Search Results (1,370)

Bioactive peptides (BPs) are widely distributed and exhibit remarkable physiological activities. However, their natural forms are frequently characterized by short half-lives, low membrane permeability, poor stability, and inadequate oral bioavailability, which severely limit their applications in the food, pharmaceutical, and biomaterial fields. Therefore, modification and engineering of natural BPs are essential to surmount these inherent limitations. Synthetic biology-based modification strategies, including amino acid substitution, sequence truncation and hybridization, side-chain functionalization, and main-chain/side-chain integration, are comprehensively summarized in this review. Chemical modification strategies, such as terminal modification, cyclization, backbone modification, polymer conjugation, lipidation, and glycosylation, are also discussed, with particular attention to their advantages, potential drawbacks, and practical limitations. Based on 122 studies identified through systematic literature searches across major scientific databases, this review also discusses the current challenges and future trends in BP modification, providing theoretical guidance and innovative insights for the further development and enhanced utilization of BPs. Full article

Monoubiquitination is a significant post-translational modification that plays a pivotal role in various biological processes. Chemical monoubiquitination holds significant value in investigating the functional implications of site-specific ubiquitination on target proteins. Despite all progress made in this area, conventional enzymatic methods so far rely largely on high yields of substrate proteins and the removal of tags to prevent non-specific ubiquitin binding, which poses substantial challenges for low-solubility proteins. Here, an optimized chemical monoubiquitination system that facilitates precise, site-specific ubiquitination of low-solubility target protein was developed using SSPP as an example. A cysteine-free GST tag (GST^4CS) was engineered, and a flexible (GGGGS)₃ linker was incorporated to mitigate steric hindrance and enhance the solubility of GST-SSPP fusion protein, resulting in a 2.5-fold increase in purification yield. Successful monoubiquitination of SSPP at the position of lysine 305 was achieved using disulfide-mediated conjugation, as proven via SDS-PAGE and Western blotting. Moreover, the phosphatase assay showed that monoubiquitination at residue C305 of the mutated SSPP significantly decreased its phosphatase activity. This system eliminates tag interference and enhances compatibility with low-solubility targets, providing a robust platform for functional studies of plant protein ubiquitination. Full article

Polysaccharide–peptide conjugates are modular biomaterials that combine hydrated carbohydrate frameworks with peptide domains capable of mediating molecular recognition, degradability, antimicrobial activity, and biological signaling. In this review, we discuss how covalent, bioorthogonal, and enzymatic conjugation strategies regulate peptide density, orientation, accessibility, and stability within polysaccharide-based matrices. These chemical choices are analyzed in relation to network architecture, viscoelasticity, ligand presentation, degradation behavior, and cell–material interactions. Representative systems based on hyaluronic acid, alginate, chitosan, dextran, cellulose, and glycosaminoglycans are examined to illustrate how peptide functionalization can transform otherwise passive scaffolds into adhesive, degradable, antimicrobial, or therapeutically responsive platforms. We further highlight dynamic and enzyme-responsive materials, localized drug delivery systems, antimicrobial coatings, and antibiofilm interfaces as key biomedical applications of these conjugates. The review also addresses translational challenges associated with structural heterogeneity, stability, immunogenicity, sterilization, batch-to-batch reproducibility, and clinical feasibility. Taken together, the evidence discussed here indicates that the performance of polysaccharide–peptide conjugates depends on reproducible structure–function relationships linking conjugation chemistry, macromolecular architecture, and biological activity under application-relevant conditions. Full article

Lead (Pb) induces oxidative stress, inflammation, and hepatorenal injury. We evaluated whether fenugreek (Trigonella foenum-graecum) seed powder (200 mg/kg) protects against subchronic Pb-acetate exposure in male albino mice. Sixty mice were randomized to six groups (n = 10): control (G1), fenugreek-only (G2), Pb 150 mg/kg (G3), and three co-exposure groups receiving fenugreek with Pb at 50, 100, and 150 mg/kg (G4–G6), gavaged daily for 8 weeks. LC–DAD–ESI–MS/MS of the seed batch tentatively identified 32 metabolites, dominated by flavonoid C-glycosides, luteolin dihydrogalloyl-glucosyl-pentosyl glucoside (15.90%), vicenin-3 (14.46%), vicenin-2 (9.66%), vicenin-1 (8.80%), kaempferol 7-O-rhamnosyl-glucoside (8.71%), with additional acylated phenolic conjugates. Pb exposure (G3) significantly reduced growth and intake, elevated serum ALT, AST, ALP, urea, and creatinine, raised blood Pb, and produced hepatic necrosis, vacuolation, and inflammation. Molecularly, Pb upregulated Nrf2, HO-1, SCD-1, TNF-α, and IL-6 and suppressed SOD-3. Fenugreek co-treatment attenuated all these changes across the three Pb doses, with greatest effect at the lowest Pb load (G4). Notably, fenugreek co-treatment reduced rather than further increased Nrf2 and HO-1 expression relative to Pb alone, a pattern most consistent with lowering the upstream oxidative stimulus rather than direct induction of these pathways. The seed’s polyphenolic profile—rich in vicenin-type C-glycosides and luteolin and kaempferol derivatives—offers a plausible chemical basis for the antioxidant, anti-inflammatory, and modest Pb-lowering effects observed; however, because whole seed powder was administered and metabolite identifications are tentative, these structure–activity relationships are presented as hypotheses for future bioactivity-guided fractionation rather than as demonstrated mechanisms. These preclinical findings support further investigation of fenugreek as a candidate dietary adjunct against environmental Pb exposure, contingent on protein-level validation, pharmacokinetic characterization, benchmarking against a standard chelator, and bioactivity-guided fractionation. Full article

Qualitative and quantitative analysis of complex mixtures and structure elucidation is generally impeded by the intrinsic complexity of the NMR spectra and the extensive signal overlap. The conventional approach to characterizing individual metabolites from complex crude extracts of natural products relies on multistep separation workflows employing diverse liquid chromatographic approaches and/or hyphenated techniques, which combine online integration of NMR with separation methods and other forms of spectroscopy. In recent decades, considerable efforts have been devoted to NMR applications in crude extracts without previous separation and isolation of the individual analytes. We present herein a critical overview of several NMR applications using chemical shift ranges of common organic functional groups, which can provide significant resolution advantages under specific experimental conditions. Particular emphasis is placed on: (i) characteristic chemical shift regions of strongly deshielded phenol OH groups, aldehyde CHO groups, hydroperoxide C-O-O-H groups and olefinic protons in conjugated double bonds; (ii) the advantages of using ¹³C chemical shift ranges through 2D ¹H-¹³C HSQC and HMBC experiments of strongly deshielded phenol OH groups, aldehyde CHO groups, hydroperoxide groups, conjugated double bonds, and deshielded aliphatic CH groups; (iii) selective 1D NMR-spin chromatography techniques (1D TOCSY, 1D NOE); (iv) multiple suppression of strong resonances for minor analyte identification and (v) band-selective excitation techniques for minor analyte identification and quantification. The complementary contributions of statistical heterospectroscopy and computational chemical shift prediction are also considered, together with a brief assessment of the NMR experimental parameters and performance characteristics. Full article

Antisense oligonucleotides (ASOs) are a class of nucleic acid therapeutics that modulate gene expression through diverse mechanisms. Since their initial demonstration in inhibiting viral genes, advances in medicinal chemistry, pharmacology, and delivery have enabled robust and durable target engagement across multiple tissues. Chemical modifications to the backbone, ribose, and nucleobases have improved nuclease resistance, binding affinity, and pharmacokinetics, while conjugation and delivery technologies have expanded tissue accessibility. Beyond classical RNase H–mediated RNA degradation, ASOs regulate gene expression via splicing modulation, microRNA inhibition, transcriptional activation, and translation modulation, supporting both gene silencing and upregulation strategies. Multiple ASO drugs are now approved, particularly for genetic diseases, with many more in clinical development. This review outlines the evolution of antisense technology, key chemical and delivery innovations, ASO pharmacokinetics and intracellular trafficking, the mechanisms underlying gene regulation, and current clinical applications and future opportunities. Full article

Light-triggered hydrogel systems offer precise spatiotemporal control over drug release, yet most existing approaches require direct chemical conjugation of a photocleavable linker to the payload, which risks compromising bioactivity and limits applicability to structurally diverse molecules. Here, we report a gelatin–poly(ethylene glycol) (PEG) hybrid hydrogel crosslinked via strain-promoted azide–alkyne cycloaddition (SPAAC) click chemistry, in which an o-nitrobenzyl photocleavable (PC) linker is incorporated into the PEG crosslinker arm rather than conjugated to the drug. Acetylated gelatin–azide (AGA) was synthesized by sequential azide functionalization and amine capping of gelatin, and four-arm PEG-PC-DBCO (4armPEG-PC-DBCO) was prepared by coupling a PC DBCO-PEG4-NHS ester to four-arm PEG amine. Successful incorporation of the azide, DBCO, and o-nitrobenzyl moieties was confirmed by FT-IR spectroscopy, ¹H NMR spectroscopy, and UV-Vis spectrophotometry. Hydrogel formation under physiological conditions (PBS, 37 °C) without catalysts or initiators was verified by rheological frequency sweep analysis, which confirmed elastic-dominant behavior (G′ > G″). Upon irradiation at 365 nm, the crosslinker was cleaved, and rapid network dissolution was observed both macroscopically and by in situ time sweep rheology. This platform enables on-demand, UV-selective hydrogel degradation independently of payload identity, providing a versatile foundation for future controlled drug release applications and dynamic, on-demand degradable scaffolds for tissue engineering. Full article

Developing zinc oxide-based nano-bactericides as alternatives to conventional chemical bactericides for controlling rice bacterial diseases has become a major research focus. In this study, ZnO nanoparticles were initially surface-modified and subsequently covalently conjugated with chitooligosaccharide (COS) via imine bonds to get a pH-responsive zinc oxide–chitooligosaccharide (ZnO–COS) delivery system. A series of physicochemical characterizations, including FTIR, UV-vis, XRD, and TGA, confirmed the successful synthesis of ZnO–COS NPs. Building on this foundation, the pH-responsive release behavior, foliar deposition performance, antibacterial activity, and biosafety of the nanoparticles were systematically investigated. The prepared ZnO–COS NPs exhibited pronounced acid-triggered Zn²⁺ release, together with enhanced wettability, spreadability, and retention on rice leaf surfaces, owing to COS incorporation. In both in vitro and in vivo assays against Xanthomonas oryzae pv. oryzae (Xoo), ZnO–COS NPs demonstrated effective antibacterial activity associated with bacterial cell damage and the activation of antioxidant defense responses in plants. Consequently, ZnO–COS NPs achieved a preventive efficacy of 56.0% against rice bacterial blight, surpassing those of ZnO (33.3%) and COS (14.3%). Furthermore, safety assessment confirmed the good biocompatibility of ZnO–COS NPs towards rice seed germination and seedling growth. In summary, the synthesised ZnO–COS NPs integrated pH-responsive release, improved foliar deposition, and enhanced antioxidant capacity of rice, offering a promising strategy for mitigating bacterial diseases in rice. Full article

Symmetry plays a fundamental role in the structural analysis of lattice-based systems, particularly in graphene-like molecular structures. In chemical graph theory, counting independent sets is equivalent to computing the Merrifield–Simmons (M–S) index, a key descriptor of molecular stability in conjugated systems. Most existing exact counting methods rely on regular lattice symmetry, where structural uniformity simplifies computation; however, these approaches are difficult to extend to irregular graphs, where symmetry breaking introduces non-local dependencies and increases computational complexity. This paper proposes an asymmetry-aware algorithmic framework based on Hamiltonian traversals and a traversal-induced pathwidth parameter $w\left(G\right)$, defined through backward dependencies. Our method organizes non-local adjacencies into a bounded set of structured constraints, enabling a dynamic programming scheme over a reduced state space. The resulting algorithm runs in time $\mathcal{O}\left(2^{w\left(G\right)}·\mathrm{poly}\left(n\right)\right)$ and is fixed-parameter tractable with respect to $w\left(G\right)$. The results demonstrate that asymmetry-aware traversal strategies enable efficient exact enumeration in irregular mesh graph families, providing a robust computational framework for analyzing molecular descriptors in graphene-based structures with topological defects such as Stone–Wales transformations. Full article

Background: Gynecological cancers include collections of cancers with diverse cellular and molecular characteristics that often develop drug resistance, making them treatment-resistant. Biomolecule–drug conjugates (BDCs), especially antibody–drug conjugates (ADCs), have revolutionized the targeted therapy of cancer; however, the creation of these entities has so far been achieved by empirical, resource-intensive design methods. Objective: The aim of this review is to critically analyze how AI can be used for the rational design and optimization of high-affinity BDCs for gynecological cancer treatment. Methods and discussion: Recent advances in machine learning (ML)- and deep learning (DL)-based methods to predict biomolecule-target binding affinity, structural compatibility, linker stability, payload selection, trafficking in the cell, and biomolecule resistance mechanisms are summarized. The review also explores the possibilities for incorporation of structural, chemical, biological, and multi-omics data to enhance specificity, efficacy, and safety of conjugates. Besides antibody-based systems, AI-assisted design approaches with peptides, aptamers, and hybrid biomolecular systems are also included. This review also highlights parameters and experimental/numerical validation restrictions related to data quality, interpretability of models, regulatory aspects, etc. Conclusions: AI-based conjugate engineering is increasingly moving BDC development from a largely ‘trial and error’ approach to a more predictive and data-driven approach. While there are still challenges to be addressed in terms of translations and validations, the potential of AI approaches in the field of precision oncology and the development of more personalized treatment is promising in the context of gynecological cancers. Full article

Extracellular vesicles (EVs) have attracted considerable attention as natural nanocarriers for immune modulation owing to their intrinsic biocompatibility, nanoscale size, and capacity to transport diverse bioactive cargos. In inflammatory diseases, EV-based therapeutics provide unique opportunities to regulate dysregulated immune responses; however, their clinical translation remains constrained by limited cell-specific targeting efficiency and uncontrolled biodistribution. Achieving precise and selective delivery to immune cells and other inflammation-associated cellular components within diseased tissues is therefore critical for maximizing therapeutic efficacy while minimizing off-target effects. This review comprehensively summarizes recent advances in cell-specific EV-targeting strategies for immune modulation in inflammatory diseases, with a particular focus on active targeting approaches enabled by EV surface engineering. A range of targeting ligands, including antibodies, peptides, aptamers, glycans, and membrane proteins, is discussed in the context of enhancing selective interactions between EVs and specific immune cell subsets. Special emphasis is placed on cell-directed targeting strategies toward diverse immune cell populations, including macrophages and T cells, highlighting how rational control of EV–cell interactions can be utilized to reprogram immune phenotypes, suppress pathological inflammation, and restore immune homeostasis. Accordingly, this review integrates recent progress in cell-specific EV targeting into a coherent conceptual framework, which may assist researchers in the rational design of EV-based immunomodulatory therapeutics. Full article

Synthesis of bifunctional cytisine–squaramide derivatives bearing a single amino acid moiety has revealed an unexpected and intriguing chemical challenge. During modification of cytisine squaramates with α-amino acids, base-sensitive amido esters readily underwent hydrolysis, forming poorly soluble amido-acid side products that resisted standard purification and initially obscured their identity. Persistent observation of these elusive precipitates prompted a deliberate co-crystallization approach, which unambiguously revealed their supramolecular nature using single-crystal X-ray diffraction. With this insight, optimized purification strategies allowed isolation of analytically pure Cyt-SQ-OH and its derivatives, which were characterized by complementary spectroscopic techniques, X-ray crystallography and computational studies. Furthermore, the DFT-optimized parameters of all compounds were determined, providing additional insight into their structural and electronic properties. This work highlights the interplay between reactivity, solubility, and supramolecular assembly in cytisine–squaramide-amino acid hybrids, providing a robust platform for future exploration of multifunctional conjugates with potential applications in medicinal chemistry, molecular recognition, and materials science. Full article

Research on oxazolones, particularly 4-alkynyloxazolones, has garnered increasing interest due to the presence of an alkynyl group, which facilitates molecular conjugation and enables diverse chemical modifications. In this study, three representative 4-alkynyloxazolone derivatives (L1–L3) were synthesized and structurally characterized through single-crystal X-ray diffraction and computational analysis to obtain a reliable structure of L1–L3 to subsequently predict in silico interactions with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein. The crystallographic results revealed high molecular planarity and multifurcated hydrogen bonding. Considering the obtained crystallographic structure, theoretical descriptors such as HOMO–LUMO energy gaps and electrostatic potential maps indicated that these compounds exhibit favorable electronic reactivity, particularly for L3, with favorable drug-like predictions. The lack of methoxy groups in L2 and L3 makes these compounds have lower predicted toxicity parameters than L1. Molecular docking calculations targeting SARS-CoV-2 spike glycoprotein in three different feasible conformations in a biological matrix, i.e., three receptor-binding domains (RBD) in down conformation, two RBD in down and one in up conformation, as well as RBD bound to the human receptor angiotensin-converting enzyme 2 (ACE2), suggested strong binding affinities and specific interactions with the RBD moiety, mainly in the up conformation. Overall, this work integrates crystallographic and computational approaches to establish the structural and in silico evaluation of spike-binding properties of early substituted 4-alkynyloxazolones, suggesting L3 as a candidate for future in vitro antiviral assays. Full article

Proteins with additives, especially in small quantities, are of great interest as a subject of study. Machine learning approaches implemented on Raman spectroscopy data could provide an insight into the chemical structures of such mixtures or conjugates. Although decision tree models could be powerful in solving either classification or regression tasks and could provide accessible predictions, they are prone to overfitting. Ensemble models that implement several decision trees could overcome the determined problem. Five different model types are discussed: RandomForest, GradientBoosting, AdaBoost, Voting, and Stacking. Raman spectroscopy data of whey protein isolates (5 wt.%) with different amounts of hyaluronic acid (0, 0.1, 0.25, and 0.5 wt.%) were used as datasets. In order to generalize the results of the study, WPI samples from three different manufacturers were used. Optimization established that ensembles of 200 decision trees with a maximum depth of four were optimal. The Stacking algorithm, which used RandomForest, GradientBoosting, and AdaBoost as base models with either LogisticRegressor (classification task) or RidgeCV (regression task), was found to be the most efficient in finding differences between the whey protein isolate and its conjugates with hyaluronic acid: specificity of 68.7% and sensitivity of 95.4% (classification task); R² = 0.764 with mean absolute error of 0.068 (regression task). According to the feature importance plots, the Raman bands that were most influential in predicting the results were 1003 cm⁻¹ (phenylalanine, ring breath), 1125 cm⁻¹ (rocking of NH₃⁺), 1206 cm⁻¹ (C–C stretching), 1240 cm⁻¹ (amide III (β-sheet), N–H in-plane bend, C–N stretch), and 1399 cm⁻¹ (aspartic and glutamic acids, C=O stretch of COO–). The findings of this study may contribute to the development of novel methods for quality control and analysis of complex multicomponent systems in various industrial settings. In particular, the ensemble approach can be adapted for monitoring in food processing or as a screening tool in pharmaceutical formulation development. Full article

Fatty acids (FAs) have drawn attention in the field of oncology due to their multifaceted role, not only as structural components of lipid-based delivery systems but also as functional moieties that can enhance the pharmacokinetic and biological behavior of anticancer drugs and, subsequently, their therapeutic performance. Due to their biocompatibility, structural diversity, high affinity for biological membranes, and albumin-binding capacity, FAs can increase drug lipophilicity, membrane permeability, systemic distribution, tissue distribution, and enable controlled enzymatic release. All these properties endorse the development of nanocarriers containing FAs, such as liposomes, lipid nanoparticles (LNPs), self-nanoemulsifying drug delivery systems (SNEDDS), and self-assembling lipidic prodrugs (LAPs). In addition, several FAs, especially polyunsaturated FAs, seem to have a direct anticancer activity by modulating lipid metabolism, oxidative stress, membrane organization, and regulating cell death pathways. This review summarizes the FA conjugation chemistry, the influence of FA on the pharmacokinetics and tumor-targeting capacity of anticancer agents, and the current developments in FA-based cancer treatment strategies, while also covering the biological functions of FA in cell death pathways and cancer metabolism. By integrating medicinal chemistry, nanocarrier design, pharmacokinetic modulation, and tumor lipid biology, this review positions FA-based strategies as a relevant and evolving platform for improving anticancer drug delivery, tumor selectivity, and therapeutic performance. Full article