Abstract: Druggable proteins are proteins that can be specifically bound and modulated by drug molecules, with such modulation expected to produce therapeutic effects. The identification and validation of druggable proteins are central steps in modern drug discovery. With the rapid advancements in biological big data and artificial intelligence, computational methods based on bioinformatics have become essential for large-scale screening of druggable proteins. This review systematically summarizes the latest research progress in this field, providing a comprehensive analysis across three dimensions: data resources, feature engineering, and predictive models. The main contributions are 4-fold: First, we systematically describe three major types of databases: pharmacological annotation databases, quantitative affinity databases, and multi-source integrated databases, and dataset construction strategies as well as strategies for handling imbalanced samples are explored. Second, multi-level feature representations across four dimensions are categorized into sequencederived features, physicochemical properties, evolutionary information, and structural information, and the corresponding methods and tools are summarized. Third, we provide a detailed review of the evolution and application paradigms of predictive models, from classical machine learning and ensemble learning to deep learning architectures and protein large language models. Fourth, based on a systematic evaluation of representative studies, current limitations in areas such as few-shot learning and model interpretability are highlighted, and offer a forward-looking perspective on future research directions. This review aims to serve as a comprehensive reference for druggable protein prediction algorithms and to provide a solid theoretical and technical roadmap for computationally driven discovery of novel drug targets.
Introduction: Liquiritigenin (LQ), a bioactive flavonoid derived from licorice, exhibits a wide range of pharmacological activities. This review comprehensively summarizes the therapeutic potential of LQ and elucidates the molecular mechanisms underlying its principal effects, including hepatoprotective, anticancer, anti-inflammatory, cardioprotective, neuroprotective, and boneprotective activities. Methods: A literature search was conducted using PubMed, ResearchGate, and Web of Science. Studies investigating the therapeutic efficacy of LQ and related signaling pathways were selected for critical analysis. Results: LQ exerts diverse pharmacological effects through coordinated regulation of multiple signaling pathways. Its anti-inflammatory is primarily associated with suppression of NF-κB signaling and NLRP3 inflammasome, coupled with upregulation of the Nrf2-dependent antioxidant pathway. Anticancer effects involve suppression of tumor growth, metastasis, and survival through modulation of ER, ERK, PI3K/AKT/mTOR, HSP90, and glutamate receptor signaling pathways. Hepatoprotection is facilitated through PI3K/AKT-driven metabolic regulation and inhibition of TGF-β1/Smadmediated fibrotic processes. Neuroprotective effects are linked to ERβ activation, stimulation of the BDNF/ERK/CREB axis, and downregulation of PI3K/AKT/mTOR signaling. Cardioprotection involves attenuation of fibrosis, oxidative stress, and calcium overload. In the skeletal system, LQ promotes osteogenesis while inhibiting osteoclast activity. Additional protective effects have been documented in renal, testicular, cutaneous, and embryonic tissues through diverse signaling pathways. Discussion and Conclusion: This review consolidates evidence for the multifaceted pharmacological activities of LQ and provides a mechanistic synthesis of its actions. These findings offer a valuable framework for future preclinical and translational investigations while highlighting important opportunities and challenges for further development.
Introduction: The emergence of Monkeypox Virus (MPXV) as a major global health concern underscores an urgent unmet need for innovative antiviral therapeutics. To address this need, a novel large-scale in silico screening strategy was adopted to identify highly potent antiviral cyclic peptides that inhibit the A42R profilin-like protein of monkeypox virus. Methods: A total of 5,115 cyclic peptides were initially screened using Tanimoto similarity analysis, followed by data clustering to ensure structural diversity. From this, 500 representative peptides were selected and subjected to molecular docking against the A42R profilin-like protein. Subsequently, density functional theory calculations were performed to evaluate electronic properties. The topranked peptides were further analyzed using 300 ns molecular dynamics simulations conducted in triplicate to ensure reproducibility. Advanced analyses, including steered molecular dynamics, umbrella sampling, and MM/GBSA binding free energy calculations, were performed to assess the stability and binding affinity of the peptide–protein complexes. Results: Molecular docking identified 12 cyclic peptides with binding energies ≤ −6.0 kcal/mol (−6.5 to −6.1 kcal/mol), with CycPept_5184 showing the lowest score (−6.5 kcal/mol). Molecular dynamics simulations revealed that CycPept_3468 and CycPept_4348 maintained stable binding (RMSD of 1 nm), whereas CycPept_5184 and CycPept_5604 exhibited large fluctuations (up to 10 nm), indicating dissociation after 40 ns. MM/GBSA analysis confirmed favorable binding for both stable complexes, with CycPept_4348 showing a more negative binding free energy (−31.94 ± 5.01 kcal/mol) than CycPept_3468 (−26.09 ± 3.74 kcal/mol), driven primarily by stronger electrostatic interactions. Discussion: A multi-step computational screening strategy has been successfully used to narrow the large peptide library down to only two potent cyclic peptides. The combination of techniques in this simulation, including docking simulations, DFT methods, long-timescale MD simulations, and binding free energy calculations, improves the reliability of the predicted binding interactions. Conclusion: The objective of the present study was to identify cyclic peptides CycPept_3468 and CycPept_4348, which showed excellent inhibitory activity against the MPXV A42R profilin-like protein. The high binding affinity and structural stability of the peptides indicate their potential efficacy as antiviral drugs.
Introduction: Triple-negative breast cancers (TNBCs) are a type of breast cancer (BC) characterized by the absence of ER, PR, and HER2 expression. They account for 10-15% of invasive BC cases and are known for being aggressive and highly metastatic. TNBC patients face limited effective treatment options due to the inherent heterogeneity of the disease and a lack of targetable receptor molecules. Methods: Chemotherapy, used as part of neoadjuvant or adjuvant therapy, remains the major treatment recourse but is associated with toxicity, resistance, and relapse. Unlike other BCs, TNBCs' tumor microenvironment (TME) features many tumor-associated antigens (TAAs) and significant lymphocyte infiltration, such as Tc cells and other immune cells, e.g., NK cells. The collection of relevant studies herein was done by typing the keywords “Targeted Immunotherapy for Triple Negative Breast Cancer” on Google and PubMed databases, which were henceforth retrieved with a focus on recent attempts. Results: TNBCs are considered immunologically "hot". However, the presence of significant immunosuppressive cells, including Tregs, TAMs, and MDSCs, along with inhibitory cytokines, such as IL- 10 secreted by these cells, expression of immunosuppressive molecules, such as PD-1, PD-L1, and CTLA-4, weakens the anti-tumor response through immunosuppressive actions. Discussion: TNBC-TME is a target for immunotherapy. Current immunotherapeutic strategies target the TNBC TME using immune checkpoint inhibitors (ICIs) against PD-1, PD-L1, and CTLA-4. Additionally, several studies focus on developing vaccines targeting immunosuppressive cells and molecules of the TNBC TME. Conclusion: This review highlights advancements in immunotherapy strategies for mitigating TNBC, with a particular focus on targeting immunosuppressive molecules.
INTRODUCTION:Cancer progression is sustained by complex interactions between oncogenic signaling pathways and immune checkpoint networks, yet their mechanistic crosstalk remains poorly integrated in existing reviews. This review synthesises the bidirectional regulatory relationships between oncogenic signaling and immune checkpoints, with emphasis on mechanistic interdependencies, therapeutic resistance, and precision oncology strategies. METHODS:A narrative review of published literature was conducted covering PI3K/AKT/mTOR, RAS/MAPK, and JAK/STAT oncogenic pathways; immune checkpoints including PD-1/PD-L1, CTLA-4, LAG-3, TIM-3, and TIGIT; tumour microenvironment interactions; multi-omics integration; pharmacogenomics; and AI-driven drug discovery platforms. RESULTS:Three core crosstalk axes were identified. First, the PI3K/AKT-PD-L1 axis: AKT-mediated GSK-3β inactivation stabilises PD-L1 protein, and PTEN loss constitutively amplifies surface PD-L1 expression, suppressing T-cell cytotoxicity. Second, the MAPK-immune suppression axis: sustained ERK signalling downregulates MHC class I and TAP1/TAP2 components, while BRAF V600E drives secretion of immunosuppressive cytokines including VEGF and IL-10. Third, the JAK/STAT-PD-L1 axis: IFN-γ-driven JAK1/JAK2 activation induces PD-L1 transcription via STAT1, while JAK loss-of-function mutations confer acquired resistance to anti-PD-1 therapy by abrogating MHC-I re-expression. DISCUSSION:These crosstalk mechanisms explain why tumours with high oncogenic signalling burden consistently show attenuated immunotherapy responses and provide the molecular rationale for combination targeting strategies. Multi-omics integration, pharmacogenomic biomarkers including MSI-H status and PIK3CA mutation, and AI-guided modelling frameworks offer structured approaches for translating these findings into clinically actionable patient stratification decisions. CONCLUSION:Rational combination strategies co-targeting oncogenic signalling and immune checkpoints, guided by multi-omics profiling and biomarker-driven patient stratification, represent the most promising approach for achieving durable precision oncology outcomes.
Introduction: Cancer remains a major global health challenge, and quercetin, a widely distributed dietary flavonoid, has attracted increasing attention for its anti-inflammatory, antioxidant, and neuroprotective properties in oncology research. Methods: This narrative review synthesizes recent preclinical and clinical evidence on quercetin for cancer prevention and treatment, with an emphasis on its adjuvant role, toxicity-modulating effects, and formulation strategies designed to improve delivery. Results: Quercetin has been reported to enhance the activity of several chemotherapeutic agents by modulating apoptosis, drug-resistance mechanisms, and key signaling pathways; moreover, it may reduce treatment-related nephrotoxicity, cardiotoxicity, reproductive toxicity, and neurotoxicity. Nevertheless, clinical translation remains limited by poor aqueous solubility, reduced stability, rapid metabolism, and low bioavailability. In addition, clinical trial data remain sparse, and many completed studies have not yet reported outcomes. Discussion: Consequently, advances in delivery systems, including nanoformulations, liposomes, and micelles, may improve quercetin stability, absorption, and tumor targeting. Conclusion: Overall, quercetin appears to be a promising adjunct in oncology; however, stronger clinical evidence and optimized delivery strategies are required to define its therapeutic value.
Introduction: Considering the shared physiological mechanisms between Alzheimer’s disease (AD) and Parkinson’s disease (PD), it is plausible that certain compounds may exert therapeutic effects on both neurological disorders. This study aimed to employ in silico techniques to investigate the pharmacological mechanisms of huperzine A (HA) as an alternative treatment for PD and AD. Methods: Molecular targets of HA and genes associated with AD and PD were identified from public databases. Gene Ontology analysis, metabolic pathway analysis, and protein-protein interaction (PPI) network construction were performed to identify shared molecular targets. Molecular docking was performed to assess HA affinity for hub proteins and to compare it with that of drugs used to treat AD and PD. Results: The results suggested that HA interacts with 77 molecular targets common to both diseases. Enrichment analysis revealed that proteins from these targets were involved in biological functions, such as serotonin and amine binding. Hub proteins (SRC, TP53, AKT1, and CASP3) were identified from the PPI network. Furthermore, molecular docking simulations showed favorable binding of HA to the hub proteins and adequate binding to the targets of standard drugs (MAOB and ACHE). On the other hand, molecular dynamics analyses were performed to compare the binding characteristics of HA with those of the control targets. Discussion: HA may modulate SRC, CASP3, and AKT1, suggesting a pleiotropic mechanism underlying the association between AD and PD. These computational findings provide a rational basis for experimental validation by modulating signaling pathways implicated in inflammatory processes and inhibiting enzymes involved in neurotransmitter degradation. Conclusion: This study contributes to the understanding of the neuroprotective activity of HA in AD and PD. However, further in vitro and in vivo investigations are required to confirm the dual therapeutic potential of HA in the treatment of AD and PD.
Background: It is always a daunting task to treat urinary tract infection (UTI) as these infections may be chronic or lead to complications and drug resistance. The bacteria form a biofilm, which results in the failure of the antibiotics. The common organisms include Escherichia coli, Klebsiella, and Enterococcus. Gepotidacin is considered to be the first-in-class oral triazaacenaphthylene bacterial topoisomerase inhibitor (NBTI). Recently, it was approved by the FDA for treating uncomplicated urinary tract infections in females aged 12 years. Objective: This literature review aims to evaluate current evidence on the clinical efficacy, safety, dosing, and resistance profile of gepotidacin in the treatment of urinary tract infections. Methods: A literature search was conducted using PubMed, Cochrane Library, Google Scholar, and Scopus to identify original and review articles published from 1990 to the present. The search was refined using the keywords: Gepotidacin, drug, DNA gyrase inhibitor, antibiotic, broad spectrum, and UTI. Results: In this review, we discuss the recently approved drug gepotidacin and highlight its action in UTIs. The drug acts on the enzyme targets such as DNA gyrase and topoisomerase IV, thereby inhibiting the DNA replication of bacteria. Interestingly, the drug acts on both gram-positive and gram-negative bacteria. Discussion: The efficacy of gepotidacin against common uropathogens makes it a popular choice for treating urinary tract and urogonorrheal infections. The drug is well-tolerated with fewer side effects and is hence considered to be safe. Conclusion: Considering the cases of antibiotic resistance and novel mechanisms of action, the broad-spectrum action of gepotidacin may be beneficial in treating UTIs.
The growing global burden of cardiovascular diseases necessitates the exploration of novel and complementary therapeutic strategies. Hawthorn (Crataegus spp.), a traditional herbal medicine, has gained considerable attention for its potential cardioprotective properties. This review provides a comprehensive overview of the botanical profile, phytochemical composition, and pharmacological activities of hawthorn, highlighting its role as a naturally derived cardiotonic agent. The therapeutic effects of hawthorn are primarily attributed to its bioactive constituents, particularly flavonoids and oligomeric proanthocyanidins, which exhibit vasodilatory, antioxidant, mild positive inotropic, and antiarrhythmic properties. Evidence from preclinical studies and selected clinical investigations suggests that hawthorn may support cardiovascular function, including improvements in exercise tolerance, endothelial function, and symptom management in conditions such as mild-tomoderate heart failure, hypertension, and angina. However, it is important to note that the current evidence is largely derived from secondary sources, including preclinical data and limited clinical trials, and does not establish hawthorn as a curative or standalone therapy. Compared with synthetic cardiotonic agents, hawthorn demonstrates a favorable safety profile, though variability in extract composition and dosing remains a significant limitation. Overall, while hawthorn shows promise as an adjunctive therapy in cardiovascular disease management, further well-designed, large-scale clinical studies and standardized formulations are required to validate its efficacy, clarify mechanisms of action, and support its integration into evidence-based clinical practice.
INTRODUCTION:Sanzi Decoction, a traditional Mongolian medicinal formula composed of Gardeniae Fructus, Chebulae Fructus, and Toosendan Fructus, has long been used in the treatment of hypertension. However, the specific active components and underlying therapeutic mechanisms remain to be fully elucidated. METHODS:Active compounds and their corresponding targets of Sanzi Decoction were screened from TCMSP, and hypertension-related targets were retrieved from GeneCards, DisGeNET, and OMIM. The shared targets between Sanzi Decoction and hypertension were subjected to GO and KEGG enrichment analyses. A protein-protein interaction network in combination with four machine learning algorithms, including LASSO, random forest, SVM-RFE, and RF-RFE, was employed to robustly identify core targets. Subsequently, molecular docking and molecular dynamics simulations were employed to predict and evaluate the binding affinity and stability of key compound-target complexes. RESULTS:A total of 23 bioactive compounds and 164 targets associated with Sanzi Decoction were identified, among which 81 overlapped with hypertension-related targets. Network pharmacology analysis identified four key compounds, including quercetin, kaempferol, (R)-(6-methoxy-4- quinolyl)-[(2R,4R,5S)-5-vinylquinuclidin-2-yl]methanol, and stigmasterol. Enrichment analysis revealed that the intersected targets were involved in key cardiovascular pathways, including atherosclerosis and the AGE-RAGE signaling pathway. Machine learning-assisted protein-protein interaction identification converged on three central targets: EGFR, ESR1, and TP53. Molecular docking and dynamics simulations suggested stable binding interactions within the EGFR-ligand complexes and the ESR1-quercetin complex, implying their potential physiological relevance. DISCUSSION:This study systematically identified the key bioactive components and potential therapeutic targets of Sanzi Decoction for hypertension therapy through data mining, offering theoretical evidence-based support for its therapeutic use. Nevertheless, given the in silico nature of these findings, further in vitro and in vivo investigations are warranted to validate the pharmacological mechanisms. CONCLUSION:Sanzi Decoction may exert antihypertensive effects via key compounds targeting EGFR, ESR1, and TP53 and modulating atherosclerosis and AGE-RAGE pathways, providing evidence- based support for its therapeutic potential.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
