Search Results (1,067)

Extracellular glutathione (GSH) is degraded on the cell surface, in which the γ-glutamyl residue is removed to generate cysteine–glycine (Cys–Gly) dipeptides that are subsequently transported to the cytoplasm. Carnosine dipeptidase 2 (CNDP2) is a cytoplasmic enzyme that hydrolyzes Cys–Gly and plays an important role in maintaining intracellular cysteine (Cys) homeostasis. CNDP2-mediated hydrolysis of Cys–Gly promotes Cys mobilization and contributes to the replenishment of intracellular GSH levels. CNDP2 is frequently overexpressed in various cancers and has been implicated in tumor cell proliferation and progression. This mechanism may enhance cancer cell survival by causing resistance to oxidative stress, which indicates that CNDP2 is a potential therapeutic target for cancer treatment. Although bestatin (BES) has been identified as a CNDP2 inhibitor, its limited specificity and suboptimal drug-like properties have limited its therapeutic potential. In this study, we performed an in silico screen of a small-molecule compound library and identified KKL-35 as a novel CNDP2-binding molecule. Molecular dynamics (MD) simulations suggested that KKL-35 interacts within the catalytic pocket. Biochemical assays confirmed that it inhibits CNDP2 enzymatic activity, albeit with lower potency compared with BES. Despite its modest intrinsic activity, KKL-35 exhibits favorable physicochemical and pharmacokinetic properties, which are characterized by a low topological polar surface area (TPSA), reduced molecular flexibility, and well-balanced lipophilicity. This positions it as an attractive and tractable starting point for lead optimization. Taken together, these findings establish KKL-35 as a validated CNDP2 inhibitor and a promising lead compound for the development of more selective therapeutics targeting CNDP2-mediated cancer cell metabolism. Full article

Human Epidermal Growth Factor Receptor 2 (HER2) is a key therapeutic target in breast cancer. However, the application of existing anti-HER2 antibody drugs is limited by such issues as large molecular weight and poor stability. In this study, a series of small protein minibinders targeting HER2 domain IV were de novo designed using the RFdiffusion method. Candidate molecules were selected through a combination of ProteinMPNN and AlphaFold2 screening, and their binding capabilities were further evaluated using Escherichia coli surface display coupled with flow cytometry analysis. By integrating molecular dynamics simulations, confocal fluorescence imaging, and isothermal titration calorimetry (ITC) experiments, a highly efficient minibinder (0_703_6) with nanomolar affinity and a smaller molecular size was finally identified. Compared with the existing drug molecules, the identified minibinder exhibited approximately threefold higher affinity and a threefold reduction in molecular size. This study provides strong support for the development of novel, stable, and easily expressible HER2-targeted therapeutic molecules and also offers new insights into the rapid development of robust breast cancer drugs that may serve as ideal alternatives to monoclonal antibodies. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder characterized by insulin resistance, impaired insulin secretion, and chronic hyperglycemia. Recent studies have identified microRNAs (miRNAs), a class of small non-coding RNAs that regulate gene expression at the post-transcriptional level, as modulators of pathways involved in T2DM pathophysiology. Dysregulated miRNA expression has been detected in various samples collected from patients with T2DM, implicating these molecules in disease onset and progression. Methods: We systematically searched PubMed, Scopus, and Web of Science for studies published from the earliest available records to 18 August 2025 using the following Boolean search terms: “miRNA AND gliclazide”, “miRNA AND glibenclamide”, “miRNA AND gliquidone”, “miRNA AND glimepiride”, “mirRNA AND metformin”, “miRNA AND pioglitazone”, “miRNA AND rosiglitazone”, “miRNA AND sitagliptin”, “miRNA AND vildagliptin”, “miRNA AND alogliptin”, “miRNA and saxagliptin”, “miRNA AND linagliptin”, “miRNA AND liraglutide”, “miRNA and dulaglutide”, “miRNA AND semaglutide”, “miRNA AND tirzepatide”, “miRNA AND lixisenatide”, “miRNA AND empagliflozin”, “miRNA AND dapagliflozin”, miRNA AND insulin glargine”, “miRNA AND insulin detemir”, “miRNA AND insulin degludec”, “miRNA AND insulin aspart”, “miRNA AND insulin glulisine”, and “miRNA AND insulin lispro”. Additionally, gray literature was searched in ClinicalTrials.gov, the EU Clinical Trials Register (EudraCT), and the ISRCTN Registry to identify unpublished studies. Studies were eligible for inclusion if they were clinical interventional studies assessing the impact of currently available antidiabetic treatments on miRNA expression. Only articles published in English were considered. The risk of bias was evaluated using the RoB2 (Risk of Bias 2) and ROBINS-I (Risk Of Bias In Non-randomized Studies—of Interventions) tools. Study characteristics and major findings were tabulated. Results: A total of 1263 manuscripts was identified initially. After removing duplicates, 726 articles remained for further screening. Ultimately, 17 manuscripts reporting interventional clinical trials on the effects of antidiabetic treatment on miRNA were included, encompassing a total of 1093 patients. Key findings included treatment-associated changes in miRNA expression and their potential utility for the prediction of clinical outcomes. Conclusions: Current evidence supports the hypothesis that antidiabetic treatments modulate miRNA expression, with some findings showing predictive value for metabolic outcomes. However, the available data remain limited and of low grade of certainty, and further large-scale clinical studies are needed to provide deeper insights into these associations. Full article

Zika virus (ZIKV) caused Zika outbreaks and continues to post threats to public health. ZIKV infection may cause congenital abnormalities during pregnancy and neurological manifestations in adults. The recurrent public health threat of Zika in various geographical areas demonstrates a need for the development of effective therapeutics. Currently, there are no approved therapies for Zika. ZIKV is a single-stranded, positive-sense RNA virus, whose genome encodes three structural proteins and seven non-structural proteins. The surface envelope (E) protein is essential for host–cell recognition and viral entry; therefore, inhibition of E-mediated viral entry is a key strategy underlying antiviral treatments. Here, molecular docking-based virtual screening was used to screen small-molecule compound libraries to identify potential ZIKV entry inhibitors. Among the compounds identified, Pyrimidine-Der1 exhibited efficient inhibition of reporter ZIKV infection. The microscale thermophoresis assay confirmed its binding with the ZIKV E protein. This compound has effective inhibition of authentic ZIKV infection in a plaque inhibition assay against R103451, PAN2016, and FLR human strains (IC₅₀: ~3–5 μM). Additionally, it efficiently inhibited ZIKV infection at viral entry and fusion steps of the virus life cycle in a time-of-addition assay. Overall, Pyrimidine-Der1 is a promising ZIKV entry inhibitor, warranting further optimization and evaluation. Full article

Background: Photostability assessment is a critical component in the development of drug products, particularly for antibody–drug conjugates (ADCs) containing light-sensitive small molecules such as camptothecin (CPT) and its derivatives. ADCs conjugated with CPT derivative payloads often require extensive formulation and drug product development to ensure product stability due to their unique light-induced degradation pathways. In this study, we assessed the photostability of two ADC molecules with a CPT derivative payload (deruxtecan, DXd). Methods: Following light exposure, the stability of ADCs was assessed by examining critical quality attributes, such as aggregation and photodegradation products of the antibody, payload, and formulation excipients, using advanced liquid chromatography and mass spectrometry techniques. Results: Our results revealed key degradation pathways, including the formation of high-molecular-weight (HMW) species, payload degradation, and post-translational modifications (PTMs) on amino acid residues in the antibodies. Additionally, the DXd payload amplified the photosensitivity of the formulation solution, leading to histidine degradation in the formulation buffer and subsequent pH changes. To enhance the stability of ADCs for manufacturing and therapeutic use, we developed a robust formulation by systematic buffer screening and a targeted evaluation of selected antioxidant excipients. Further investigations into light conditions revealed that DXd ADCs are particularly sensitive to short-wavelength light. When evaluating the container closure system, it was demonstrated that using amber vials is a viable option for protecting against light-induced degradation. Conclusions: This report outlines a comprehensive strategy to address photo instability in DXd ADC drug product development, focusing on formulation optimization, controlled manufacturing light settings, and the option of using protective containers to ensure product stability. Full article

Selective depression of serpentine remains a major challenge in the flotation of low-grade nickel sulphide ores because serpentine slimes impair concentrate grade and recovery. In this study, four structurally related micromolecular depressants bearing amino and phosphonic functionalities were designed, synthesized and systematically evaluated. Micro-flotation screening (depressant range: 0–20 mg·L⁻¹) and bench-scale tests identified an operational optimum near pH 9 and a reagent dosage of ≈18 mg·L⁻¹; potassium butyl xanthate (PBX) was used as a collector and methyl isobutyl carbinol (MIBC) as a frother. Phosphonate-containing molecules (PMIDA and GLY) delivered the largest gains in pentlandite recovery and concentrate selectivity compared with carboxylate analogues and a benchmark depressant. Mechanistic studies (zeta potential, adsorption isotherms, FT-IR, and XPS) indicated that selective adsorption of amino and phosphonate groups on serpentine occurs via coordination with surface Mg sites and by altering the electrical double layer. The DLVO modelling showed that these reagents generate an increased repulsive barrier, mitigating slime coating and entrainment. Contact-angle measurements confirmed selective hydrophilization of serpentine while pentlandite remained hydrophobic. These findings demonstrate that incorporating targeted phosphonate chelation into small-molecule depressants is an effective strategy to control serpentine interference and to enhance flotation performance. Full article

The ongoing challenge of doping in sports has triggered the adoption of advanced scientific strategies for the detection and prevention of doping abuse. This review examines the potential of integrating metabolomics aided by artificial intelligence (AI) and machine learning (ML) for profiling small-molecule metabolites across biological systems to advance anti-doping efforts. While traditional targeted detection methods serve a primarily forensic role—providing legally defensible evidence by directly identifying prohibited substances—metabolomics offers complementary insights by revealing both exogenous compounds and endogenous physiological alterations that may persist beyond direct drug detection windows, rather than serving as an alternative to routine forensic testing. High-throughput platforms such as UHPLC-HRMS and NMR, coupled with targeted and untargeted metabolomic workflows, can provide comprehensive datasets that help discriminate between doped and clean athlete profiles. However, the complexity and dimensionality of these datasets necessitate sophisticated computational tools. ML algorithms, including supervised models like XGBoost and multi-layer perceptrons, and unsupervised methods such as clustering and dimensionality reduction, enable robust pattern recognition, classification, and anomaly detection. These approaches enhance both the sensitivity and specificity of diagnostic screening and optimize resource allocation. Case studies illustrate the value of integrating metabolomics and ML—for example, detecting recombinant human erythropoietin (r-HuEPO) use via indirect blood markers and uncovering testosterone and corticosteroid abuse with extended detection windows. Future progress will rely on interdisciplinary collaboration, open-access data infrastructure, and continuous methodological innovation to fully realize the complementary role of these technologies in supporting fair play and athlete well-being. Full article

Background/Objective: Oncogenic tyrosine kinases (TKs) such as ALK and SRC promote cancer progression, but their effects on metabolic enzymes are still not well understood. This study examines how TK signaling regulates inosine monophosphate dehydrogenase 2 (IMPDH2), a rate-limiting enzyme in purine biosynthesis, and assesses its potential as a therapeutic target. Methods: Phosphoproteomic screening and in vitro kinase assays were used to identify phosphorylation sites on IMPDH2. Lipid-binding assays explored the role of phosphatidylinositol 3-phosphate (PI3P) in IMPDH2 regulation. Structure-based virtual screening discovered small-molecule allosteric inhibitors, which were tested in lymphoma cell models, including ALK and BTK-inhibitor resistant lines. Results: Here, we identify Inosine monophosphate dehydrogenase-2 (IMPDH2), a rate-limiting enzyme in purine biosynthesis, as a novel substrate of ALK and SRC. We show that phosphorylation at the conserved Y233 residue within the allosteric domain enhances IMPDH2 activity, linking TK signaling to metabolic reprogramming in cancer cells. We further identify PI3P as a natural lipid inhibitor that binds IMPDH2 and suppresses its enzymatic function. Using structure-based virtual screening, we developed Comp-10, a first-in-class allosteric IMPDH inhibitor. Unlike classical active-site inhibitors such as mycophenolic acid (MPA), Comp-10 decreases IMPDH1/2 protein levels, blocks filament (rod/ring) formation, and inhibits the growth of ALK and BTK inhibitor-resistant lymphoma cells. Comp-10 acts post-transcriptionally and avoids compensatory IMPDH upregulation observed with MPA (rod/ring) formation, and inhibited growth in TKI-resistant lymphoma cells. Notably, Comp-10 avoided the compensatory IMPDH upregulation observed with MPA. Conclusion: These findings uncover a novel TK–IMPDH2 signaling axis and provide mechanistic and therapeutic insight into the allosteric regulation of IMPDH2. Comp-10 represents a promising therapeutic candidate for targeting metabolic vulnerabilities in tyrosine kinase driven cancers. Full article

The urgent need to reduce the cost of new drug discovery has led us to create a new, more selective screening method using free chemoinformatics tools to restrict the high failure rates of lead compounds (>90%) during the development process because of the lack of clinical efficacy (40–50%), unmanageable toxicity (30%), and poor drug-like properties (10–15%). Our efforts focused on new molecular entities (NMEs) with reported activity as tyrosine kinase inhibitors (small molecules) as a class of great potential. The criteria for the new method are acceptable Druglikeness, desirable ADME (absorption, distribution, metabolism, and excretion), and low toxicity. After a bibliographic review, we first selected the 29 most promising compounds, always according to the literature, then collected the in silico calculated data from different platforms, and finally processed them together to conclude at 14 compounds meeting the aforementioned criteria. The novelty of the present screening method is that for the evaluation of the compounds for Druglikeness, and ADMET properties (absorption, distribution, metabolism, excretion, and toxicity), the data of the different platforms were used as a whole, rather than the results of each platform individually. Additionally, we validated our new consensus-based method by comparing the final in silico results with the experimental values of FDA (Food and Drug Administration)-approved tyrosine kinase drugs. Using inferential statistics of 39 FDA-approved tyrosine kinase drugs obtained after applying our method, we delineated the intervals of the desired values of the physicochemical properties of future active compounds. Finally, molecular docking studies enhance the credibility of the applied method as an identification tool of Druglikeness. Full article

Background: Angiogenesis, the physiological process by which new blood vessels originate from pre-existing ones, can be triggered by tumor cells to promote the growth, survival, and progression of cancer. Malignant tumors require a constant blood supply to meet their needs for oxygen and nutrients, making angiogenesis a key process in tumor development. Its pathologic role is caused by the dysregulation of signaling pathways, particularly those involving VEGFR-2, a key mediator of angiogenesis, and the K-RAS G12C mutant, a promoter of VEGF expression. Given their critical involvement in tumor progression, these targets represent promising candidates for new cancer therapies. Methods and Results: In this study, we applied an in silico hybrid and hierarchical virtual screening approach to identify potential dual VEGFR-2/K-RAS G12C inhibitors with anticancer and antiangiogenic properties. To this end, we screened the National Cancer Institute (NCI) database through ADME filtering tools. The refined dataset was then submitted to the ligand-based Biotarget Predictor Tool (BPT) in a multitarget mode. Subsequently, structure-based analysis, including molecular docking studies on VEGFR and K-RAS G12C, was performed to investigate the interactions of the most promising small molecules with both targets. Conclusions: Finally, the molecular dynamics simulations suggested compound 737734 as a promising small molecule with high stability in complex with both VEGFR-2 and K-RAS G12C, highlighting its potential as a dual-target inhibitor for cancer therapy. Full article

The need for prostate cancer (PCa)-specific biomarkers that enable more accurate detection of the disease and better prediction of tumor aggressiveness remains ongoing due to the low cancer specificity of PSA screening. Several potential mRNA markers for diagnosing PCa, in tissue and urine, have been reported in the literature. In this study, we aim to explore the potential of selected prostate-specific molecules and transcripts contained in small extracellular vesicles (sEVs) in semen to predict PCa risk reclassification for patients with moderately elevated PSA levels—a clinical scenario where identifying truly non-invasive biomarkers is especially critical. RT-qPCR analysis in semen sEVs successfully showed differential expression of KLK3 and PCA3 genes between PCa and healthy controls, whereas CREB3L4, CCNQ and DUSP23 levels were related to the severity or degree of PCa affectation. Our findings also present strong evidence that classifiers based on combined long transcript levels in semen sEVs serve as effective biomarkers. They can be used alone or in combination with blood PSA and/or semen citric acid levels to improve the diagnosis of PCa and assess its severity and disease progression with high accuracy. This strategy would allow a more comprehensive assessment, increase prognostic accuracy, and facilitate accurate clinical decision-making in the management of PCa. Full article

Mechanistically, OPs inhibit acetylcholinesterase (AChE), an enzyme that terminates cholinergic transmission, triggering a sustained activation of acetylcholine receptors. A component of the treatment for OP intoxication is oximes as AChE reactivators. However, oximes may not be efficacious and could worsen OP effects. Further, dealkylation of the AChE-OP adducts prevents oxime reactivation. Therefore, other approaches are needed to rescue AChE activity. We propose that replacing aged extracellular AChE with active intracellular enzymes may be an effective approach. Thus, molecular screening was used to identify small molecules that could displace aged AChE. C2C12 myoblasts were treated with 20 μM of diisopropylfluorophosphate (DFP) for one hour, followed by a drug panel. AChE activity and surface abundance were measured after 6 h. From the chemical screen, a promising hit, Pz-1 (a tyrosine kinase inhibitor), was identified, which decreased surface AChE on DFP-exposed C2C12 myoblasts in a dose-dependent manner without impacting viability. Additionally, AChE presence and activity were recovered after washing and supplementing the media with 100 nM of acetylcholine. Biochemically, Pz-1 inhibits muscle-specific protein kinase (MuSK), a kinase that interacts with AChE. These results suggest that altering MuSK activity may disrupt protein–protein interactions, destabilizing AChE, which may lead to the discovery of new countermeasures for OP exposures. Full article

Nucleic acid aptamers are single-stranded DNA or RNA molecules that can bind to a target with high specificity and affinity, as screened by the Systematic Evolution of Ligands by Exponential Enrichment (SELEX). In recent years, SELEX technologies have been significantly advanced for the screening of aptamers for a variety of target molecules, cells, and even bacteria and viruses. By integrating recent advances of emerging technologies with SELEX, novel screening technologies for nucleic acid aptamers have emerged with improved screening efficiency, reduced production costs and enhanced aptamer performance for a wide range of applications in medical diagnostics, drug delivery, and environmental monitoring. Aptasensors utilize aptamers to detect a wide range of analytes, allowing for the accurate identification and determination of small molecules, proteins, and even whole cells with remarkable specificity and sensitivity. Further optimization of the aptasensor can be achieved by aptamer truncation, which not only maintains the high specificity and affinity of the aptamer binding with the target analytes, but also reduces the manufacturing cost. Predictive models also demonstrate the powerful capability of determination of the minimal functional sequences by simulation of aptamer–target interaction processes, thus effectively shortening the aptamer screening procedure and reducing the production costs. This paper summarizes the research progress of protein-targeted aptamer screening in recent years, introduces several typical aptasensors at present, discusses the optimization methods of aptasensors by combining efficient SELEX with advanced predictive algorithms or post-SELEX processes, as well as the challenges and opportunities faced by aptasensors. Full article

Introduction: Tumor necrosis factor-α (TNF-α) is a key regulator of inflammatory responses, and its biological activity is dependent on proteolytic processing by the tumor necrosis factor-α-converting enzyme (TACE), also known as ADAM17. Aberrant TACE activity has been associated with various inflammatory and immune-mediated diseases, positioning it as a compelling target for therapeutic intervention. Methods: While our previous study explored TACE inhibition via repositioned FDA-approved drugs, the present study aims to examine previously untested chemical scaffolds from the Enamine compound library, seeking first-in-class TACE inhibitors. We employed an integrated in silico workflow that combined ligand-based virtual screening using a graph convolutional network (GCN) model trained on known TACE inhibitors with structure-based methodologies, including molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. Results: Several enamine-derived compounds demonstrated strong predicted inhibitory potential, favorable docking scores, and stable interactions with the TACE active site. Among them, Z1459964184, Z2242870510, and Z1450394746 emerged as lead candidates based on their highly stable 300 ns RMSD and robust hydrogen bonding profile as compared to the reference compound BMS-561392. Conclusions: This study highlights the utilization of deep learning-driven screening combined with extended 300 ns molecular simulations to identify novel small-molecule scaffolds for TACE inhibition and supports further exploration of these hits as potential anti-inflammatory therapeutics. Full article

iPSCs and their derivatives are used to investigate the molecular genetic mechanisms of human diseases, to identify therapeutic targets, and to screen for small molecules. Combining technologies for generating patient-specific iPSC lines and genome editing allows us to create cell models with unique characteristics. We obtained and characterized three iPSC lines by reprogramming peripheral blood mononuclear cells of a patient with Huntington’s disease (HD) using episomal vectors encoding Yamanaka factors. iPSC lines expressed pluripotency marker genes, had normal karyotypes and were capable of differentiating into all three germ layers. The obtained iPSC lines are useful for modeling disease progression in vitro and studying pathological mechanisms of HD, such as ER stress. A transgene of genetically encoded biosensor XBP1-TagRFP was introduced into the iPSCs to visualize ER stress state of cells. The study demonstrated that iPSC-derived medium spiny neurons develop ER stress, though the IRE1-mediated pathway does not seem to be involved in the process. Full article