Current Drug Targets[JOURNAL]
Sun
200 papers
Extracellular Vesicles from Mesenchymal Stem Cells Alleviate Spinal Cord Injury via the miR-486-5p/PTEN/PI3K/AKT Pathway.
Chen Y, Zhu J, Wang X … +5 more , Xu F, Zhou Y, Zhang X, Wu J, Xu Y
Curr Drug Targets · 2026 Jun · PMID 42381337 · Publisher ↗
INTRODUCTION: Spinal Cord Injury (SCI) is a severe central nervous system disorder with limited effective treatments. Mesenchymal stem cell (MSC)-derived exosomes have emerged as important mediators of intercellular comm...
INTRODUCTION: Spinal Cord Injury (SCI) is a severe central nervous system disorder with limited effective treatments. Mesenchymal stem cell (MSC)-derived exosomes have emerged as important mediators of intercellular communication and carry microRNAs with potential neuroprotective properties. This study aimed to explore the role and underlying mechanism of human umbilical cord MSC (hUMSC)-derived exosomal miR-486-5p in experimental SCI. METHODS: Exosomes were isolated from hUMSCs and characterized by transmission electron microscopy, nanoparticle tracking analysis, and exosomal marker expression. A rat SCI model and an LPS-induced PC12 cell inflammatory injury model were established. Histological injury and apoptosis were assessed by HE staining and TUNEL assay. Inflammatory cytokine levels were measured by ELISA. Cell viability, apoptosis, and gene and protein expression were evaluated using CCK-8 assay, flow cytometry, qPCR, and western blotting. A dual-luciferase reporter assay was performed to validate the interaction between miR-486-5p and PTEN. RESULTS: hUMSC-derived exosomes attenuated spinal cord tissue damage, reduced neuronal apoptosis, and suppressed inflammatory cytokine production in vivo and in vitro. Inhibition of exosomal miR-486-5p partially reversed these protective effects. Mechanistically, miR-486-5p directly targeted the 3'-UTR of PTEN, leading to reduced PTEN expression and enhanced phosphorylation of AKT and mTOR. DISCUSSION: These findings indicate that exosomal miR-486-5p contributes to the regulation of apoptosis- and inflammation-associated molecular events following SCI, primarily through modulation of the PTEN/AKT/mTOR signaling pathway. Given the experimental design, these results should be interpreted as mechanistic insights rather than evidence of functional recovery. CONCLUSION: hUMSC-derived exosomal miR-486-5p alleviates apoptosis and inflammation following SCI by targeting PTEN and activating the AKT/mTOR pathway. These findings provide mechanistic support for the potential application of exosome-based miRNA therapy in SCI.
Improving B-cell Linear Epitope Prediction Multiple Feature Fusion and an Integrated Machine Learning Algorithm.
Rao B, Tang Y, Hu J … +4 more , Alahmadi H, Alqahtani Y, Arif M, Alam T
Curr Drug Targets · 2026 · PMID 42374910 · Publisher ↗
INTRODUCTION: The identification of linear B-Cell epitopes (BCEs) is significantly important for the discovery of drugs, such as antibody production, peptide-based vaccines, and other therapeutics. MATERIALS AND METHODS:...
INTRODUCTION: The identification of linear B-Cell epitopes (BCEs) is significantly important for the discovery of drugs, such as antibody production, peptide-based vaccines, and other therapeutics. MATERIALS AND METHODS: Unlike traditional laboratory-based methods, computational techniques can save cost and time in predicting large-scale BCEs. For this purpose, numerous in-silico methods have been designed to enhance the overall efficacy of BCE prediction. However, research gaps exist for further improvement in the context of using novel feature representations and learning models for BCE prediction. Therefore, in the present study, we aimed to design a novel sequence- based predictor named CoBCEs for screening and discriminating accurate BCEs. The proposed CoBCEs model incorporates the notion of graph-based signature, texture-based, and protein language model (pLM)-based features to sufficiently explore the local and global evolutionary information from protein sequences alone. Then, we fed the fused features, i.e., ProtVec sequence embeddings, Distance-Enhanced Graph (DE-Graph), and term frequency-inverse document frequency (TF-IDF), to an ensemble machine learning classifier. RESULTS: Experimental results of cross-validation and independent tests on several datasets demonstrate that CoBCEs attained superior performance in terms of accuracy, 77.3%, and Matthews correlation coefficient (MCC) of 61.8%, compared with other existing BCE predictors. DISCUSSION: Detailed data analyses show that the major advantage of CoBCEs lies in the combined utilization of graph-based and pLM-based features, which extract more discriminative information from sequences. In the future, we aim to develop a publicly available web server using biological language models for large-scale BCE peptide prediction. CONCLUSION: We believe our proposed approach will offer valuable insights for drug discovery and disease treatment.
Mechanistic Insights into the Inhibition of Plasmodium falciparum DNA Gyrase A by Withanolide Derivatives through Integrated Computational Analysis.
Soren BC, Vastrad SJ, Junied S … +4 more , Srikanth D, Chimalamari A, Mahender Kumar Jayappa BJ, Dasari JB
Curr Drug Targets · 2026 Jun · PMID 42337902 · Publisher ↗
INTRODUCTION: Malaria is a fatal disease affecting millions of people worldwide, primarily due to infection by Plasmodium falciparum. The emergence of multidrug-resistant parasite strains has necessitated the exploration...
INTRODUCTION: Malaria is a fatal disease affecting millions of people worldwide, primarily due to infection by Plasmodium falciparum. The emergence of multidrug-resistant parasite strains has necessitated the exploration of novel therapeutic targets. Plasmodium falciparum DNA gyrase A (pfDNA gyrase A), an essential topoisomerase II that is not present in humans, is a promising antimalarial drug target. This study explores the inhibitory potential of three Withania somnifera withanolide derivatives, D, E, and O, against pfDNA gyrase A. METHODS: An integrated structure-based computational analysis was conducted to explore the inhibitory potential of three withanolides (D, E, and O) against pfDNA gyrase A. Molecular docking, Molecular Dynamics (MD) simulations, and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy calculations were performed. Pharmacokinetic properties were analysed using SWISS ADME and pkCSM tools. RESULTS: Molecular docking revealed high binding affinities for withanolide D (-9.14kcal/mol), E (-9.73kcal/mol), and O (-9.00kcal/mol), with interactions mediated through key catalytic residues, such as GLU648, LYS647, and TRY590, via hydrogen bonding and hydrophobic contacts. MD simulations confirmed the structural integrity and compactness of the complexes through Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration (Rg), and Solvent Accessible Surface Area (SASA). MM/GBSA calculations are further supported by showing the lowest binding free energy for withanolide O and E (ΔGbind =-20.89 and -20.22 kcal/mol). The ADME studies showed favourable pharmacokinetic and physicochemical properties. DISCUSSION: This study identifies pfDNA gyrase A as a potential molecular target of Withania somnifera-derived withanolides and elucidates their inhibitory mechanism. Withanolides O and E exhibited strong binding affinity, favorable energetics, and distinct dynamic effects, acting through activesite occlusion and allosteric modulation, respectively. Molecular dynamics and free-energy analyses suggest that effective inhibition results from both structural stabilization and the disruption of critical enzyme motions. CONCLUSION: Withanolide derivatives were identified as promising inhibitors of pfDNA gyrase A, highlighting their potential as antimalarial agents for addressing drug-resistant malaria.
Epitranscriptomics in Breast Cancer: The Unveiled Role of RNA Modifications.
Kumari P, Kumar S
Curr Drug Targets · 2026 Jun · PMID 42333563 · Publisher ↗
Epitranscriptomics, the study of dynamic chemical modifications on RNA molecules, has emerged as a pivotal layer of gene expression regulation with profound implications for cancer biology. This review centers on three w...
Epitranscriptomics, the study of dynamic chemical modifications on RNA molecules, has emerged as a pivotal layer of gene expression regulation with profound implications for cancer biology. This review centers on three well-characterized RNA modifications, N6-methyladenosine (m6A), pseudouridine (Ψ), and 5-methylcytosine (m5C), and highlights their diverse roles in the pathogenesis of breast cancer. These modifications modulate critical post-transcriptional processes such as RNA splicing, stability, translation, and degradation, thereby influencing tumor initiation, progression, metastasis, therapy resistance, and interactions within the tumor microenvironment. Also the study briefly explores emerging modifications, including Adenosine-to-Inosine (A-to-I) editing and N1-methyladenosine (m1A), which add further complexity to the epitranscriptomic landscape. Advances in high-throughput sequencing, bioinformatics, and single-cell technologies have significantly deepened understanding of the context-dependent and reversible nature of these modifications. Importantly, RNA modification signatures show promise as non-invasive biomarkers and therapeutic targets. However, translating these insights into clinical applications remains challenging due to issues related to delivery mechanisms, specificity, and regulatory hurdles. This review provides a comprehensive synthesis of current knowledge, highlights key controversies and technological limitations, and discusses future directions for leveraging epitranscriptomics in the early detection and personalized treatment of breast cancer.
Neuroinflammation in Alzheimer's Disease: New Approaches.
Katiyar S, Yadav D, Rabbee MF
Curr Drug Targets · 2026 Jun · PMID 42304748 · Publisher ↗
Alzheimer's Disease (AD), the most prevalent neurodegenerative disorder, is the leading cause of dementia in older adults and is closely associated with chronic neuroinflammation within the central nervous system. The ha...
Alzheimer's Disease (AD), the most prevalent neurodegenerative disorder, is the leading cause of dementia in older adults and is closely associated with chronic neuroinflammation within the central nervous system. The hallmark pathological features of AD include neurofibrillary tangles, amyloid -β plaques, and extensive neuronal loss. Although amyloid-β has been extensively studied, the development of effective disease-modifying therapies remains limited in clinical practice. Novel therapeutic approaches are increasingly focused on modulating these immune mechanisms, such as altering microglial phenotypes, inhibiting the NLRP3 inflammasome, regulating NF-κB and JAK/STAT signalling, and employing cytokine-based interventions. Additionally, stem cell-derived therapies and extracellular vesicles with strong immunomodulatory properties have emerged as promising candidates. This review aims to deepen the understanding of immunoregulatory and inflammatory mechanisms in Alzheimer's disease and to support the development of novel antiinflammatory therapies that may slow or prevent disease progression.
FXYD3: A Key Regulator of Ion Homeostasis and Redox Balance in Cancer Biology.
Gupta M, Rao S, Kumar R
Curr Drug Targets · 2026 Jun · PMID 42304747 · Publisher ↗
Cancer continues to be a major health burden, with millions of new cases and deaths reported annually, and metastasis remains the leading cause of cancer-related mortality. Disruption of transmembrane proteins is a major...
Cancer continues to be a major health burden, with millions of new cases and deaths reported annually, and metastasis remains the leading cause of cancer-related mortality. Disruption of transmembrane proteins is a major regulator of tumor development and progression. This review highlights FXYD3, a single-transmembrane protein that regulates Na+ /K+ -ATPase activity and functions in maintaining ion balance, redox homeostasis, and proliferative signaling in both cancer stem cells and bulk tumor populations. Its expression varies across various cancers, such as breast, pancreatic, lung, colorectal, gastric, and endometrial cancer, where it is linked with tumor development, therapy resistance, and immune modulation. Its involvement in pathways such as PI3K-AKT and cGMP-PKG contributes to malignancy. It protects cells from oxidative stress, thereby promoting cell survival and inhibiting apoptosis. Accumulating evidence highlights the potential role of FXYD3 as an emerging biomarker with relevance to diagnosis, prognosis, and therapeutics. This review provides an overview of FXYD3's role in cancer biology from translational relevance to its potential as a diagnostic, prognostic, and therapeutic target.
Multi-target Agents in Complex Diseases: From Design Principles to Therapeutic Applications.
Maity S, Srinivas MG, Nayak G … +4 more , M I MA, M M, Prabhu PP, Nair A
Curr Drug Targets · 2026 Jun · PMID 42304746 · Publisher ↗
INTRODUCTION: Multifactorial complex diseases such as cancer, neurodegeneration, and infections are poorly treated with traditional single-target therapies because biological networks are redundant and adaptively resista...
INTRODUCTION: Multifactorial complex diseases such as cancer, neurodegeneration, and infections are poorly treated with traditional single-target therapies because biological networks are redundant and adaptively resistant. METHODS: A comprehensive literature review was conducted to investigate the theoretical basis, design approaches (pharmacophore linking, fusing, and merging), and clinical uses of multi-target agents using network pharmacology and systems biology. RESULTS: Multi-kinase inhibitors (imatinib, sunitinib, cabozantinib) approved by the Food and Drug Administration have shown superior efficacy to traditional monotherapies due to multiple driver inhibition; dual acetylcholinesterase and Beta-site amyloid precursor protein cleaving enzyme 1 inhibitors show enhanced neuroprotective effects against Alzheimer's disease; and β-lactam/βlactamase inhibitor combinations address drug resistance. Artificial intelligence can accelerate target identification, and novel design technologies, such as fragment-based screening, can generate balanced polypharmacology. DISCUSSION: Multi-target strategies are ideal for overcoming redundancy in biological networks and minimizing drug resistance. However, several issues remain, including the complexity of target selection, the need to achieve balanced efficacy across multiple targets, ADMET optimization, and regulatory hurdles. Emerging technologies, such as quantum computing, precision polypharmacology based on multiomics profiling, and digital health integration, could improve target selection and optimization. CONCLUSION: Multi-target agents are no longer constrained by single-target effects; however, issues of balanced potency, ADMET, and control still exist. The combination of AI, quantum computing, and precision polypharmacology may enable more effective multi-target interventions to address unmet demands in complex diseases.
DiffDR: A Diffusion-based Deep Learning Framework for Accurate Drug Response Imputation and Feature Selection.
Zheng Q, Zheng S, Jiang Y … +3 more , Wu B, Chai H, Tang H
Curr Drug Targets · 2026 Jun · PMID 42283181 · Publisher ↗
INTRODUCTION: Molecular features play critical roles in shaping cellular responses to therapeutic agents, and understanding their influence on drug sensitivity and resistance is essential for explaining heterogeneous tre...
INTRODUCTION: Molecular features play critical roles in shaping cellular responses to therapeutic agents, and understanding their influence on drug sensitivity and resistance is essential for explaining heterogeneous treatment outcomes. Integrating multi-omics molecular information can uncover complex cross-modal dependencies, identify potential biomarkers, and enhance drug response prediction. However, the high dimensionality and strong interdependencies of multi-omics data pose substantial modeling challenges, underscoring the need for robust, interpretable computational approaches. METHODS: This study presents DiffDR, a diffusion-based framework that models multi-omics features and drug representations through an energy-constrained diffusion module. This module encodes batched samples and efficiently propagates information while preventing over-smoothing, enabling the capture of both global and local dependencies without relying on explicit graph structures. To enhance model transparency, DiffDR incorporates an integrated gradient-based interpretability module that quantitatively attributes prediction outcomes to specific omics features. RESULTS: DiffDR demonstrates superior predictive performance compared with several state-of-theart drug response prediction methods. Ablation analysis indicates that the energy-constrained diffusion mechanism substantially improves predictive accuracy, confirming its effectiveness in handling high-dimensional multi-omics data. DISCUSSION: The findings highlight the value of DiffDR in capturing cross-modal molecular dependencies and providing interpretable insights into drug response mechanisms. CONCLUSION: Overall, DiffDR represents a robust and interpretable approach for drug response prediction, enabling biologically meaningful mechanistic insights into molecular drivers of drug response.
Molecular Docking and Dynamics Simulations of Natural Limonoids Interacting with the Nipah Virus Attachment Glycoprotein.
de Oliveira VM, Marinho MM, Dos Santos HS … +1 more , Marinho ES
Curr Drug Targets · 2026 Jun · PMID 42261155 · Publisher ↗
INTRODUCTION: The Nipah virus (NiV) belongs to the Paramyxoviridae family and is a zoonotic pathogen associated with severe respiratory disease and encephalitis. Fatality rates of up to 70% of diagnosed cases justify its...
INTRODUCTION: The Nipah virus (NiV) belongs to the Paramyxoviridae family and is a zoonotic pathogen associated with severe respiratory disease and encephalitis. Fatality rates of up to 70% of diagnosed cases justify its classification as a biosafety level-4 agent. The absence of specific antiviral therapies underscores the urgent need to identify novel molecular inhibitors. METHODS: This study involved the virtual screening of natural limonoids using molecular docking against the NiV glycoprotein, which is a key target in the adhesion of the virus to human host cells. Subsequently, molecular dynamics simulations were conducted to evaluate the stability of the protein- ligand complexes. RESULTS: Molecular docking results showed that desacetylspathelin (DSP) and nimolicinol (NCL) had the most favourable binding free energy (ΔG) values and relevant interactions with residue Leu124. Molecular dynamics simulations revealed greater structural stability for the DSP-containing complex. DISCUSSION: The observed interaction profiles suggest that these limonoids, particularly DSP, may interact with the NiV glycoprotein, suggesting a possible influence on virus-host adhesion mechanisms. CONCLUSION: These findings suggest that natural limonoids, particularly DSP, are promising candidates for further investigation as potential Nipah virus glycoprotein modulators/inhibitors and could contribute to the development of antiviral strategies.
Piperlongumine: A Natural Alkamide with Multi-target Anti-inflammatory Mechanisms of Action.
Damasceno ROS, Rodrigues LHM, Pinheiro JLS … +1 more , de Sousa DP
Curr Drug Targets · 2026 Jun · PMID 42260787 · Publisher ↗
INTRODUCTION: Natural products are a rich source of bioactive compounds, which present attractive properties for preventing and treating diseases associated with inflammation. Piperlongumine, also known as piplartine, is...
INTRODUCTION: Natural products are a rich source of bioactive compounds, which present attractive properties for preventing and treating diseases associated with inflammation. Piperlongumine, also known as piplartine, is an alkamide found in several types of peppers of the Piper genus, such as Piper longum. This metabolite is a versatile molecule with diverse pharmacological activities that has been used as a prototype in the synthesis of bioactive structural analogs. METHODS: Scientific articles published between 2015 and 2025 were retrieved from the databases PubMed, Google Scholar, Web of Science, and ScienceDirect. Eligibility criteria included experimental studies in English that investigated the anti-inflammatory effects of piperlongumine. RESULTS/DISCUSSION: Current evidence indicates that piperlongumine can inhibit or modulate inflammatory responses, suggesting its pharmacological application in disease prevention and treatment, and the management of complications. CONCLUSION: This review describes recent advances in the anti-inflammatory activity of piperlongumine and its derivatives, providing evidence of their therapeutic potential across inflammatory conditions.
Evaluating the Biological Activities of Oleanolic Acid and Apigenin in a 2-in-1 Nanoparticulate System: A Proof-of-concept Study.
Haider S, Naz A, Afzal A … +3 more , Malik N, Shah NH, Sarfraz M
Curr Drug Targets · 2026 May · PMID 42227514 · Publisher ↗
BACKGROUND: Apigenin (APG) and Oleanolic Acid (OA) exhibit diverse biological activities; however, their pharmaceutical applications are limited by poor solubility, low bioavailability, and restricted permeability. This...
BACKGROUND: Apigenin (APG) and Oleanolic Acid (OA) exhibit diverse biological activities; however, their pharmaceutical applications are limited by poor solubility, low bioavailability, and restricted permeability. This study developed a hybrid nanoparticulate system consisting of apigenin nanoparticles loaded into oleanolic acid micelles, named 2-in-1-NPs, to enhance their therapeutic potential. It was designed as a pilot study to identify the most promising biological activity of the 2-in-1-NPs. METHODS: APG nanoparticles were prepared using the liquid anti-solvent method, while OA micelles were formulated via thin-film hydration. The hybrid system was characterized in terms of particle size, zeta potential, polydispersity index, encapsulation efficiency, and an in vitro drug release study. RESULTS: The optimized hybrid 2-in-1 nanoparticle formulation exhibited a mean particle size of 150.4 ± 0.055 nm with sustained drug release over 72 hours, and high encapsulation efficiencies of 83 ± 0.577% for OA-MM and 92 ± 0.431% for APG-NP. While APG and OA alone showed limited antimicrobial activity against Escherichia coli, Salmonella typhi, Staphylococcus aureus, and Bacillus cereus, the hybrid nanoparticle system significantly enhanced anti-inflammatory activity, demonstrated by a marked reduction in IL-6 levels (p < 0.0001) compared with free or individually loaded drugs, and showed increased cytotoxicity against HepG-2 liver cancer cells with an IC₅₀ of 16.988 μg/mL, highlighting its potential for improved therapeutic efficacy. DISCUSSION: The results demonstrate that the developed system successfully transports the drugs through the cell membrane and exhibits synergistic or additive biological activities, including antiinflammatory and anticancer effects. CONCLUSION: The hybrid 2-in-1-NPs system presents a promising platform for the treatment of various diseases, offering enhanced bioactivity and therapeutic efficacy.
Novel Approaches to Diagnosing and Treating Non-alcoholic Fatty Liver Disease: Opportunities and Accomplishments.
Uzyanbaev I, Timoshenko S, Spirina L … +1 more , Matveeva M
Curr Drug Targets · 2026 May · PMID 42227513 · Publisher ↗
The concept of nonalcoholic fatty liver disease (NAFLD) provides a more precise understanding of the origins of the disease. This is crucial for identifying risk factors, monitoring patients, and developing novel pharmac...
The concept of nonalcoholic fatty liver disease (NAFLD) provides a more precise understanding of the origins of the disease. This is crucial for identifying risk factors, monitoring patients, and developing novel pharmacological approaches for treating MAFLD. Single-nucleotide variations in genes related to fat and carbohydrate metabolism, as well as the state of gut microbiota, are becoming increasingly important. Currently, MAFLD management primarily relies on significant lifestyle modifications, including avoiding alcohol and smoking, and adopting a Mediterranean-style diet. For individuals with excess weight, bariatric surgery remains the only effective option. Among approved medications for MAFLD, only vitamin E and pioglitazone are currently available. However, the potential for fluid retention with pioglitazone limits its use. Therefore, it is important to explore existing treatments and identify new physiological pathways in MAFLD to develop innovative therapies that can effectively address this condition.
Microbial Proteases: Pioneering Tools for Modern Therapeutic Innovations.
Salem GEM, El-Sakhawy MA, Darwish A … +5 more , Negm RM, Ashfaq M, Alhoot MA, Mohammad ZZAE, Tongdeesoontorn W
Curr Drug Targets · 2026 May · PMID 42227512 · Publisher ↗
INTRODUCTION: Proteases are enzymes that play important physiological roles in both production and breakdown. They also play a variety of roles in physiology, biochemistry, and cell regulation. Furthermore, proteases hav...
INTRODUCTION: Proteases are enzymes that play important physiological roles in both production and breakdown. They also play a variety of roles in physiology, biochemistry, and cell regulation. Furthermore, proteases have various uses in the chemical and pharmaceutical industries. Microbial proteases offer many advantages over animal and plant sources, including their wide substrate specificity, fast growth, and ease of genetic manipulation. METHODS: This review explores the benefits of using microbial proteases. The literature search was conducted across electronic bibliographic databases, including PubMed, MEDLINE, Scopus, and Google Scholar, to find pertinent scientific publications on the therapeutic uses of microbial proteases. RESULTS: Microbial proteases are the largest group of industrial enzymes. This review examines their wide range and organizes them according to their catalytic mechanisms and active sites. It highlights their physiological uses in dietary protein digestion, blood coagulation, and cell division. The study also highlights potential therapeutic uses, including biofilm degradation, anti-inflammatory effects, digestive assistance, wound healing, and fibrinolytic proteases. It also discusses its use in treating medical disorders like liver fibrosis and Alzheimer's disease. DISCUSSION: The investigation of microbial proteases as promising new-generation therapeutic agents highlights their exceptional potential for tackling medical issues. Their adaptable catalytic capabilities and environmental friendliness make them attractive as therapeutic agents. CONCLUSION: Microbial proteases are incredibly versatile, exhibiting unique features and functioning in harsh conditions, which creates opportunities for novel uses in treatments and improve biomarkers detection. This review highlights their growing importance in the creation of innovative therapeutic approaches and improve biomarkers detection.
Nanostructured Polymer Scaffolds in Local Chemotherapy in Solid Tumors.
Talele C, Aundhia C, Talele D … +4 more , Shah N, Kumari M, Lalan M, Kulkarni S
Curr Drug Targets · 2026 May · PMID 42227511 · Publisher ↗
INTRODUCTION: Multidrug resistance, inadequate tumor penetration, and systemic toxicity significantly limit the effectiveness of conventional chemotherapy in solid tumors. Scaffold-based localized chemotherapy offers a p...
INTRODUCTION: Multidrug resistance, inadequate tumor penetration, and systemic toxicity significantly limit the effectiveness of conventional chemotherapy in solid tumors. Scaffold-based localized chemotherapy offers a promising approach to overcome these challenges by delivering drugs directly to the tumor site with sustained and controlled release. METHODS: This article reviews electrospun nanofiber scaffolds, injectable hydrogels, 3D-printed scaffolds, and composite biomaterial scaffolds engineered from biodegradable and bioresponsive polymers such as PLGA, PCL, chitosan, and hyaluronic acid. The influence of drug incorporation strategies, including surface loading, encapsulation, and post-fabrication soaking, on drug loading capacity, degradation behavior, mechanical strength, and release kinetics is examined. RESULTS: Preclinical studies in breast cancer, glioblastoma, colorectal cancer, and pancreatic cancer demonstrate that scaffold-based systems increase local drug concentration, reduce systemic toxicity, and improve therapeutic outcomes. Advanced systems such as dual-drug platforms, stimuliresponsive constructs, and immunomodulatory scaffolds show additional potential to modulate the tumor microenvironment, prevent recurrence, and enhance antitumor immune responses. Moreover, technologies such as electrospinning are well established, whereas advanced modalities like 4D bioprinting remain in early developmental stages, limiting their current translational readiness. DISCUSSION: The application of scaffolds in cancer therapy highlights their theranostic potential, combining controlled chemotherapeutic delivery with capabilities for tissue support, microenvironment modulation, and functional integration with biological systems. CONCLUSION: Nanostructured polymer scaffolds represent a promising strategy for localized chemotherapy in solid tumors. By overcoming key limitations of systemic drug delivery, these platforms enhance treatment precision, improve patient outcomes, and demonstrate strong translational potential for next-generation oncology therapeutics.
Exploring the Potential Molecular Mechanisms of Berberine against Gastric Cancer Liver Metastasis Based on Network Pharmacology and Bioinformatics.
Shao T, Wang Y, Lv Y … +3 more , Huang X, Xue K, Jiang X
Curr Drug Targets · 2026 May · PMID 42227510 · Publisher ↗
INTRODUCTION: Gastric cancer (GC) is a common malignancy with a tendency for liver metastasis, leading to poor prognosis. Berberine (BBR), derived from Coptis chinensis Franch., exhibits potent anticancer effects on GC....
INTRODUCTION: Gastric cancer (GC) is a common malignancy with a tendency for liver metastasis, leading to poor prognosis. Berberine (BBR), derived from Coptis chinensis Franch., exhibits potent anticancer effects on GC. However, the mechanism by which BBR affects gastric cancer liver metastasis (GCLM) remains unclear. This study employed network pharmacology and bioinformatics approaches to investigate the potential targets and molecular mechanisms of BBR as a candidate therapeutic drug for GCLM. METHODS: The targets of GCLM and BBR were acquired from public databases. Subsequently, the Protein-Protein Interaction (PPI) network and enrichment analyses were conducted to identify key targets and underlying mechanisms. Pivotal target genes were screened using machine learning algorithms. CIBERSORT analysis was applied to explore the involvement of immune cells in GCLM samples and their correlation with pivotal genes. Ultimately, molecular docking was performed to evaluate the binding affinities between BBR and pivotal target proteins. RESULTS: A total of 120 common targets were obtained after screening. These targets were primarily enriched in the PI3K/Akt signaling pathway. By employing a PPI network, the top 16 targets were acquired. Subsequently, three pivotal target genes (CCL2, SPP1, and ALB) were further identified using machine learning models. CIBERSORT analysis demonstrated significant correlations between three pivotal genes and the tumor immune microenvironment in GCLM patients, especially in the regulation of M0/M2 macrophage infiltration and dendritic cell activation. Molecular docking confirmed stable binding affinities between three pivotal target proteins and BBR. DISCUSSION: This study suggests that BBR may inhibit GCLM by targeting pivotal genes CCL2, SPP1, and ALB, blocking the PI3K/Akt pathway and remodeling the immunosuppressive microenvironment. However, further experimental validation is required to confirm these findings. CONCLUSION: This study revealed the molecular mechanism behind GCLM suppression and identified BBR as a promising therapeutic candidate, providing a basis for the development of novel treatment strategies for GCLM.
predALZ: An Ensemble Learning Framework for Identifying Genetic Biomarkers in Familial Alzheimer's Disease.
Karim A, Alturise F, Alkhalifah T … +1 more , Khan YD
Curr Drug Targets · 2026 May · PMID 42163597 · Publisher ↗
INTRODUCTION: Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder with a substantial genetic contribution, especially in the early-onset form. Mutations in genes like APP, PSEN1, and PSEN2 serve as cr...
INTRODUCTION: Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder with a substantial genetic contribution, especially in the early-onset form. Mutations in genes like APP, PSEN1, and PSEN2 serve as crucial biomarkers, indicating a heightened risk of developing AD. Leveraging these genetic markers, we introduce predALZ, a prediction model designed to enhance early detection of familial AD through genomic sequence analysis. METHODS: The model integrates data derived from genome-wide association studies (GWAS) and employs advanced feature encoding techniques to generate a robust representation of genomic patterns. A diverse ensemble of classifiers, namely XGBoost, Random Forest, LightGBM, and ExtraTrees, is employed to train the predALZ model, utilizing the generated feature vector for training. RESULTS: The predALZ framework achieved 94% accuracy on an independent test set and approximately 96% accuracy in cross-validation for Alzheimer-related driver gene prediction. The ensemble model also yielded consistently high sensitivity, specificity, and Matthews correlation coefficient values, indicating stable and reliable classification performance. DISCUSSION: The model's effectiveness was further rigorously validated through a comprehensive evaluation, using metrics such as accuracy, sensitivity, specificity, and Matthew's correlation coefficient. The study underscores the predictor's remarkable performance, consistently achieving 94% accuracy in an independent Test and ~96% in cross-validation. CONCLUSION: These findings highlight predALZ's potential for application in predictive diagnostics and targeted therapeutic development for Alzheimer's disease.
FAVAR-GAT: A Hybrid Temporal-structural Model for Drug-target Binding Affinity Prediction.
Sharma M, Singh A
Curr Drug Targets · 2026 May · PMID 42163596 · Publisher ↗
INTRODUCTION: The accuracy of drug-target binding affinity prediction is a critical component of modern drug discovery, as it accelerates the efficient identification of compounds with high therapeutic potential. Despite...
INTRODUCTION: The accuracy of drug-target binding affinity prediction is a critical component of modern drug discovery, as it accelerates the efficient identification of compounds with high therapeutic potential. Despite recent advancements, many traditional computational approaches have failed to fully capture the complex temporal dynamics and structural dependencies that control protein- ligand interactions, thereby restricting their predictive accuracy and stability. METHODS: To resolve these constraints, we propose FAVAR-GAT a hybrid framework combining Factor-Augmented Vector Autoregression (FAVAR) and Graph Attention Networks (GAT). To model temporal interaction patterns, FAVAR extracts low-dimensional latent factors, while GAT encodes molecular graph structures through adaptive attention. This hybrid architecture captures structural, temporal, and relational features of drug-target interactions. RESULTS: The hybrid FAVAR-GAT methodology is estimated on various benchmark datasets: Davis, KIBA, BindingDB, and PDBbind. Our experimental results show that FAVAR-GAT outperforms the state-of-the-art baseline models across various evaluation metrics, including Concordance Index (CI), Mean Squared Error (MSE), and R², demonstrating improved predictive accuracy. DISCUSSION: The proposed hybrid framework combines latent factor modeling with attention-based graph learning to improve drug-target binding affinity prediction. CONCLUSION: The study demonstrates that integrating graph attention mechanisms with latent feature extraction provides a robust and scalable approach for computational drug discovery. The framework shows strong potential for improving drug-target interaction analysis and supporting future AIdriven pharmaceutical research.
Target-based Antidiabetic Indole Derivatives and Insights into Structure-activity Relationships: A Mechanistic Update 2020-2025.
Wal A, Wal P, Gupta A … +5 more , Hemalatha G, Kumar M, Chellammal HSJ, Mundada AB, Gasmi A
Curr Drug Targets · 2026 May · PMID 42136244 · Publisher ↗
INTRODUCTION: Type 2 diabetes mellitus (T2DM) continues to rise globally, and the limitations of existing therapies highlight the urgent need for novel interventions. Indole derivatives have emerged as promising candidat...
INTRODUCTION: Type 2 diabetes mellitus (T2DM) continues to rise globally, and the limitations of existing therapies highlight the urgent need for novel interventions. Indole derivatives have emerged as promising candidates due to their structural adaptability, multi-target engagement, and favorable pharmacokinetic profiles. METHODS: We conducted a comprehensive review of literature published between 2020 and 2025, systematically searching PubMed, Scopus, and Web of Science for studies on indole-based antidiabetic agents. The inclusion criteria emphasized mechanistic insights, structure-activity relationships (SAR), preclinical advancements, and early clinical evaluations. RESULTS: Over 120 indole derivatives were identified targeting key diabetes-related pathways, including AMPK activation, insulin receptor sensitization, β-cell protection, and enzyme inhibition (e.g., DPP-4, α-glucosidase). SAR analyses revealed that position-specific modifications at N1, C2, C3, and C5 significantly enhance bioactivity and selectivity. Innovations in synthesis (e.g., microwave-assisted, green chemistry approaches), formulation (e.g., nanoparticles, prodrugs), and AI-assisted drug design have improved clinical viability. DISCUSSION: The evidence supports the unique polypharmacological profile of indole scaffolds, enabling multi-pathway modulation and addressing both hyperglycaemia and its complications. Challenges remain regarding toxicity, solubility, and translational gaps, but emerging delivery strategies and personalized medicine approaches show promise. CONCLUSION: Indole derivatives represent a transformative class of antidiabetic agents with multitarget activity and strong therapeutic potential, warranting further clinical validation to optimize their role in precision medicine.
Decoding the Molecular Targets of Luteolin and Fisetin: Emerging Trends in Flavonoid-Based Therapeutics (A Systematic Review).
Aziz N, Wal A, Parveen G … +5 more , Basra GS, Tandey R, Khan A, Chellammal HSJ, Gasmi A
Curr Drug Targets · 2026 May · PMID 42136243 · Publisher ↗
BACKGROUND: Luteolin and fisetin are emerging lead flavonoids with significant therapeutic promise due to their wide-spectrum modulation of key molecular signalling pathways implicated in oxidative stress, inflammation,...
BACKGROUND: Luteolin and fisetin are emerging lead flavonoids with significant therapeutic promise due to their wide-spectrum modulation of key molecular signalling pathways implicated in oxidative stress, inflammation, metabolic dysfunction, neurodegeneration, and cancer. However, mechanistic integration, SAR-based interpretation, and translational pharmacokinetic understanding remain fragmented. This systematic review aims to consolidate molecular targets, signalling network interactions, structure-activity relationships, pharmacokinetic limitations, and clinical advancement potential of luteolin and fisetin to define their future drug development relevance. METHODS: A systematic PRISMA-based strategy was employed across PubMed, Scopus, Web of Science, and Google Scholar up to March 2025. Eligible in vitro, in vivo, and clinical studies evaluating the mechanistic activity, SAR influence, pharmacokinetics, or therapeutic efficacy of luteolin/ fisetin were included. Data were narratively synthesised due to heterogeneity in study designs. RESULTS: A total of 127 studies met eligibility criteria. Both flavonoids demonstrated multi-target and multi-pathway modulation involving NF-κB, Nrf2, MAPK, PI3K/Akt, apoptotic regulators, neuroinflammatory signals, and metabolic pathway nodes. SAR analysis identified hydroxylation patterns, O-methylation, and glycosylation as determinants of potency, membrane permeability, and ADME properties. Pharmacokinetic evidence revealed poor solubility, low oral bioavailability, and rapid metabolism, though nanoformulations, prodrugs, and targeted delivery systems significantly enhanced systemic exposure and therapeutic index. CONCLUSION: Luteolin and fisetin represent valuable flavonoid scaffolds with highly relevant druggable molecular targets. Despite promising mechanistic depth, clinical validation remains limited, and pharmacokinetic barriers warrant strategic optimisation. Future translational advancement should prioritise structure-guided analogue development, BBB penetration enhancement, and biomarker-linked clinical endpoints.
Innovative Nanoparticle-based Therapeutic Strategies: Overcoming Biological Barriers for Enhanced Efficacy.
Rathee S, Soni S, Sen D … +1 more , Jain SK
Curr Drug Targets · 2026 May · PMID 42136242 · Publisher ↗
The Blood-Brain Barrier (BBB) poses a formidable challenge for drug delivery to the Central Nervous System (CNS) due to its selective permeability and robust defense mechanisms. This review provides a comprehensive exami...
The Blood-Brain Barrier (BBB) poses a formidable challenge for drug delivery to the Central Nervous System (CNS) due to its selective permeability and robust defense mechanisms. This review provides a comprehensive examination of the anatomical structure, physiology, and physiological challenges of the BBB, along with innovative approaches for overcoming these barriers to enhance CNS drug delivery. The BBB is primarily composed of endothelial cells, pericytes, and astrocytic end-feet, reinforced by tight junctions that tightly regulate the passage of substances into the brain parenchyma. Various transport mechanisms, including carrier-mediated transport, receptor-mediated transport (e.g., via LDL and transferrin receptors), absorptive-mediated transport, and active efflux transport, govern the selective influx and efflux of molecules across the BBB to maintain CNS homeostasis. Biological approaches harness endogenous transport mechanisms to facilitate drug delivery across the BBB, while chemical approaches leverage nanotechnology to engineer nanoparticles capable of traversing the barrier. These include liposomes, solid-lipid nanoparticles, polymeric nanoparticles, and inorganic nanoparticles, each designed with specific parameters such as particle size, shape, and surface charge to optimize drug delivery. Drug loading strategies, such as covalent bonding and non-covalent adsorption, enhance the encapsulation and release of therapeutic agents from nanoparticles. Furthermore, the incorporation of ligands facilitates receptor targeting and protein corona formation, enhancing nanoparticle properties and improving BBB penetration. By synthesizing recent advancements in BBB permeation strategies, this review aims to provide insights into the development of effective therapies for neurological disorders, ultimately advancing the field of CNS drug delivery.
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