Journal of pharmaceutical analysis最新文献

Therapeutic monoclonal antibodies (mAbs) have garnered significant attention for their efficacy in treating a variety of diseases. However, some candidate antibodies exhibit non-specific binding to off-target proteins or other biomolecules, leading to high polyreactivity, which can compromise therapeutic efficacy and cause other complications, thereby reducing the approval rate of antibody drug candidates. Therefore, predicting the polyreactivity risk of therapeutic mAbs at an early stage of development is crucial. In this study, we fine-tuned six pre-trained protein language models (PLMs) to predict the polyreactivity of antibody sequences. The most effective model, named PolyXpert, demonstrated a sensitivity (SN) of 90.10%, specificity (SP) of 90.08%, accuracy (ACC) of 90.10%, F1-score of 0.9301, Matthews correlation coefficient (MCC) of 0.7654, and an area under curve (AUC) of 0.9672 on the external independent test dataset. These results suggest its potential as a valuable in-silico tool for assessing antibody polyreactivity and for selecting superior therapeutic mAb candidates for clinical development. Furthermore, we demonstrated that fine-tuned language model classifiers exhibit enhanced prediction robustness compared with classifiers trained on pre-trained model embeddings. PolyXpert can be easily available at https://github.com/zzyywww/PolyXpert.

Rheumatoid arthritis (RA) is a systemic autoimmune condition that leads to chronic arthritis, disability, and reduced lifespan. Current therapies show limited effectiveness and often cause severe side effects, with up to 50% of patients discontinuing disease-modifying antirheumatic drugs (DMARDs) due to unsatisfactory outcomes. Natural bioactive compounds (NBCs), such as glycosides, alkaloids, terpenoids, flavonoids, polyphenols, and coumarins, have gained attention for their immunomodulatory and anti-inflammatory properties. However, challenges like poor solubility, high dosage requirements, short action duration, and low tissue specificity hinder their clinical use. Nanoparticle (NP)-based delivery systems, including lipid NPs (LNPs), polymer carriers, and inorganic nanocarriers, have been designed to address these challenges through passive, active, and stimuli-responsive strategies. NBC-loaded NPs target immune dysfunction, synovial hyperplasia, bone destruction, angiogenesis, inflammation, and oxidative stress (OS) in RA. This article highlights recent advancements in NBCs for RA treatment, nanoformulation design, and targeted mechanisms, while addressing challenges and future directions in this field. The integration of cutting-edge nanotechnology has demonstrated significant potential to overcome traditional barriers such as low bioavailability and off-target effects through intelligent NPs design. Future research should enhance artificial intelligence (AI)-driven modeling to predict drug-nanocarrier interactions, develop biomarker frameworks for precision nanomedicine, and optimize RA management.

Diabetic foot ulcer (DFU) is an increasing global burden due to the rising prevalence of diabetes, and no specific pharmacological targets or satisfactory drugs are currently available for this devastating ailment. In this study, naringenin (NAR) was found to accelerate diabetic wound healing in diabetic C57BL/6J wild-type (WT) mice by reducing oxidative stress, as assessed through histological assay. NAR also alleviated the inhibition of proliferation, inflammation, cell senescence, and apoptosis in HaCaT cells induced by high glucose (HG). Mechanistically, the beneficial effects of NAR on wound healing are dependent on the E3 ubiquitin-protein ligase parkin (Parkin/PRKN/Prkn). NAR upregulated the expression level of Parkin and promoted its mitochondrial translocation, thereby activating Parkin-mediated mitophagy and maintaining mitochondrial quality control (MQC). Moreover, the wound healing-promoting effects of NAR were significantly diminished in Parkin knockdown HaCaT cells and Prkn knockout (Prkn ^-/-) DFU mice. Inhibition of NAR binding to estrogen receptors (ERs) using tamoxifen (TAM) abolished the protective effects of NAR in HG-induced HaCaT cells. The luciferase reporter assay confirmed that NAR enhanced ERs binding to the estrogen response element (ERE), thereby upregulating Parkin transcription. Additionally, the cellular thermal shift assay (CETSA) revealed that NAR specifically bound to ERα. In conclusion, NAR promoted DFU wound healing by enhancing Parkin-mediated mitophagy via binding to ERα, highlighting its potential as a promising therapeutic candidate.

A supramolecular system of active pharmaceutical ingredients (APIs) can modify the physicochemical properties and enhance the synergistic efficacy of their components; however, the relevant underlying mechanisms in vivo remain unclear. This study employed a metabolomics-driven approach, combined with biological validation, to investigate the synergistic mechanisms of API-based supramolecular systems. Metabolic dysfunction exacerbates insulin resistance and obesity, contributing to hepatic steatosis and cardiac hypertrophy. A novel sodium-dependent glucose transporter 2 (SGLT-2)/peroxisome proliferator-activated receptor-γ (PPAR-γ) dual receptor (dapagliflozin-pioglitazone (DAP-PIO)) supramolecular system was selected as the model to explore the synergistic mechanism involved in the treatment of metabolic dysfunctions, diabetes and obesity. First, metabolomics analyses were performed to compare the effects of a simple physical mixture (PM) of DAP and PIO with the DAP-PIO supramolecular system after absorption into the bloodstream. The results demonstrated significant differences, with the supramolecular system activating the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) and adenosine monophosphate-activated protein kinase (AMPK) signaling pathways. Ceramide (Cer), a key metabolite in sphingolipid metabolism, emerged as a critical mediator. Subsequently, the mechanisms underlying the DAP-PIO supramolecular system's hypoglycemic effects and its ability to ameliorate hepatic steatosis and myocardial hypertrophy by reducing insulin resistance were evaluated and confirmed. These findings provide an innovative strategy for developing SGLT-2/PPAR-γ dual-receptor supramolecular systems to enhance the therapeutic outcomes for diabetes and obesity.

Drug-drug interactions (DDI) are a critical concern in drug development and clinical practice. A new molecular entity often requires numerous clinical DDI studies to assess potential risks in humans, which involves significant time, cost, and risk to healthy study participants. Consequently, there is growing interest in innovative techniques to improve the prediction of transporter-mediated DDI. Researchers in this field have focused on identifying endogenous molecules as biomarkers of transporter function. The development of biomarkers is notably more complex than that of exogenous drugs. Owing to their inherent selectivity, sensitivity, and ability to provide absolute quantification, liquid chromatography-mass spectrometry (LC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) are increasingly being employed for the quantitative investigation of new biomarkers. This review article presents recently developed bioanalytical approaches using LC-MS/MS for putative transporter biomarkers identified to date. Additionally, we summarize the published baseline endogenous levels of these potential biomarkers in a biological matrix to suggest a set of reference values for future research, thereby minimizing errors in biomarker-related data analyses or calculations.

Mesoporous carbon nanoparticles (MCNs) have received considerable attention for biomedical applications due to their unique structural features, including high specific surface area, adjustable pore size, and remarkable biocompatibility. These properties have addressed key challenges such as inefficiencies in drug loading and release, minimizing the side effects associated with conventional treatments. In this review, the classification and the research progress of MCNs are summarized firstly, the preparation and modification techniques to enhance their functionality and properties are further reviewed, the main physicochemical properties are introduced as well, highlighting their contributions to MCNs in applications. In addition, the biomedical applications of MCNs are emphasized, including tumor therapy, tumor theranostics, antibacterial, delivery of active molecules and biological detection. Finally, the prospects and challenges of clinical application based on MCNs are analyzed to provide an effective reference and lay the foundation for further research.

Due to its high sensitivity and non-destructive nature, Raman spectroscopy has become an essential analytical tool in biopharmaceutical analysis and drug development. Despite of the computational demands, data requirements, or ethical considerations, artificial intelligence (AI) and particularly deep learning algorithms has further advanced Raman spectroscopy by enhancing data processing, feature extraction, and model optimization, which not only improves the accuracy and efficiency of Raman spectroscopy detection, but also greatly expands its range of application. AI-guided Raman spectroscopy has numerous applications in biomedicine, including characterizing drug structures, analyzing drug forms, controlling drug quality, identifying components, and studying drug-biomolecule interactions. AI-guided Raman spectroscopy has also revolutionized biomedical research and clinical diagnostics, particularly in disease early diagnosis and treatment optimization. Therefore, AI methods are crucial to advancing Raman spectroscopy in biopharmaceutical research and clinical diagnostics, offering new perspectives and tools for disease treatment and pharmaceutical process control. In summary, integrating AI and Raman spectroscopy in biomedicine has significantly improved analytical capabilities, offering innovative approaches for research and clinical applications.

Liraglutide (Lira), a glucagon-like peptide-1 (GLP-1) receptor agonist approved for diabetes and obesity, has shown significant potential in treating metabolic dysfunction-associated steatotic liver disease (MASLD). However, its systematic molecular regulation and mechanisms remain underexplored. In this study, a mouse model of MASLD was developed using a high-fat diet (HFD), followed by Lira administration. Proteomics and glycoproteomics were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS), while potential molecular target analysis was conducted via quantitative real-time polymerase chain reaction (qPCR) and Western blotting. Our results revealed that Lira treatment significantly reduced liver weight and serum markers, including alanine aminotransferase (ALT) and others, with glycosylation changes playing a more significant role than overall protein expression. The glycoproteome identified 255 independent glycosylation sites, emphasizing the impact of Lira on amino acid, carbohydrate metabolism, and ferroptosis. Simultaneously, proteomic analysis highlighted its effects on lipid metabolism and fibrosis pathways. 21 signature molecules, including 7 proteins and 14 N-glycosylation sites (N-glycosites), were identified as potential targets. A Lira hydrogel formulation (Lira@fibrin (Fib) Gel) was developed to extend drug dosing intervals, offering enhanced therapeutic efficacy in managing chronic metabolic diseases. Our study demonstrated the importance of glycosylation regulation in the therapeutic effects of Lira on MASLD, identifying potential molecular targets and advancing its clinical application for MASLD treatment.

Sulfonylation is extensively used to label DNA and RNA, assess their interactions, and quantify components including nucleobases and nucleosides/nucleotides although the sulfonylation sites remain controversial. Here, we systematically investigated the sulfonylation of adenine (ade) and its nucleosides/nucleotides with 5-(dimethylamino)-naphthalene-1-sulfonyl chloride (DNS-Cl), 5-(diethylamino)-naphthalene-1-sulfonyl chloride (DEANS-Cl), and 5-((N,N-diethylleucyl)amino)-naphthalene-1-sulfonyl chloride (DELANS-Cl). Detailed spectral analysis with nuclear magnetic resonance (NMR) spectroscopy and high-resolution mass spectrometry (HRMS) showed similar sulfonylation behaviors among the reagents. For ade, its secondary amine in the imidazole ring (N⁹H) sulfonylated more readily than the exocyclic amino group (N⁶H₂). For adenosine and its nucleotides, the 2'-OH group in the ribosyl moiety was preferably sulfonylated, whereas the 3'-OH was the preferred site for 2'-deoxyadenosine and its nucleotides. Alkylation and amidation of the aromatic amino group in these 5-amino-naphthalene-1-sulfonyl chlorides did not influence the sulfonylation preferences. This offered a reliable approach and comprehensive details of such sites for ade and its nucleosides/nucleotides.

The critical role of protein disequilibrium in driving carcinogenesis has long been recognized. Though several inhibitors of heat shock protein (HSP) family members have entered clinical trials, none of them have been approved for clinical use as a result of inevitable toxicity, leading to the identification of safer therapeutic approaches sharing a similar efficacy relevant and urgent. Through delineating the role of HSP90 inhibitors in arresting cancer hallmarks, this paper identified HSP90 inhibition as an effective therapeutic strategy capable of concomitantly targeting multiple key transformed properties of cancers via modulating cellular proteostasis. Through interrogating intrinsic connections between proteostasis and redox homeostasis, this paper proposed cold atmospheric plasma (CAP) as a possible alternative of HSP90 inhibitors with little adverse effects. This paper extended the therapeutic spectrum of HSP90 inhibitors and CAP to inflammation-driven pathologies including autoimmune diseases, as inflammation is a manifestation of failed proteostasis. These insights may conceptually advance our understandings on the driving force of cancers that can be easily extended to other disorders originated from imbalanced proteostasis and abnormal inflammation. Tools proposed here for inhibiting HSP90 including CAP and its possible synergy with HSP90 inhibitors may shift the current treatment paradigm to a new avenue in oncology and other relevant fields.