacology was employed to identify the most favorable target receptor for the disease. Molecular docking simulations evaluated the binding affinities of chemical and protein-based compounds from Bombyx mori to the selected receptor. Molecular dynamics (MD) simulations confirmed the stability of these interactions under physiological conditions. Pharmacophore modeling identified key structural features critical for bioactivity, while in silico toxicity assessments evaluated the safety profiles of the compounds. Results: Key bioactive compounds from Bombyx mori, including Menaquinone-7, Quercetin, and Behenic acid, showed strong interactions with the target receptor, ACE2. The MD-based MM/PBSA calculations revealed the binding free energy values of Menaquinone-7 (−35.12 kcal/mol), Quercetin (−29.38 kcal/mol), and Behenic acid (−27.76 kcal/mol), confirming their strong binding affinity. Protein-based compounds, such as Chorion class high-cysteine HCB protein 13 (−212.43 kcal/mol), Bombyxin A-5 (−209.36 kcal/mol), and FMRFamide-related peptides (−198.93 kcal/mol), also displayed promising binding affinities. In silico toxicity assessments revealed favorable safety profiles for most compounds. Conclusions: This study positions Bombyx mori as a promising source of therapeutic agents for IHD. Future work should focus on experimental validation of these computational findings through in vitro and in vivo studies. Full article