This manuscript investigates the utilization of chitosan (CS) as a preservative in the food industry, covering its sources, extraction methods, structural properties, and preparation techniques. CS, derived from shell wastes of crustaceans and various fungi, offers promising antimicrobial and antioxidant properties due to factors like degree of deacetylation and molecular weight. Its application as a preservative spans across diverse food sectors, showcasing its effectiveness in enhancing food quality and extending shelf life while minimizing reliance on chemical additives. CS fortification demonstrates notable impacts on food composition, including moisture retention, reduced lipid oxidation, and improved protein functionality. Notably, its application in the meat and seafood industries proves effective in inhibiting bacterial growth and preserving product freshness. Additionally, the antioxidant activity of CS, influenced by its structural characteristics and supplementation with natural compounds, contributes to its role as a secondary antioxidant in food products. By summarizing existing studies and research, this document provides a comprehensive understanding of CS's multifaceted applications and benefits in enhancing food quality and promoting sustainable practices in food preservation.
Label-free quantitative detection of chemically diverse molecules is of critical importance across fields spanning medical diagnostics, food safety, and law enforcement. Surface-enhanced Raman spectroscopy (SERS) provides powerful molecular identification through fingerprint spectra, capable of achieving single-molecule detection limits when analytes are positioned directly at the plasmonic hotspots of Au/Ag substrates. Yet conventional contact-mode SERS, which relies on the direct adsorption of analytes onto bare metal surfaces, is limited by poor reproducibility and signal heterogeneity arising from random molecular orientations and competitive binding. Here, we present a proof-of-concept noncontact mode SERS platform that routinely delivers reproducible, predictable, and quantitative spectra readout, including discrimination of subtle enantiomeric differences. This platform utilizes fluorenylmethoxycarbonyl-lysine (Fmoc-Lys) scaffolds confined within 1-2 nm channels of nanoporous gold nanospheres. The Fmoc core captures target analytes through hydrophobic interactions, while the chiral center regulates the adsorption configuration/strength. This design fixes analyte distance and orientation relative to the metal surface, thereby minimizing stochastic spectral variation. We applied this platform to quantitatively analyzed methamphetamine (METH), a globally prevalent abused drug, in complex human urine samples and achieved accuracy comparable to mass spectrometry without requiring analyte-specific reference spectra. Our results highlight noncontact SERS as a general strategy for reliable, ultrasensitive molecular analysis, especially for targets lacking standard spectral libraries.
Although existing molecular pretraining models have achieved favorable performance on various downstream tasks, their reliance on explicit three-dimensional conformer sampling or external natural-language corpora often increases computational cost and affects structural fidelity. Here, we propose ClipMol, a molecular representation learning framework based on SMILES-InChI dual-view chemical-language alignment. Without requiring explicit three-dimensional conformers or external corpora, ClipMol jointly models local chemical microenvironments and global structural constraints of molecules. Benchmark results show that ClipMol and its scaled variant, ClipMol-XL, achieve strong overall performance on both classification and regression tasks. More importantly, for collision cross-section (CCS) prediction in ion mobility-mass spectrometry, ClipMol shows stable and competitive performance on two independent benchmark data sets, METLIN-CCS and ALLCCS, while maintaining robustness across different adduct compositions and diverse chemical categories. Compared with state-of-the-art and competitive CCS prediction models, the ClipMol models achieved the best or highly competitive averaged performance on both data sets, with ClipMol-XL showing the strongest overall R2 and root-mean-square error performance. Overall, ClipMol provides a scalable and structurally faithful solution for molecular representation learning and IM-MS-related CCS prediction in analytical chemistry.
Spider venoms are rich sources of peptide toxins that modulate ion channels and receptors. Although individual toxins from the genus Psalmopoeus have been shown to be critical for probing the function of certain ion channels, the overall venom composition of this genus remains poorly characterized. In this study, we investigated the molecular and structural features of peptide toxins from the spider Psalmopoeus pulcher (P. pulcher), focusing on peptide diversity and structural architecture. The molecular diversity of P. pulcher venom was examined through mass spectrometric analysis combined with construction of a venom-gland cDNA library. A total of 495 high-quality expressed sequence tags (ESTs) were obtained, including 357 toxin-like ESTs, encoding 69 non-redundant toxin precursors containing signal peptides. Based on sequence homology and cysteine frameworks, these precursors were classified into 11 families. Structural predictions using AlphaFold 3 revealed marked diversity in cysteine connectivity and folding patterns among the predicted mature peptides, encompassing canonical inhibitory cystine knot scaffolds, disulfide-directed hairpin motifs, peptides with expanded disulfide networks, and a subset of precursors predicted to adopt complex, multi-domain architectures. Functional exploration combining sequence analysis, molecular docking, and limited experimental validation identified Pp1a, a PcTx1-like peptide encoded by multiple precursors, as an inhibitor of acid-sensing ion channel 1a (ASIC1a). Collectively, this study expands current knowledge of the molecular diversity and structural characteristics of P. pulcher venom peptide and provides a foundation for further functional exploration and utilization of this venom-derived peptide resource.
Hepatocellular carcinoma (HCC) is an aggressive malignancy with limited therapies. We explored the anti-HCC mechanisms of Zanthoxylum nitidum (Roxb.) DC. via network pharmacology, bioinformatics and molecular docking. We identified its active components, targets and HCC-related key genes by differential expression analysis. Enrichment analysis showed these targets act in HCC-related pathways like alcoholic liver disease and the PPAR signalling pathway. Machine learning screened 5 characteristic genes (ESR1, CCNA2, CYP2B6, CHRM2, IL10), among which ESR1 and CCNA2 correlate with patient prognosis. These genes regulate tumour microenvironment and show epigenetic variations in methylation and copy number. Molecular docking confirmed stable binding between plant components and core targets. This study first reveals the multi-target anti-HCC mechanisms of Z. nitidum, offering evidence for its clinical use. Follow-up experiments are needed to validate our findings.
Public health nutrition lacks scalable, objective tools for real-time dietary surveillance. We developed FoodSeq-FLOW (Food Landscape Observation in Wastewater), a genomic platform that sequences chloroplast trnL and mitochondrial 12SV5 DNA in municipal wastewater. Across 183 samples from 21 North Carolina wastewater treatment plants serving 2.1 million people, we detected 184 plant and 116 animal food taxa at a cost of <US $0.01 per person. Wastewater-derived dietary profiles correlated with paired individual stool dietary data (Spearman ρ = 0.64), and 98% of animal-derived sequences mapped to known food taxa. Temporal sampling revealed seasonal shifts in food taxa consistent with regional food availability patterns. Spatial analysis revealed community-level dietary signatures associated with per capita income and education, beer ingredient abundance with discretionary income, tropical fruits and pulses with foreign-born population size, and local seafood with coastal geography. FoodSeq-FLOW extends wastewater-based epidemiology from pathogens to diet, providing a scalable platform that existing global wastewater surveillance networks can deploy to inform nutrition policy and market analytics.
Hawthorn vinegar is a fermented product with functional properties, containing phenolic compounds and bioactive ingredients that could promote health. In this study, ultrasound-ohmic (USOH) processing conditions were optimized using a hybrid machine-learning-based approach to maximize the α-glucosidase and α-amylase and inhibitory activities of hawthorn vinegar. A Box-Behnken experimental design with 27 runs was used, including four independent variables: ultrasound amplitude (40-80%), ultrasound duration (2-6 min), ohmic field strength (20-40 V/cm), and ohmic heating time (2-6 min). Thirteen machine learning algorithms were comparatively evaluated using systematic hyperparameter optimization with GridSearchCV and 5-fold cross-validation. The Lasso Poly2 model showed the highest predictive performance for both α-glucosidase and α-amylase inhibition, with CV R 2 values of 0.9301 and 0.9299, respectively, and low MAPE values (<1%). Metaheuristic optimization algorithms, including Particle Swarm Optimization (PSO), Differential Evolution (DE), and Gray Wolf Optimization (GWO), converged to similar optimum processing conditions, indicating the robustness of the optimized process region. Under the combined optimal conditions, the experimental α-amylase and α-glucosidase inhibition activities were 39.27 ± 1.36% and 37.54 ± 0.53%, respectively. In addition, USOH treatment significantly enhanced the phenolic profile of hawthorn vinegar compared to thermally pasteurized and untreated samples. In particular, the contents of chlorogenic acid, catechin hydrate, caffeic acid, rutin, naringin, resveratrol, and quercetin were markedly increased after treatment. Additionally, five phenolic compounds were evaluated by molecular docking analysis against α-amylase and α-glucosidase, and the strongest binding affinities were observed for naringin (-7.40 kcal/mol) and chlorogenic acid (-7.17 kcal/mol), respectively. These findings demonstrate that machine learning-assisted ultrasound-ohmic processing can effectively improve the antidiabetic and functional properties of hawthorn vinegar.
Genetic engineering was utilized to fuse transglucosidase (TG) and hexose oxidase (HOX), producing a fusion enzyme TGHOX. This novel enzyme eenabled a sequence reaction involving starch chain transformation and oxidation in a single system. Compared with native wheat starch (24.07% amylose), TGHOX treatment increased the amylose content of wheat starch, with the TGHOX-16 treatment reaching a maximum amylose content of 41.77%. The A-chain content of wheat starch increased from 31.31% to 41.68% after TGHOX treatment. Higher A-chain content provided more highly accessible non-reducing end substrates for transglycosylation for TGHOX, thereby increasing the branching density of starch to 6.3%. Furthermore, the branched terminals with reactive hydroxyl groups served as abundant substrates for oxidation by the HOX moiety. This, yielded carbonyl and carboxyl content of 0.3847 g/100 g and 0.4003 g/100 g, respectively. The oxidative modification reduced the relative crystallinity of starch from 36.95% to 28.42% and disrupted the intermolecular chain aggregation (from -6.13 mV to -24.91 mV). This green and efficient fusion enzyme system shows promising potential for industrial production of oxidized starch.
Multicomponent membrane organization of mRNA-lipid nanoparticles (LNPs) critically determines their formulation behavior, organ selectivity, and immunological outcomes. However, compared to ionizable lipids, sterols remain a relatively underexplored design axis. This study discusses the engineering of a library of nine bile acid-derived sterols with different hydroxylation patterns and alkyl tail lengths, and systematically maps how sterol structure governs formulation-level properties and organ-level expression profiles. After integrating physicochemical characterization with all-atom molecular dynamics (MD) simulations, the experimentally observed formulation behaviors correlate with MD-derived membrane structural descriptors. These descriptors provide a quantitative evaluation framework for prioritizing sterol chemotypes based on their predicted encapsulation performance and membrane organization, supporting the notion that sterol-dependent membrane organization provides a structural basis for formulation properties, including mRNA encapsulation. Moreover, substituting cholesterol with bile acid-derived sterols consistently attenuated hepatic expression and shifted organ-level expression toward spleen-dominant profiles, which is central to immune priming and adaptive immune activation. Among bile acid-derived sterols, CA-20 LNPs functionally enhance antigen-specific humoral immunity and elicit antigen-specific cellular immune responses, including improved memory-associated immune features, while maintaining an acute safety profile. Collectively, these results establish sterol engineering as a powerful design strategy for modulating LNP formulation properties, in vivo fate, and immunological function.
This study reports the synthesis, structural characterization, and antibacterial evaluation of 5-(3-nitrophenyl)-1,3,4-thiadiazol-2-amine (NPTA), a commercially available thiadiazole derivative with potential antimicrobial activity. NPTA was synthesized through a green, one-pot condensation reaction between thiosemicarbazide and 3-nitrobenzoic acid in absolute ethanol, affording a pale-yellow crystalline solid with a melting point of 110 °C-112 °C. The compound was characterized using Fourier-transform infrared (FTIR) and nuclear magnetic resonance (NMR) spectroscopy, confirming its structure. In vitro antibacterial assays, in silico ADMET and toxicity profiling, molecular docking, frontier molecular orbital (FMO) analysis, and 200 ns molecular dynamics simulations were performed. In vitro antibacterial assays revealed significant activity against Klebsiella pneumoniae ATCC 13883, Acinetobacter baumannii, and Listeria monocytogenes ATCC 19114, with growth inhibition zones of 25.63 ± 0.17 mm, 29.09 ± 1.31 mm, and 26.65 ± 0.19 mm, respectively, and minimum inhibitory concentrations (MICs) ranging from 50 to 100 μg/mL. In silico ADMET and toxicity profiling predicted favourable drug-likeness, absorption, and safety. Molecular docking indicated strong binding affinities (-6.2 to -7.0 kcal/mol) with key bacterial targets, i.e., DNA gyrase subunit B (PDB: 1KZN) and penicillin-binding protein 4 (PDB: 3HUN). Frontier molecular orbital (FMO) analysis revealed a HOMO-LUMO energy gap of 3.79 eV, suggesting high electronic stability and reactivity. Furthermore, 200 ns molecular dynamics simulations confirmed the temporal stability of NPTA-protein complexes, particularly with DNA gyrase subunit B. These results demonstrate the promising antibacterial potential of NPTA and support its further development as a multifunctional thiadiazole-based antimicrobial candidate.
Taste is a key determinant of food preference and involves basic tastes and complex sensations such as mouthfeel. To understand taste at a molecular level, researchers have used cryo-electron microscopy (cryo-EM) to determine the structures of taste receptors. Cryo-EM has also been applied to analyze the interactions between food components and biological systems, playing a vital role in food science. A key example is the calcium-sensing receptor (CaSR), a class C G-protein-coupled receptor (GPCR) essential for the oral perception of kokumi substances, which are taste modulators. We used cryo-EM to determine the structure of CaSR complexed with γ-glutamyl-valyl-glycine (γ-EVG), a potent kokumi peptide. This analysis identified the precise site and key residues of CaSR involved in binding γ-EVG. Identification of the molecular basis of kokumi peptide recognition facilitates the rational design of novel taste modulators for the food industry.
CPs possess considerable bioactive potential, yet their underlying immunomodulatory mechanisms remain incompletely elucidated. In the present work, CPCR were extracted from fresh cassava tubers and further separated into five purified polysaccharide fractions (CP1-CP5) with distinct monosaccharide profiles and molecular weights. Systematically investigated the immunomodulatory capacities of CPCR and its purified fractions via in vivo assays using Cy-induced immunosuppressed mice and in vitro tests on RAW264.7 murine macrophages. Multiple readouts were quantified, including gut microbial community structure, fecal SCFAs concentrations, intestinal tight junction protein expression, serum anti-inflammatory cytokine levels, as well as macrophage proliferation, phagocytic activity and inflammatory mediator release. In vivo data demonstrated that CPCR reshaped gut microbiota homeostasis by selectively enriching beneficial commensal genera and families linked to intestinal health, namely Muribaculaceae, Bacteroides, Alloprevotella, and Prevotellaceae. Enrichment of these probiotic taxa boosted intestinal SCFAs production; notably, fecal acetic acid concentration reached 141.0 mg/g following CPCR intervention, significantly exceeding levels measured in both normal control and Cy-induced immunosuppressed groups. Moreover, CPCR robustly upregulated the expression of intestinal barrier proteins ZO-1, occludin and Claudin-1, facilitating the repair and preservation of intestinal epithelial integrity. Serum cytokine profiling revealed prominent elevations in the anti-inflammatory mediators IL-2, IL-4 and IL-10 upon CPCR administration. Structural characterization of isolated subfractions revealed stark compositional disparities: CP1 predominantly consisted of 97% glucose with a molecular weight of 3 kDa, while CP2 contained 31.1% glucose, 20% galactose and 15.2% arabinose with a molecular weight of 62.4 kDa, this represents a preliminary structural characterization of the polysaccharide fractions. The results demonstrated that all CPs fractions could enhance immune cell activity, including phagocytic capacity and anti-inflammatory cytokine secretion. In summary, this study demonstrates that CPs exert immunostimulatory effects through dual pathways: direct activation of macrophage immune function and indirect regulation of gut microbiota-intestinal barrier homeostasis. Our results support the translational potential of CPs as bioactive functional food ingredients for immune regulation.
Alprazolam, a frequently prescribed anxiolytic, is extensively metabolized in the liver mostly by the cytochrome P450 3A4 (CYP3A4) enzyme. Cranberry and pomegranate juices, often suggested for their possible therapeutic effects in kidney stone management, have been identified as strong inhibitors of CYP3A4. This raises considerable concerns about possible drug-food interactions that could modify the pharmacodynamic profile of alprazolam. This study aimed to comprehensively assess the pharmacodynamic interactions between alprazolam and these juices, focusing on their collective impact on behavioral and histological results. Molecular docking studies were conducted utilizing AutoDock Vina to assess the binding affinities of active compounds from cranberry and pomegranate juices to the CYP3A4 enzyme, resulting in binding energies of -9.2 and -9.3 kcal/mol, respectively. In vivo tests were performed on adult male Wistar albino rats, which were divided into five experimental groups: control, alprazolam alone, and alprazolam co-administered with cranberry juice, pomegranate juice, or a combination of both. Pharmacodynamic interactions were evaluated via behavioral analyses using the Elevated Plus Maze, Rotarod, and Y-Maze tests to assess anxiety, motor coordination, and cognitive performance. Furthermore, histological analyses of brain tissues were performed to detect neuronal changes and evaluate the degree of neurodegeneration linked to the treatment. Molecular docking analyses revealed strong binding affinities of anthocyanins from cranberries and ellagic acid from pomegranates to the CYP3A4 enzyme, suggesting their ability to inhibit its activity. Behavioral tests indicated considerable deficits in memory and motor coordination in groups receiving cranberry or pomegranate drinks in conjunction with alprazolam, relative to the alprazolam-only and control groups. Histopathological examination of brain tissues supported these findings, revealing a significant elevation in neuronal degeneration in the coadministration groups compared to controls, indicating a synergistic effect on neurotoxicity. The pharmacodynamic changes observed suggest that the coadministration of cranberry and pomegranate juices with alprazolam alters the drug's effects, likely due to CYP3A4 inhibition by the juices' phytochemicals. These interactions may enhance alprazolam's neuropharmacological effects, resulting in an increased risk of cognitive and motor impairments. These findings underscore the clinical importance of monitoring food-drug interactions, especially in patients using natural products concurrently with CNS-active medications. This study highlights significant pharmacodynamic interactions between alprazolam and cranberry/pomegranate juices, highlighting their potential to influence the drug's therapeutic effectiveness and safety profile. The findings highlight the essential necessity for monitoring when concurrently administering these natural medicines with alprazolam, as their simultaneous usage may result in altered pharmacological effects and increased risk of adverse effects.
Brown algal extracts increase crop yield by stimulating growth and enhancing resistance to environmental stress, making them a sustainable and effective biostimulant for modern agriculture. Population growth, climate change, and intensive agrochemical use pose significant challenges to environmental sustainability and food security. Seaweeds, particularly brown algae, have attracted considerable attention as promising biostimulants for sustainable agricultural applications. Brown algae, the second most prevalent group of marine macroalgae, are rich in polysaccharides (alginates, fucoidans, and laminarins), vitamins, minerals, and polyphenols, which contribute to their biostimulant properties. Previous studies have provided important insights into the mechanisms of action of seaweed extracts and the physiological and biochemical changes they induce in crop plants. Although the molecular mechanisms underlying the effects of seaweed biostimulants remain incompletely understood, recent research efforts have substantially advanced our understanding of their functional roles. This review discusses conventional and advanced extraction techniques used to obtain bioactive compounds from seaweeds. In addition, it examines the composition of brown algae and their roles in promoting plant growth, development, and stress tolerance in various crop species. Furthermore, this review highlights the molecular mechanisms underlying growth promotion, biotic stress resistance, and abiotic stress tolerance in brown algae-treated plants, along with key findings from recent metabolomics studies. The use of brown algal extracts or their components influences crop plants by enhancing nutrient uptake, regulating phytohormone signalling, boosting antioxidant defence, facilitating osmotic adjustment, and stimulating stress-responsive genes and pathways. Collectively, these properties highlight the potential of brown algae-derived biostimulants to support sustainable agriculture by reducing the need for synthetic agrochemicals while increasing food security amid growing environmental challenges.
As persistent organic pollutants, polychlorinated biphenyls (PCBs) pose significant environmental and health risks due to their widespread contamination and bioaccumulation through the food chain. Therefore, the development of sensitive and reliable analytical methods for their accurate determination is critical. In this study, a competitive coordination strategy was employed to transform hydrogen-bonded organic frameworks into hollow metal-organic frameworks (MOFs) via a one-pot solvothermal process, in which metal-ligand coordination bonds played a key role in framework reconstruction. The resulting MOFs were subsequently used as precursors to synthesize nickel-doped hollow carbon nanotubes (nNi-HMCNTs) through pyrolysis. By adjusting the nickel content in the precursor, the pore structure and Ni-related interaction sites of the derived carbon materials were optimized, improving their suitability as solid-phase microextraction (SPME) coatings. When coupled with gas chromatography-tandem mass spectrometry (GC-MS/MS), the optimized 2.4Ni-HMCNTs coating enabled the sensitive determination of PCBs in food matrices. The established HS-SPME-GC-MS/MS method exhibited a wide linear range (0.001-1000 ng·L-1), low limits of detection (0.33-1.67 pg·L-1), and high enrichment factors (13897-14787). Furthermore, density functional theory calculations and experimental characterization were combined to elucidate the enrichment mechanism of PCBs on 2.4Ni-HMCNTs. This work provides a competitive coordination-regulated strategy for constructing hollow carbon-based SPME coatings and demonstrates its potential for trace contaminant enrichment in complex food samples.
Cassava brown streak disease (CBSD) threatens food security for millions in East Africa, yet its control remains limited by the absence of field-deployable molecular diagnostics. Here, we introduce ELLA (Electrochemical Lateral flow assay with Linked Analytics), a battery-free, smartphone-powered electrochemical lateral flow assay that delivers enzyme-linked immunosorbent assay (ELISA)-grade protein detection directly in the field. ELLA integrates near-field communication, a single-chip potentiostat, metal-pin electrodes, and ferrocene-labeled nanoparticles into a fully disposable cassette, enabling quantitative immunoassays without optical instrumentation or centralized laboratory infrastructure. Validated across laboratory studies and extensive field trials in Tanzania, ELLA achieved 95% agreement with ELISA and 89% agreement with RT-qPCR, outperforming ELISA's limit of detection while maintaining a material cost below US$1. By coupling molecular test results with cloud-linked analytics, we further trained DeepELLA, a smartphone-based image classification model that enables scalable surveillance from field-acquired leaf images. Together, these advances unify electrochemical sensing, digital connectivity, and AI-assisted interpretation, enabling portable, ELISA-level diagnostics for plant, environmental, and health monitoring in resource-limited regions.
Salvia (Lamiaceae) species have been used in food, cosmetics, and medicine for centuries. Besides their use as food, these species are potential raw material candidates for pharmaceuticals due to their rich phytochemical content. Studies on the endemic Turkish Salvia species examined in this study, S. ballsiana (Rech.f.) Hedge, S. hedgeana Dönmez, and S. vermifolia Hedge & Hub.-Mor., are very limited. The aim of this study is to evaluate the antioxidant, antidiabetic, and anti-obesity effects of these species and to elucidate their chemical profiles. In this context, the antidiabetic effect was determined by α-glucosidase and α-amylase inhibitory activity tests, and the anti-obesity effect was determined by the pancreatic lipase inhibitory activity test. The chemical profiles of the extracts were determined by LC-MS/MS. S. vermifolia and S. hedgeana demonstrated strong α-glucosidase inhibitory activity (IC50 values of 36.46 ± 1.25 and 52.89 ± 3.36 μg/mL, respectively). Among the extracts, the strongest α-amylase and pancreatic lipase inhibitory activity was found in the S. vermifolia extract (IC50 values 68.38 ± 4.27 and 89.46 ± 6.80 μg/mL, respectively). Additionally, the reference compounds acarbose and orlistat exhibited stronger inhibitory activity than all extracts: acarbose showed IC50 values of 1.52 ± 0.15 and 2.99 ± 0.04 μg/mL for α-glucosidase and α-amylase, respectively, while orlistat demonstrated pancreatic lipase inhibition with an IC50 value of 11.82 ± 2.54 μg/mL. S. vermifolia extract demonstrated strong metal chelation capacity, ABTS and DPPH radical scavenging activity (65.50%, 70.73% and 83.80%, respectively). Rosmarinic acid was found to be major phytoconstituent of the species with the highest inhibition potency on enzymes (S. vermifolia). Binding potential and mode of action for rosmarinic acid were explored through molecular docking. Results that corroborated the enzymatic assay studies were obtained.
Quercetin is a widely consumed dietary flavonoid and nutraceutical with diverse biological activities, yet the mechanisms underlying its potent antioxidant effects remain incompletely understood. This study aims to examine the hypothesis that quercetin's antioxidant efficacy is associated with a unique coordinating network in which radical-derived oxidation metabolites retain reducing capacity, supporting successive scavenging reactions and potentially contributing to selected regulatory pathways. To investigate this hypothesis, oxidation metabolites were first generated using 2,2-diphenyl-1-picrylhydrazyl as a readily monitored and well-controlled radical oxidant. The reaction mixture was separated using an Agilent 1290 Infinity ultrahigh-performance liquid chromatography system with a water-acetonitrile gradient. Metabolites of interest were then characterized using a quadrupole time-of-flight tandem mass spectrometer in negative-ion mode and annotated based on [M-H]⁻ and fragmentation patterns. Electronic-structure and thermodynamic calculations based on density functional theory (DFT) were performed to evaluate frontier molecular orbitals and the mechanistic feasibility of the common antioxidant pathways. These results indicate that these metabolites can retain, and in some cases exceed the radical-scavenging capacity of the parent molecule. Network pharmacology analysis and molecular docking further suggest that these metabolites potentially engage a substantial portion of quercetin's core regulatory targets and may contribute to its broader biological effects. Notably, among these metabolites, 2-benzoyl-2-hydroxy-3(2H)-benzofuranones emerged as promise. Explanatorily, time-dependent density functional theory (TD-DFT) analysis further suggested that the formation of successively reactive metabolites may be facilitated by the characteristic excited-state intramolecular proton-transfer mechanism of flavonols. These findings warrant further investigation of oxidation metabolites within quercetin's antioxidant network.
With this status report, we aim to provide a timely snapshot of the protein engineering field as a broad and rapidly advancing discipline that integrates computational, molecular biology, structure-guided, evolutionary, and synthetic approaches to create new and improved proteins with tailored structures and useful functions. The report is organized into eight thematic areas spanning core methodologies and major application domains, including enzymes, therapeutics, detection, synthetic biology, and materials. Contributions from experts across these areas highlight both the historical foundations and recent advances in their respective fields, with particular emphasis on the growing influence of machine learning and artificial intelligence-based methods. Emerging from this broad overview is a central message: protein engineering appears to be entering a golden age, defined by a rapidly accelerating pace of progress, even as significant challenges in design, screening, and real-world application remain. Looking ahead, the continued integration of computational and experimental strategies is poised to further accelerate the impact of protein engineering across an expanding range of economically and societally important sectors, from therapeutics and molecular imaging to diagnostics, plastic recycling, and industrial chemistry.
Reducing staple-food digestibility is an important nutritional target for wheat starch-based products, yet how starch chain architecture regulates gel digestibility remains unclear. In this study, starches from 14 wheat varieties were used to prepare 40% (w/w) gels, and their gel structure, in vitro digestibility, and chain-length evolution during digestion were investigated. The results showed that elevated short-chain amylopectin or long-chain amylose produced gel networks with different macroscopic mechanics but similar local barrier function, yielding comparable digestion rates and lower final digestibility (77.71% and 79.72%, respectively). A high proportion of short-chain amylopectin promoted densely packed A-type double helices through high viscosity and a uniform hydrogen-bonding environment, forming a homogeneous barrier against enzyme diffusion and hydrolysis. In contrast, long-chain amylose more readily reorganized with amylopectin into a stable semicrystalline continuous network, whose resistance also arose from dense internal order. The enrichment of DP 24-34 and DP 44-58 chains in digestion residues further indicates that these fractions were major contributors to enzyme resistant structures. DP 24-34 chains favored local ordered lamellae, whereas DP 44-58 chains acted as internal supporting scaffolds. This study provides key approaches for tailoring starch digestibility through molecular design.