Current Drug Targets[JOURNAL]
Sun
200 papers
An Explainable Deep Learning Model for Clathrin Protein Prediction Using a DCT-Enhanced Position-Specific Scoring Matrix.
Ghulam A, Ali T, Sikander R … +3 more , Ali F, Masmoudi A, Alsini R
Curr Drug Targets · 2026 Feb · PMID 41735215 · Publisher ↗
INTRODUCTION: Clathrin protein (CP) plays a vital role in essential cellular processes, in-cluding endocytosis and signal transduction. Dysfunctions in CP have been associated with vari-ous diseases, including neurodegen...
INTRODUCTION: Clathrin protein (CP) plays a vital role in essential cellular processes, in-cluding endocytosis and signal transduction. Dysfunctions in CP have been associated with vari-ous diseases, including neurodegenerative disorders and cancer, making it a significant focus of biomedical research. METHODS: This study introduces Pred-CLGRUs, a novel computational framework for predicting Clathrin protein using Gated Recurrent Units (GRUs). Pred-CLGRUs utilize a Position-Specific Scoring Matrix (PSSM) in conjunction with the Discrete Cosine Transform (DCT) to enhance feature extraction while reducing noise and redundancy. A potential explanation for this mis-match could be that the Average Block-PSSM feature is derived from the Position-Specific Scor-ing Matrix (PSSM). The proposed model is trained using four deep learning architectures: GRUs, Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs). RESULTS: The PSSM-DCT input enabled GRUs to achieve 93.33% accuracy, producing a Mat-thews Correlation Coefficient value of 0.86. Pred-CLGRUs enabled GRUs to achieve an accuracy of 93.33%, sensitivity of 94.44%, and specificity of 92.22%, while maintaining a Matthews corre-lation coefficient of 0.86. DISCUSSION: We began by calculating PSSM to detect evolutionary changes. The compression method named DCT was applied within each PSSM during the second implementation step. CONCLUSION: The predictive performance can be significantly enhanced if the model can incorpo-rate heterogeneous types of biological information, such as structure, evolution, and function. We plan to design a novel prediction model that combines Capsule Neural Networks (CapsNet) with DeepWalk to obtain structural features.
Mechanistic Approach to Ferroptosis in Cancer and Neurological Diseases.
Wal P, Jadaun AS, Verma R … +4 more , S RJ, Dwivedi SK, Surwade KS, Aziz N
Curr Drug Targets · 2026 Jan · PMID 41603173 · Publisher ↗
Ferroptosis is a form of oxidative, iron-dependent, non-apoptotic cell death characterized by the accumulation of lipid peroxides and the depletion of glutathione. Ferroptosis plays a significant role in human cancer and...
Ferroptosis is a form of oxidative, iron-dependent, non-apoptotic cell death characterized by the accumulation of lipid peroxides and the depletion of glutathione. Ferroptosis plays a significant role in human cancer and is essential in neurological disorders, including neurodegeneration, stroke, and neurotrauma. One of the key challenges in cancer research is how to effectively kill cancer cells while leaving healthy cells intact. Cancer cells often have defects in cell death executioner mechanisms, which is one of the main reasons for therapy resistance. To enable growth, cancer cells exhibit an increased iron demand compared with normal, non-cancer cells. This iron dependency can make cancer cells more vulnerable to iron-catalyzed necrosis, referred to as ferroptosis. It is a newly identified regulated form of cell death, which is thought to play a major role in neurodegenerative diseases. The mechanisms of ferroptosis in several neurological disorders are discussed in detail in this article. It also provides an overview of emerging medications that target ferroptosis in the treatment of neurological disorders. It also highlights the variations and connections between the different cell death pathways implicated in neurological disorders. Clarifying the function of ferroptosis in the brain will help us better understand the mechanisms behind neurological disorders and offer possible strategies for both acute and long-term neurological illness prevention and therapy. Consequently, we provide an overview and brief description of the main pathways involved in ferroptosis in this review, focusing on its regulation and its dual roles as a tumor suppressor and an oncogenic process in various human malignancies. The identification of FDA-approved drugs as ferroptosis inducers has raised high expectations for ferroptosis as a promising new approach to killing therapy-resistant cancers.
Possible Applications of Azurin, a Copper-Containing Protein, in Cancer Treatment: Prospects and Challenges.
Karmanova EE, Goncharov RG, Burmistrov DE … +3 more , Chernikov AV, Novoselov VI, Sharapov MG
Curr Drug Targets · 2026 Jan · PMID 41588952 · Publisher ↗
INTRODUCTION: Conventional cancer therapies are limited by systemic toxicity, poor selectivity, and drug resistance. Bacterial proteins, such as azurin, represent a promising alternative due to their tumor selectivity, l...
INTRODUCTION: Conventional cancer therapies are limited by systemic toxicity, poor selectivity, and drug resistance. Bacterial proteins, such as azurin, represent a promising alternative due to their tumor selectivity, low immunogenicity, and multifunctional mechanisms. This review highlights recent progress in azurin-based anticancer strategies, including mechanisms of action, structural modifications, and integration with peptide systems, nanotechnology, and gene therapy. METHODS: A search for articles using the keywords "azurin, cancer" was conducted on the Google Scholar and PubMed databases, with an emphasis on the years 2023-2024. RESULTS: Azurin and its peptide derivative p28 selectively target cancer cells by stabilizing p53, inducing apoptosis, and arresting the cell cycle, while also modulating key signaling pathways. Structural features of azurin enable interactions with multiple molecular targets, and p28 enhances cellular uptake and sensitizes tumors to chemotherapeutics. Advanced delivery platforms, including engineered bacteria (E. coli Nissle 1917, S. typhimurium VNP-20009), chimeric peptides, and nanocarriers, improve tumor targeting and therapeutic outcomes. Preclinical models and clinical trials demonstrate low toxicity and efficacy against various solid tumors and gliomas. DISCUSSION: Evidence supports azurin as a versatile anticancer agent with unique advantages over conventional therapies. Its compatibility with delivery innovations enhances precision and minimizes systemic toxicity. However, further optimization, large-scale clinical validation, and long-term safety studies are required. CONCLUSION: Azurin and its derivatives provide a promising platform for anticancer therapy, offering tumor specificity, low toxicity, and synergy with multiple treatment modalities. Their integration into advanced delivery and genetic systems may significantly improve cancer treatment and recurrence prevention.
MET Exon 14 Skipping Mutation in NSCLC: From Genomic Discovery to Biomarker-Guided Therapeutic Innovation.
Huang X, Zhang S, Wang L … +3 more , Qiu Y, Zhao M, Chen Q
Curr Drug Targets · 2026 Jan · PMID 41588951 · Publisher ↗
INTRODUCTION: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and the MET exon 14 skipping mutation is a key oncogenic driver, which promotes tumor progression and provides a new direction for...
INTRODUCTION: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and the MET exon 14 skipping mutation is a key oncogenic driver, which promotes tumor progression and provides a new direction for precision therapy. METHODS: A systematic search of English-language literature and clinical trial data related to the MET exon 14 skipping mutation from 2020-2025 was performed to summarize the role of the mutation and therapeutic advances. RESULTS: DNA-based next-generation sequencing (NGS), RNA-based NGS, and RT-qPCR were employed as the main detection methods. Preclinical models confirmed that mutations promote tumor progression by activating the RAS/MAPK pathway. Clinical trials have reported objective remission rates (ORR) of 46-68% for first-line treatment with MET inhibitors in NSCLC patients harboring MET exon 14 skipping mutations. DISCUSSION: MET exon 14 skipping mutation as a therapeutic target for NSCLC has made significant progress, and MET inhibitors are more advantageous than chemotherapy and immunotherapy, and have been recommended by national and international guidelines as a first-line treatment option. Additionally, NGS technology has the potential to dynamically monitor tumor evolution and drugresistant mutations, thereby helping to realize precision medicine. CONCLUSION: The MET exon 14 skipping mutation is an important target for the precision treatment of NSCLC, and MET-TKIs have remarkable efficacy but a prominent problem with drug resistance. The construction of a precision medicine system encompassing diagnosis, treatment, and drug resistance management through multi-omics research, technological innovation, and international collaboration is a key direction for improving prognosis.
XCPP: A Multi-model Explainable Deep Learning Framework for Accurate Identification of Cell-Penetrating Peptides from Structured Sequence Features.
Riasat H, Alkhalifah T, Alturise F … +1 more , Khan YD
Curr Drug Targets · 2026 Jan · PMID 41588770 · Publisher ↗
INTRODUCTION: The therapeutic candidate CPPs are short amino acid sequences that can deliver attractive therapeutic molecules across cellular membranes. Hence, CPPs can provide the backbone and mechanisms for drug tailor...
INTRODUCTION: The therapeutic candidate CPPs are short amino acid sequences that can deliver attractive therapeutic molecules across cellular membranes. Hence, CPPs can provide the backbone and mechanisms for drug tailoring and diagnostics. METHODS: A structured dataset consisting of 473 confirmed CPPs derived from the EnDM-CPP database was analyzed. Four sequence descriptors were computed: Position Relative Incidence Matrix (PRIM), Reverse PRIM (RPRIM), Accumulative Absolute Position Incidence Vector (AAPIV), and Reverse AAPIV. These feature vectors were used to train and test three deep learning architectures: Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks. Self-consistency testing, independent testing, and 10-fold crossvalidation were used for model evaluation. Additionally, SHAP values were employed to explain the XAI sequences and identify the most important sequence components. RESULTS: The best score during cross-validation was achieved by the CNN model, with an accuracy of 99.05%, followed by the DNN. In contrast, the LSTM model achieved an accuracy of 95.24%, a substantial drop from the former, suggesting it may be suffering from overfitting. In general, all models were able to predict outputs with reasonable accuracy given the structured input features. Biologically relevant descriptors were highlighted by the SHAP analysis, which improved the transparency of the predictions. DISCUSSION: The performance of the CNN indicates its ability to process structured sequence-based biological data effectively. The drop in accuracy with the LSTM model suggests insufficient training data or lack of proper regularization. The use of SHAP enhances explainability by linking features to biological properties. While in vitro or in vivo validation has not yet been performed, the current analysis suggests that in silico CPP prediction is feasible. CONCLUSION: Deep learning in this case has created a framework that can accurately identify CPPs. The CNN model also has additional features that make it ideal for use in drug delivery, molecular diagnostics, and personalized medicine. SHAP-based XAI further adds explainability, increasing trust in the model's predictions.
In vitro Evaluation of Memantine and Nicotinamide Combination for Synergistic Cytotoxicity in U87MG Glioblastoma Cells.
Kumari P, Garg S, Dang S
Curr Drug Targets · 2026 Jan · PMID 41588590 · Publisher ↗
INTRODUCTION: Glioblastoma multiforme (GBM) is one of the most aggressive and treatment-resistant brain tumors. Conventional therapies often fail to produce durable clinical responses due to rapid progression and therape...
INTRODUCTION: Glioblastoma multiforme (GBM) is one of the most aggressive and treatment-resistant brain tumors. Conventional therapies often fail to produce durable clinical responses due to rapid progression and therapeutic resistance. Drug repurposing offers a promising strategy to identify effective combinations using existing drugs. METHODS: This study evaluated the synergistic effects of Memantine (MEM), an NMDA receptor antagonist, and Nicotinamide (NAM), a form of vitamin B3, in U87MG GBM cells. The Chou- Talalay fixed-ratio (1:1) design was employed across five concentration levels. Cytotoxicity and anti-migratory effects were assessed after 24 h of treatment, and data were analyzed using CompuSyn (v2.0). RESULTS: The MEM-NAM combination exhibited significant synergistic cytotoxicity with a combination index (CI) of 0.45 ± 0.08. The IC₅₀ values were 48.2 ± 2.6 μM for Memantine and 1297.90 ± 2.46 μM for Nicotinamide. The combination also markedly inhibited GBM cell migration compared with single-drug treatments. DISCUSSION: The synergistic interaction between MEM and NAM suggests a complementary mechanism that enhances anti-proliferative and anti-migratory responses in GBM cells. This supports the therapeutic potential of repurposed drug combinations in overcoming tumor resistance. CONCLUSION: The Memantine-Nicotinamide combination demonstrates significant in vitro synergy and anti-migratory effects against glioblastoma cells, warranting further investigation in preclinical and clinical models to validate its translational potential.
Evaluation of the Combined Therapeutic Potential of Turmeric and Donepezil on the Cholinergic System in a Mouse Model of AD-like Pathology.
Justin S, Ali SA, Masood M … +8 more , Abbasi SW, Farhat SM, Shakeel R, Khalid A, Mahboob A, Zafar S, Zahid S, Ahmed T
Curr Drug Targets · 2026 Jan · PMID 41588589 · Publisher ↗
INTRODUCTION: The multifactorial pathogenesis of Alzheimer's Disease (AD) makes effective prevention and treatment challenging. Integrative medicine presents a promising approach by complementing conventional treatments...
INTRODUCTION: The multifactorial pathogenesis of Alzheimer's Disease (AD) makes effective prevention and treatment challenging. Integrative medicine presents a promising approach by complementing conventional treatments with neuroprotective nutraceuticals. This study investigates the individual and combinatorial effects of turmeric, a neuroprotective herb, and donepezil, an acetylcholinesterase (AChE) inhibitor, on cognitive functions in a scopolamine-induced amnesic mouse model. METHODS: Molecular interactions of curcuminoids and donepezil with AChE were analyzed using AutoDock Vina and AMBER22. In animal model studies, amnesia was induced in BALB/c mice via subcutaneous injections of scopolamine (1mg/kg/day) for a duration of 25 days. From the 11th day onwards, the turmeric rhizome powder (20mg/kg/day) and donepezil (0.5mg/kg/day) were orally administered as monotherapies or in combination. Cognitive functions were assessed through behavior tests. RESULTS: Molecular docking and dynamics simulations revealed that curcuminoids (curcumin, bisdemethoxycurcumin, and desmethoxycurcumin) inhibited AChE more effectively than donepezil. Animal studies demonstrated significant enhancements in spatial, reference, recognition, and contextual fear memories, with both turmeric and donepezil monotherapies, and their combination therapy. No significant differences were observed between monotherapies, and no additive effect was evident in the combination therapy. DISCUSSION: Co-administration of turmeric and donepezil did not yield a significant additive effect on cognitive improvement in scopolamine-induced amnesic mice. Turmeric monotherapy showed cognitive improvements comparable to those of donepezil monotherapy, highlighting its potential as a candidate therapy for donepezil-resistant AD. CONCLUSION: Turmeric monotherapy improved cognitive performance similarly to donepezil monotherapy in scopolamine-induced amnesic mice. These preliminary findings require further research, including dose optimization and clinical trials, to establish their clinical relevance.
Personalized Nanocomposite-based Drug Delivery Systems: Integration of AI and 3D Printing.
Aundhia C, Parmar G, Talele C … +2 more , Kumari M, Gupta G
Curr Drug Targets · 2026 Jan · PMID 41588588 · Publisher ↗
INTRODUCTION: This review aims to comprehensively discuss the emerging role of artificial intelligence (AI) and three-dimensional (3D) printing in the design and development of personalized polymeric nanocomposite-based...
INTRODUCTION: This review aims to comprehensively discuss the emerging role of artificial intelligence (AI) and three-dimensional (3D) printing in the design and development of personalized polymeric nanocomposite-based drug delivery systems. The focus is on how integrating these technologies enhances the precision, efficacy, and customization of pharmacotherapy compared with conventional formulations. METHODOLOGY: An extensive literature survey was conducted using databases such as PubMed, Scopus, Web of Science, and ScienceDirect, focusing on publications from the past decade. Peerreviewed studies, reviews, and reports on polymeric nanocomposites, AI-based formulation design, and 3D-printed drug delivery systems were critically analyzed. The collected data were synthesized to elucidate design principles, fabrication methods, and the synergistic application of AI and 3D printing in personalized medicine. RESULTS: Polymeric nanocomposites have demonstrated superior performance in targeted and controlled drug release due to their adaptable physicochemical properties and biocompatibility. The application of AI enables predictive modeling, optimization of formulation parameters, and patient stratification through data-driven algorithms. Concurrently, 3D printing enables the fabrication of patient-specific dosage forms and implants with programmable drug-release profiles. Together, these technologies enable the development of individualized therapeutic systems that enhance treatment outcomes and minimize adverse effects. DISCUSSION: This synergistic incorporation of AI and additive manufacturing tackles some of the main obstacles in precision medicine by diminishing trial-and-error in formulation, enhancing reproducibility, and promoting better outcomes during treatment. Such multidisciplinary applications are most promising in cancer, diabetes, neurodegenerative, infectious, and cardiovascular diseases. CONCLUSION: The integration of AI and 3D printing represents a transformative advancement in personalized nanocomposite drug delivery. These interdisciplinary approaches collectively enable precise control over drug release kinetics, dosage customization, and formulation design. Future developments focusing on regulatory standardization, ethical data use, and large-scale clinical translation will further accelerate the adoption of AI- and 3D-printing-assisted personalized drug delivery systems in clinical practice. While these technologies hold great potential for personalized and precise therapeutics, their clinical translation remains challenged by regulatory validation, manufacturing reproducibility, and data transparency requirements.
Long Non-coding RNAs in Non-small Cell Lung Carcinoma: Regulatory Mechanisms, Diagnostic Potential, and Therapeutic Perspectives.
Ma L, Yang F
Curr Drug Targets · 2026 Jan · PMID 41582572 · Publisher ↗
INTRODUCTION: Long noncoding RNAs (lncRNAs) are a unique class of RNA molecules that do not code for proteins but play a significant role in regulating various cellular processes. This article aims to contribute to a bet...
INTRODUCTION: Long noncoding RNAs (lncRNAs) are a unique class of RNA molecules that do not code for proteins but play a significant role in regulating various cellular processes. This article aims to contribute to a better understanding of lncRNA biology in NSCLC and to inspire further research that will improve the diagnosis, treatment, and prevention of this deadly disease. METHODS: A literature review was performed using PubMed, Scopus, and Web of Science to analyze studies on lncRNAs in NSCLC published between 2015 and 2025. RESULTS: In NSCLC, lncRNAs are commonly dysregulated and can function as either oncogenic or tumor-suppressive regulators, contributing to cancer development and progression. They regulate gene expression directly, act as competitive endogenous RNAs that bind to microRNAs and proteins, and interact with RNA-binding proteins. Furthermore, lncRNAs influence the tumor immune microenvironment, alter cellular metabolism, maintain cancer stem cell properties, and induce angiogenesis by activating specific signaling pathways. LncRNAs have attracted increasing attention for their roles as diagnostic and prognostic biomarkers in liquid biopsies and for their therapeutic relevance in NSCLC. DISCUSSION: This review examines the critical roles and diverse functions of lncRNAs, emphasizing their clinical applicability, recent advances in research, existing challenges, novel approaches, and prospects for NSCLC treatment. CONCLUSION: By synthesizing recent findings, this study highlights the significant role of lncRNAs in carcinogenesis, encourages further research in this field, and uncovers the complex network of lncRNA-mediated regulatory effects that could lead to innovative diagnostic tools and therapeutic interventions.
Bidirectional Communication of Estrogen in Gut-Brain Axis: Evidence from Preclinical and Clinical Studies.
Chaudhary R, Bansal N, Sharma S … +3 more , Gupta S, Chopra K, Bansal S
Curr Drug Targets · 2026 Jan · PMID 41582391 · Publisher ↗
INTRODUCTION: Estrogen deficiency in postmenopausal women influences several physiological processes, notably affecting the gut-brain axis (GBA). Emerging evidence from both preclinical and clinical studies suggests that...
INTRODUCTION: Estrogen deficiency in postmenopausal women influences several physiological processes, notably affecting the gut-brain axis (GBA). Emerging evidence from both preclinical and clinical studies suggests that the loss of estrogen following menopause contributes to GBA dysfunction. The present review aims to explore the clinical and preclinical evidence linking estrogen deficiency-induced gut dysbiosis with GBA dysfunction in postmenopausal women. METHODS: A literature survey was conducted using scientific databases such as PubMed, Google Scholar, ResearchGate, and Semantic Scholar to evaluate studies focused on estrogen's role in modulating GBA dysfunction using keywords such as estrogen, GBA, menopause, gut dysbiosis, and GM. Both experimental and observational studies were considered to synthesize current findings. RESULTS: Estrogen deficiency has been shown to alter the composition and diversity of GM, impair gut barrier function, and dysregulate immune responses involving T cells and microglia within the GIT and CNS. These disruptions are associated with cognitive decline, emotional disturbances, and neurodegenerative conditions. Evidence supports a strong association between menopause-related estrogen loss, gut microbial imbalance, and GBA dysfunction. DISCUSSION: The estrogen-GBA plays a crucial role in postmenopausal health, and phytoestrogenmediated modulation of GM offers a promising therapeutic approach supported by preclinical evidence. However, limited clinical data and population variability highlight the need for well-designed human studies to validate these findings. CONCLUSION: Targeting GM modulation presents a promising therapeutic strategy for mitigating GBA dysfunction in postmenopausal women. This review consolidates existing evidence and highlights the need for further research into microbiota-based interventions to alleviate estrogen deficiency- related neurophysiological disorders.
Molecular Dynamics Simulations and Current Trends in Designing New Antivirals Targeting Proteases: A Review from 2018 to 2025.
Nogueira AG, Silva HF, Sales TA … +1 more , Ramalho TC
Curr Drug Targets · 2026 Jan · PMID 41572761 · Publisher ↗
In recent years, Molecular Dynamics (MD) simulations have emerged as a cornerstone in molecular biology and antiviral drug discovery, driven by the growing demand for high-resolution insights into biomolecular behaviour....
In recent years, Molecular Dynamics (MD) simulations have emerged as a cornerstone in molecular biology and antiviral drug discovery, driven by the growing demand for high-resolution insights into biomolecular behaviour. This surge in relevance stems from the need to understand complex molecular mechanisms at an atomic scale, an area where traditional experimental techniques often face limitations. MD simulations offer a powerful computational framework capable of capturing the dynamic behaviour of proteases and other biomolecules with unparalleled spatial and temporal resolution. As a result, they have become instrumental in elucidating protein inhibition mechanisms, unveiling the molecular basis of various diseases, and guiding the rational design and optimization of therapeutic agents. In this review, we synthesize recent advances in the application of MD simulations to the study of protease inhibitors, highlighting their transformative impact on drug discovery and structural biology.
Targeting InhA for Tuberculosis Therapy: A Review of Recent Advances in Enzyme Inhibition and Drug Development.
Parigi SN, Thunga G, Bhat V
Curr Drug Targets · 2026 Jan · PMID 41572760 · Publisher ↗
Mycobacterium Tuberculosis (Mtb) is developing resistance to available antibiotics, posing new challenges and making first-line drugs (Isoniazid, ethambutol, pyrazinamide) ineffective. Second-line medications are also lo...
Mycobacterium Tuberculosis (Mtb) is developing resistance to available antibiotics, posing new challenges and making first-line drugs (Isoniazid, ethambutol, pyrazinamide) ineffective. Second-line medications are also losing effectiveness due to their high toxicity and limited availability, necessitating more advanced treatment in modern drug discovery and development. Tiliacorinine, 2'-nortiliacorinine, and griselimycin, derived from natural sources, paved the way for the development of compounds and approved drugs, such as bedaquiline, delamanid, pyrifazimine, proteomandid, and telacebec, which are currently under review for use. The primary outcome of this worldwide endeavour is the breakthrough of the late-stage T.B. medication pipeline into the clinics. Fundamental research must be supported to maintain a robust pipeline of T.B. drugs, and early-stage discovery work must be pursued. Understanding pathophysiology, enzyme structure, and function helps identify novel therapeutic targets and associated therapeutic approaches. A comprehensive literature search was conducted across PubMed Central, MEDLINE, Scopus, and Embase. A total of 893 studies have been retrieved from the databases. Out of which 150 duplicates were removed. The studies were included based on InhA targeted in TB, "in-silico" studies, which performed biological activity on the molecules published from 2015 to date. The futuristic approach to treating tuberculosis on the ground level could be identifying potential targets and their pharmacophores. We selected an enzyme called InhA because InhA (enoyl acyl carrier protein reductase) plays a crucial role in metabolism, and its sequence is conserved across numerous bacterial species. This review provides a brief on the design, synthesis, protein, activity, and pharmacophore moieties and their substitutions that cause the inhibition of this versatile target. We verified publications from 2013 that explore the same topic and reviewed chemistry-related research from Elsevier and other publishers, including future directions and targets that have been available.
Association Between EGFR Expression in Non-Small Cell Lung Cancer and Dietary Legume Intake.
Wang C, Fu F, Zhang Y … +4 more , Tong M, Huang S, Fu D, Wang X
Curr Drug Targets · 2026 Jan · PMID 41568509 · Publisher ↗
INTRODUCTION: This study aimed to investigate the expression of the epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC) tissues and its association with the frequency of legume food intake. METH...
INTRODUCTION: This study aimed to investigate the expression of the epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC) tissues and its association with the frequency of legume food intake. METHODS: Clinical data from 93 NSCLC patients at Jiujiang University-affiliated Hospital (2018-2023) were collected. Postoperative recurrence status and legume intake were obtained via telephone follow-up. Fourteen patients with recurrence or metastasis were assigned to the first progression (FP) group. Propensity score matching (1:3) was used to select 42 non-progression (NP) matched patients, totaling 56 for analysis. Patients were divided into low- and high-legume intake groups. EGFR expression was assessed by immunohistochemistry and statistical analysis. RESULTS: EGFR positivity was higher in the FP group (78.6%, 11/14) than in the NP group (47.6%, 20/42) (P < 0.05). The NP group had a greater proportion of patients with high-frequency legume consumption compared to the FP group (71.4% vs. 35.7%, P < 0.05). Furthermore, patients with high-frequency legume intake (42.9%, 15/35) showed significantly lower EGFR positivity than those in the low-frequency intake group (76.2%, 16/21) (P < 0.05). These results indicate that higher legume intake correlates with both reduced EGFR expression and a decreased postoperative recurrence risk. DISCUSSION: These findings suggest that higher legume intake is associated with reduced EGFR expression and better postoperative outcomes in NSCLC patients. Legume consumption may modulate disease progression through EGFR regulation. CONCLUSION: High legume intake correlates with improved prognosis and lower EGFR expression in NSCLC. Further large-scale prospective studies are needed to validate these associations and explore their clinical implications.
Marine Microbes: A Source of Novel Antibiotics against Antimicrobial-resistant (AMR) pathogens: A Systematic Review.
Raninga I, Banerjee D
Curr Drug Targets · 2026 Jan · PMID 41510723 · Publisher ↗
INTRODUCTION: The development of novel antibiotics is urgently needed due to the rise in multidrug-resistant (MDR) infections globally. Marine microorganisms have emerged as unexplored sources of bioactive compounds with...
INTRODUCTION: The development of novel antibiotics is urgently needed due to the rise in multidrug-resistant (MDR) infections globally. Marine microorganisms have emerged as unexplored sources of bioactive compounds with unique mechanisms to combat antimicrobial resistance (AMR). METHODS: This review summarizes peer-reviewed and recent research from PubMed, Scopus, and Web of Science to evaluate the scope of marine-derived metabolites against AMR pathogens. The focus was on studies describing antimicrobial metabolites produced by marine actinomycetes, bacteria, and fungi. Studies involving non-resistant pathogens or non-marine sources were excluded. RESULTS: The review identifies various secondary metabolites, including peptides, polyketides, macrolides, fatty acid amines, equisetin, and aminolipids. These compounds target AMR pathogens such as MRSA, VRE, and VRSE. Marine actinomycetes-including Streptomyces spp., Micromonospora spp., and Verrucosispora spp.-are key producers of antimicrobial compounds. Likewise, marine bacterial species such as Bacillus spp., Aequorivita spp., and Zobellia galactanivorans, as well as fungal species like Penicillium spp. and Fusarium spp., produce bioactive compounds. DISCUSSION: These findings highlight the potential of marine microbes as sources of novel antibiotics. Despite this potential, several limitations persist, including scalability issues, the noncultivability of many microbes, toxicology concerns, source-dependent variability, and insufficient in vivo validation. These challenges can be addressed by integrating modern omics technologies to advance drug discovery for AMR. CONCLUSION: This review underscores marine microbes as promising sources in the fight against AMR. To unlock their full potential, greater interdisciplinary collaboration is needed to develop sustainable solutions, accelerate antibiotic discovery, and address the global AMR crisis.
Possible Thrombus-clearing Mechanism and Modification Suggestion of β-sitosterol.
Li S, Jiang Y, Yu W … +8 more , Wang Z, Han Q, Zhou Z, Wang S, Zhang M, Liu W, Liang L, Hu J
Curr Drug Targets · 2026 Jan · PMID 41510722 · Publisher ↗
INTRODUCTION: Thrombin (THR) is a key therapeutic target for anticoagulant therapy, yet the mechanism of β-sitosterol, a natural compound with antithrombotic potential, remains unclear. METHODS: This study integrated AI-...
INTRODUCTION: Thrombin (THR) is a key therapeutic target for anticoagulant therapy, yet the mechanism of β-sitosterol, a natural compound with antithrombotic potential, remains unclear. METHODS: This study integrated AI-driven structural alignment, molecular docking, Molecular Dynamics (MD) simulations, binding free energy calculation, and Density Functional Theory (DFT) calculations to elucidate the recognition mechanism between THR and β-sitosterol. RESULTS: Simulations revealed that β-sitosterol binding is stabilized primarily by hydrophobic and van der Waals interactions, leading to the closure of the active site and conformational changes in the EF_loop (i.e., γ-loop). The large conformational changes within EF_Loop may be dominated by weak interactions between W168/ P184/ Q183/ S185 and the ligand β-sitosterol. Based on these insights, a series of novel sterol derivatives was designed with improved binding affinity and predicted antithrombotic activity, as indicated by the lowest binding free energy. DISCUSSION: This study not only reveals molecular recognition and inhibitory mechanism of βsitosterol at the atomic level, but also provides suggestions for structural optimization of novel inhibitors against human thrombin. Future work should include in vitro binding assays and in vivo functional studies to confirm the inhibitory activity. CONCLUSION: The conformational change of EF_loop with the recognition of β-sitosterol effectively occludes the catalytic site, thereby impairing thrombin's proteolytic activity. Among 13 designed sterol derivatives, the compound d3 was identified as a promising inhibitor with excellent ADMET properties. This work provides an anticoagulant mechanism for the dynamic identification of βsitosterol and supports the rational design of allosteric THR inhibitors.
Targeting STAT3 in Breast Cancer Using Innovative Natural and Synthetic Scaffolds to Trigger Apoptosis, Autophagy, and Halt Tumor Progression.
Jayadevappa B, Dinesh D, Nagalakshmi A … +21 more , Paramesh TC, Shivaprakash VK, Venkatesh P, Devarajanayaka AH, Krishna AH, Shivanna AA, Chandru CA, Agasimane H, Anthony J, Subhan NJ, Sab NU, Rangaswamy Y, Puttaraju Y, P R HV, Kandula DR, Amiranova KT, Y PR, Hidayathulla S, Nikolenko VN, Basappa B, Beeraka NM
Curr Drug Targets · 2026 Jan · PMID 41510721 · Publisher ↗
INTRODUCTION: Signal Transducer and Activator of Transcription 3 (STAT3) is a key mediator in Breast Cancer (BC) progression, contributing to tumor proliferation, metastasis, survival, and resistance to chemotherapy. Pho...
INTRODUCTION: Signal Transducer and Activator of Transcription 3 (STAT3) is a key mediator in Breast Cancer (BC) progression, contributing to tumor proliferation, metastasis, survival, and resistance to chemotherapy. Phosphorylation of STAT3 at tyrosine 705 promotes its dimerization and nuclear translocation, where it activates oncogenic transcriptional programs. Due to its central role in BC pathogenesis, STAT3 has emerged as a promising molecular target for therapeutic intervention. To synthesize, characterize, and evaluate the anticancer efficacy of synthetic and natural compounds with a focus on their ability to inhibit STAT3 phosphorylation, suppress breast cancer cell proliferation, and induce apoptosis and autophagy. METHODS: A comprehensive literature review was conducted using databases such as PubMed, Scopus, Relemed, and ResearchGate. Relevant studies were identified that examined the synthesis, molecular mechanisms, and therapeutic potential of STAT3 inhibitors. Synthetic derivatives and phytochemicals were considered for their inhibitory effects on STAT3 activation and associated cellular outcomes in breast cancers. RESULTS: Several synthetic and natural compounds demonstrated significant inhibitory effects on STAT3 phosphorylation, leading to reduced breast cancer cell proliferation, migration, and survival. These agents effectively induced apoptosis and, in some cases, autophagy, highlighting their multifaceted anti-tumor mechanisms and elucidating the potential of these compounds as lead candidates for further preclinical and clinical development. CONCLUSION: Targeting STAT3 can be a significant therapeutic strategy, as both synthetic and natural compounds capable of inhibiting STAT3 signaling have been shown in preclinical studies. These findings provide valuable insights for cancer biologists, molecular researchers, and clinicians to explore STAT3 inhibitors as potential breast cancer therapeutics.
Identification of Natural Inhibitors against the Mycobacterium tuberculosis Proteasome: Computational Study.
Alhodieb FS
Curr Drug Targets · 2026 Jan · PMID 41508963 · Publisher ↗
INTRODUCTION: Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major public health challenge. In this study, the Mtb proteasome was targeted as a promising site for novel drug development. METHODS...
INTRODUCTION: Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major public health challenge. In this study, the Mtb proteasome was targeted as a promising site for novel drug development. METHODS: A total of 190,295 natural compounds from the ZINC database were screened using a systematic approach involving Lipinski's rule of five, SwissADME, pkCSM analysis, PyRx, and molecular dynamics simulation to identify potential drug candidates. RESULTS: Finally, five compounds, namely, ZINC14688701, ZINC299835179, ZINC14638395, ZINC299839873, and ZINC14638400, were identified based on physicochemical, pharmacokinetics, drug-likeness properties, and free energy of binding. Among these, ZINC14688701 showed the highest free energy of binding (-9.3 kcal/mol) with the selected target Mtb proteasome through the amino acid residues Thr1, Arg19, Ser20, Thr21, Val31, Lys33, Gly47, Thr48, Ala49, Leu99, Ser141, and Ala180. DISCUSSION: Finally, the complex 'Mtb proteasome-ZINC14688701' was studied using Molecular Dynamics simulation (MD simulation) for 50 ns, in which RMSD, RMSF, Rg, H-bonds, and SASA showed complex stability. Physicochemical evaluations revealed that the compounds are non-toxic with favorable drug-likeness. Exploring the antibacterial natural inhibitors offers a promising strategy for novel drug development against infectious diseases. CONCLUSION: These findings suggest a potential inhibitor of Mtb proteasome that could be used for TB treatment.
PDMD: A Comprehensive Repository of Plants Reported for Skeletal Muscle-related Ailments.
Gupta A, Chawla S
Curr Drug Targets · 2026 Jan · PMID 41508962 · Publisher ↗
INTRODUCTION: Medicinal plants and phytocompounds targeting skeletal muscle wasting in humans are under-represented in the majority of databases reporting plant/herb-diseases association. However, a large body of literat...
INTRODUCTION: Medicinal plants and phytocompounds targeting skeletal muscle wasting in humans are under-represented in the majority of databases reporting plant/herb-diseases association. However, a large body of literature exists wherein plant extracts or active pharmaceutical ingredients thereof demonstrate potential benefit in skeletal muscle wasting diseases across model organisms. Underscoring the relevance of a repertoire documenting such medicinal plants, we introduce PDMD (Plants Database for Muscle Wasting Diseases), a manually curated plants database reported for muscle wasting diseases such as cachexia, sarcopenia, muscle atrophy, muscle frailty, impaired muscle regeneration, and muscle fatigue. METHODOLOGY: PDMD was developed through systematic manual collection and curation of published studies from PubMed, Science Direct, etc, retrieving literature on plants conferring pharmacological efficacy against muscle wasting across experimental model organisms. Phytochemical and taxonomic information were extracted via tools like ClassyFire, PubChem. To handle the storage of an annotated listing of plants, MS-Excel and MySQL were used. Frontend was designed in Visual Studio Code and HTML/CSS. An Apache/PHP server was used to integrate MS-Excel data and charts. RESULT AND DISCUSSION: PDMD encompasses 206 medicinal plants, 230 API reported across 18 model organisms, offering taxonomical information, phytochemical classes, SMILES structure, geographical distribution, and other bioactivity indications. PDMD is cross-referenced with standard databases such as PubChem and PubMed for enhanced functionality. PDMD highlights overlooked plant-muscle links, bridging ethnopharmacology and botany gaps, and can aid hypothesis generation for novel therapies. CONCLUSION: PDMD highlights overlooked plant-muscle links, bridging ethnopharmacology and botany gaps, and can aid hypothesis generation. PDMD is freely available at https://www.jiit.ac.in/biotechhighlightes/Research-Databases/PDMD/index.html, and was last updated in September 2025.
An In Silico Design, Simulation, Virtual Screening, and Evaluation of Natural Products as Inhibitors of Breast Cancer-Causing Kallikrein11 Protein and Comparison of Binding Affinities with Approved Drugs.
Kondaparthi V, Malkhed V, Damera T … +3 more , Bingi ML, Gangidi P, Mustyala KK
Curr Drug Targets · 2026 Jan · PMID 41503904 · Publisher ↗
INTRODUCTION: The current study aims to determine the structure of the protein Kallikrein 11 and to screen for small natural product ligands to identify inhibitors of Kallikrein 11. Kallikreinrelated peptidase 11 (KLK 11...
INTRODUCTION: The current study aims to determine the structure of the protein Kallikrein 11 and to screen for small natural product ligands to identify inhibitors of Kallikrein 11. Kallikreinrelated peptidase 11 (KLK 11) belongs to the Kallikrein family of Serine proteases. Kallikrein 11 is a multifunctional protease. In addition to causing cancer, this plays a critical role in a variety of physiological functions, including blood pressure regulation, sperm liquefaction, and skin desquamation. This study aims to identify the protein's 3D structure, perform virtual screening with a natural product database, and find ADME characteristics for the most desirable ligand retrieved. Additionally, it aims to evaluate the effectiveness of binding affinity-based scoring systems in differentiating active KLK11 inhibitors from decoy compounds through the use of Receiver Operating Characteristic (ROC) analysis. METHODS: Using homology modelling protocols, the theoretical model of Kallikrein 11 will be predicted, and the resulting structure will be validated by several server tools. To identify new scaffold compounds that are effective against Kallikrein 11, the active site is examined, and the ligand database is used for virtual screening. The ROC-Area Under the Curve (AUC) is used to assess the effectiveness of inhibitors. RESULTS: The HIS94, ASP142, and SER235 residues in the KLK 11 protein are essential as the active site triad, and residues from GLY24 to ASN281 were chosen as a pocket for ligand molecule binding, according to the results of the virtual screening. With an AUC of 0.837, the results show a strong predictive ability, indicating that binding affinity is a trustworthy parameter for early virtual screening pipelines that target KLK11. Given its superior ADME qualities, the scaffolds containing the polyphenols and flavone pharmacophores were recognized as a potential lead drug against the KLK 11 protein. DISCUSSION: The findings confirm the reliability of the homology-modelled KLK11 structure and demonstrate that its catalytic triad and binding pocket can effectively distinguish active scaffolds through virtual screening. The strong ROC-AUC value indicates that binding-affinity-based selection is robust for early inhibitor discovery. Notably, the natural-product scaffolds displayed higher binding affinities than approved drugs, highlighting their potential as superior KLK11 inhibitor candidates. CONCLUSION: The research results demonstrated that the chosen ligand molecules with ADME parameter values are more acceptable medications, highlighting the ligand molecules' drug-like activity through the inhibition of KLK 11 protein. The identification of novel therapeutic scaffolds for cancer is aided by structural data, active site details, specific ligand molecules, and ROC-AUC of inhibitors.
Biomarkers as Drivers of Innovation in Modern Diagnostics and Therapeutics.
Soni S, Rathee S, Jain SK
Curr Drug Targets · 2026 Jan · PMID 41486997 · Publisher ↗
INTRODUCTION: Biomarkers have revolutionized diagnostics and therapeutics by enabling early detection, prognosis, and treatment monitoring across a range of diseases, including cancer and neurodegenerative disorders. The...
INTRODUCTION: Biomarkers have revolutionized diagnostics and therapeutics by enabling early detection, prognosis, and treatment monitoring across a range of diseases, including cancer and neurodegenerative disorders. Their role in personalized medicine underscores their importance in modern healthcare. METHODS: This review consolidates findings from diverse sources, exploring the classes, mechanisms, and emerging technologies for biomarker discovery. Techniques such as next-generation sequencing, immunohistochemistry, and mass spectrometry were critically evaluated for their efficiency in biomarker validation. RESULTS: The study identifies various cancer biomarkers, including genetic, proteomic, and metabolomic markers, and highlights their clinical applications. It underscores significant breakthroughs in non-invasive diagnostic tools, such as exosomal proteins, miRNAs, and saliva-based markers. Challenges such as limited sample sizes, regulatory hurdles, and clinical translation bottlenecks were also discussed. DISCUSSION: Despite significant advancements, integrating biomarkers into clinical practice remains challenging due to issues of specificity, sensitivity, and cost-effectiveness. Emerging approaches such as immune checkpoint inhibitors, tumor mutational burden assessments, and chemokine profiling have shown potential in enhancing cancer immunotherapy outcomes. CONCLUSION: Biomarkers are pivotal in advancing personalized medicine by refining diagnostic and therapeutic strategies. Addressing current limitations through innovative technologies and interdisciplinary collaboration can unlock their full potential, transforming disease management and patient care.
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