INTRODUCTION:Breast cancer remains a critical global health issue, particularly in patients with BRCA1/2 mutations, which lead to genomic instability and increased cancer susceptibility. While PARP inhibitors targeting PARP1 and PARP2 have shown clinical success through synthetic lethality, PARP15, a mono-ADP-ribosyltransferase involved in DNA repair and tumour progression, remains largely understudied. METHODS:A structure-based virtual screening approach was applied to identify potential PARP15 inhibitors. The screening was performed on a Bioactive Screening Compound Library consisting of over 12,200 druglike small molecules. Using the MTiOpenScreen platform, 1,500 candidate compounds were initially shortlisted. Molecular docking was then conducted to identify top-binding compounds, followed by 500- nanosecond molecular dynamics simulations to assess complex stability. Principal component analysis (PCA), free energy landscape (FEL) evaluation, and absorption, distribution, metabolism, and excretion (ADME) profiling were also performed to characterise compound behaviour and drug-likeness. RESULTS:Three compounds, F2002-0551, F2028-0309, and F1495-1822, emerged with docking scores surpassing the known PARP15 inhibitor, Niraparib. Molecular dynamics simulations confirmed their structural stability with low RMSD values and favourable FELs. PCA revealed consistent ligand dynamics, and ADME analysis showed high gastrointestinal absorption and other drug-like characteristics. Superimposition analysis demonstrated minimal deviation in docked poses, indicating strong and stable interactions with PARP15. DISCUSSION:These results highlight the therapeutic potential of the selected compounds as novel PARP15 inhibitors. Their favourable binding stability and pharmacokinetic profiles support their candidacy for further development against BRCA-mutated breast cancer. CONCLUSION:F2002-0551, F2028-0309, and F1495-1822 represent promising leads for PARP15 inhibition. This study offers a computational foundation for future experimental validation and therapeutic exploration in BRCA-associated breast cancer.

Hepatitis C virus (HCV) remains a major global health burden, and resistance-associated substitutions in the NS5B RNA-dependent RNA polymerase (RdRp) limit the long-term efficacy of current direct-acting antivirals. Therefore, identification of novel inhibitors with improved stability and drug-like properties is urgently needed. A comprehensive multistage in silico strategy was implemented, integrating machine-learning–driven QSAR modeling with structure-based docking, long-timescale molecular dynamics simulations, MM-GBSA free-energy estimation, pharmacokinetic profiling, and hybrid QM/MM calculations. A curated dataset of 2,241 experimentally validated NS5B inhibitors was used to develop a support vector regression (SVR)-based QSAR model (5-fold CV R² = 0.8635; R²_train = 0.8619; R²_test = 0.8727; R²_external = 0.8654). The validated model screened 2,460 natural compounds, and the top-ranked candidates were docked against NS5B (PDB ID: 3G86), followed by 300 ns MD simulations and electronic-level interaction analysis. QSAR screening identified 342 compounds exceeding the µ + σ activity threshold. Docking analysis revealed several potential hits, among which HC2 showed favorable binding energy (− 10.0 kcal/mol) and key interactions with TRP397, VAL144, ARG394, GLU143, and HIS402. MD simulations confirmed structural stability, with consistent RMSD, RMSF, Rg, SASA, and hydrogen-bond profiles. MM-GBSA analysis indicated favorable binding free energy (− 18.80 ± 4.81 kcal/mol). QM/MM calculations indicated favorable ligand–protein interactions for HC2, with an interaction energy of − 13.61 kcal/mol. ADMET profiling indicated a generally favorable predicted profile, although some limitations were observed. HC2 emerged as a promising NS5B inhibitor candidate, demonstrating stable binding, favorable thermodynamics, and improved drug-like properties, warranting further experimental validation.

Background:CXCL12 is a critical chemokine involved in immune cell trafficking and tumor metastasis through its interaction with CXCR4 and CXCR7. The C55Y mutation in CXCL12 is hypothesized to disrupt its structure and function. Unlike previously reported CXCL12 mutations that affect transcriptional regulation or single-receptor binding, C55Y targets a conserved cysteine residue essential for a structural disulfide bridge, potentially inducing unique global destabilization. This study investigates the molecular consequences of the C55Y mutation using computational tools. Objectives:This study aimed to evaluate the structural and functional impact of the C55Y mutation in CXCL12, particularly its interactions with CXCR4 and CXCR7, and its relevance to prostate cancer pathogenesis. Methods:Molecular dynamics simulations (MDS), evolutionary conservation analysis, and molecular docking with CXCR4 and CXCR7 receptors were performed to assess the impact of the C55Y mutation. Tools such as I-TASSER, Meta-SNP, and PolyPhen-2 were used to analyze structural stability, while HDOCK and Schrödinger simulations assessed receptor binding. RMSD and RMSF calculations were used to evaluate protein dynamics. Results:The C55Y mutation induces significant structural instability in CXCL12, with increased RMSD and altered secondary structure. Molecular dynamics simulation further demonstrated the stability of the complexes through RMSD, RMSF, hydrogen bond, and Radius of Gyration (RoG) analyses, where the normal complexes exhibited comparatively stable structural compactness during the simulation period. Docking studies showed reduced binding affinity to CXCR4 and CXCR7, indicating disrupted receptor interactions. Notably, this dual-receptor binding loss distinguishes C55Y from other mutations that typically impair only CXCR4 signaling. These findings suggest that the mutation impairs CXCL12's function in prostate cancer, metastasis of prostate cancer, and immune response. Conclusion:The C55Y mutation in CXCL12 disrupts its structural integrity and receptor binding, uniquely compromising both the CXCR4 and CXCR7 pathways. This highlights its potential role in prostate cancer progression through mechanisms distinct from previously characterized CXCL12 variants. This study provides insights into the molecular mechanisms of CXCL12-mediated signaling and its implications for future therapeutic strategies targeting chemokine signaling to inhibit prostate cancer.

Cancer is one of the leading causes of global mortality. To reduce treatment costs, improve quality of life and increase survival outcomes for an individual, early detection of cancer is crucial. Advances in nanobiosensors offer point-of-care detection with high specificity and sensitivity for biomarkers associated with tumour detection. Such biosensors also support personalised approaches to cancer treatment. Some nanosensors might be developed as theranostics, where they deliver therapeutic molecules or aid in therapy via mechanisms like photothermal ablation, sonodynamic therapy or precise targeting of therapeutic molecule to the tumor site. A comprehensive review is presented where the latest advances in nanoparticle based sensors are discusses. To examine emerging nanotechnology-driven biosensing approaches for cancer detection, a comprehensive review that encompass the detailed modus operandi and advantages and disadvantages and advancements in Nanoparticle-based biosensors, Paramagnetic nanoparticle-based biosensor, Quantum dots, Nano-shells-based biosensor, Gold nanoparticle-based biosensor, Nanowire-based biosensors, Nanorods, Carbon Nanotube Based Biosensors, Nanocantilever-based based biosensor, Nanocomposite based biosensors, NanoVelcro based biosensors, Nanozymes, and Amperometric Sensor is presented. This review is based on a comprehensive analysis of published literature related to advanced nanomaterial-based biosensors for cancer diagnosis. Relevant research articles related to cancer detection, review papers, and reports were collected from scientific databases such as NCBI, PubMed, Web of Science, and Google Scholar. Keywords including nanobiosensors, nanocomposites, nanocantilevers, nanowires, carbon-nanotubes, cancer biomarkers, nanoparticles, aptamer-based sensors, nanomaterials, and nano-shells, were used to access literature. Articles which are published mainly within the last few years were prioritized to highlight recent advancements. Applications of various biosensors in detecting different cancer types also has been given. Only articles those are peer reviewed and published in English literature have been included. Studies based on nanomaterials show that there is significant improvement in cancer detection. Additionally, the technology also enables early diagnosis, accurate imaging with the help of biomarkers, and targeted drug delivery. However, issues such as biocompatibility, clinical testing at a large scale, potential toxicity, and challenges related to its regulation remain some of its key limitations. Nanotechnology has significantly improved early cancer diagnosis via using highly sensitive and specific nanobiosensors. Despite challenges related to safety, cost, and clinical translation, continued research is essential to realize its full potential in cancer diagnostics and management.

Motivation:Cervical cancer remains a major global health challenge, particularly in low-resource settings where treatment efficacy is limited by drug resistance and toxicity. Although Panax notoginseng (Sanqi) has demonstrated anticancer activity, its molecular mechanisms against cervical cancer remain insufficiently understood. Results:An integrated transcriptomic and systems pharmacology approach was employed to investigate the therapeutic mechanisms of Panax notoginseng in cervical cancer. Transcriptomic analysis identified 533 overlapping differentially expressed genes associated with cell cycle regulation, DNA replication, cellular senescence, and p53 signaling. Network pharmacology revealed 291 overlapping targets between P. notoginseng compounds and cervical cancer-related genes. Protein-protein interaction analysis identified tumor necrosis factor, interleukin-6, proto-oncogene, non-receptor tyrosine kinase (SRC), TOP2A, and CDC45 as key hub genes involved in inflammation, apoptosis, and tumor progression. Molecular docking demonstrated strong binding affinities of ginsenoside Re, Panaxadiol, Daucosterol, and Stigmasterol toward core targets, while molecular dynamics simulations confirmed stable protein-ligand interactions. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis suggested comparable pharmacokinetic properties and low predicted toxicity. Availability and implementation:The datasets analyzed in this study are publicly available through the Gene Expression Omnibus database under accession numbers GSE63514 and GSE9750. Additional data supporting the findings of this study are available within the article and its Supplementary Materials.

Atherosclerosis has been increasingly recognized as a contributor to cognitive decline through mechanisms such as cerebral hypoperfusion, oxidative stress, and chronic inflammation. These mechanisms include cerebral hypoperfusion, which limits oxygen and nutrient supply to the brain; microvascular damage, which impairs small vessel function and blood-brain barrier integrity; chronic inflammation, which promotes neurodegeneration through sustained immune activation; and oxidative stress, which accelerates neuronal aging via mitochondrial dysfunction. This narrative review synthesizes findings from epidemiological studies, mechanistic research, and clinical trials to examine the interplay between atherosclerotic diseases and cognitive impairment. Shared risk factors, including hypertension, diabetes, hyperlipidemia, and smoking, accelerate neurovascular dysfunction and increase susceptibility to dementia. Advances in neuroimaging and biomarker research offer improved diagnostic precision, facilitating early detection and intervention. Preventive strategies, including lifestyle modifications, pharmacological therapies such as statins and antihypertensives, and cognitive rehabilitation, have the potential to mitigate cognitive deterioration associated with atherosclerosis. Despite accumulating evidence, vascular contributions to dementia remain underdiagnosed in clinical settings, highlighting the need for a multidisciplinary approach that integrates cardiovascular and neurological care. A comprehensive strategy encompassing risk stratification, early therapeutic intervention, and long-term monitoring is essential for improving cognitive outcomes in at-risk populations. Future research should focus on refining diagnostic methodologies, optimizing prevention and treatment protocols, and identifying high-risk individuals for targeted interventions. Given the rising global burden of both cardiovascular disease and dementia, a proactive approach addressing modifiable risk factors is critical to reducing morbidity and enhancing quality of life.

INTRODUCTION:This study presents a comprehensive exploration of the biomedical potential of the synthesized metal-organic framework Zn4O(BDC)3, focusing on its applications in cancer and diabetes treatment and its advanced drug delivery capabilities. METHODS:The structural and physicochemical properties of Zn4O(BDC)3 were characterized using FTIR, TGA, 1H NMR, PXRD, and elemental analysis, revealing its exceptional stability and coordination properties. Molecular docking, molecular dynamics simulations (100 ns), and MM-GBSA calculations were performed to assess binding affinities and stability. RESULTS:The interactions of Zn4O(BDC)3 with salmon sperm DNA (SSDNA) and bovine serum albumin (BSA) demonstrated significant anticancer potential, evidenced by binding constant values of 6.0 × 106M-1 and Gibbs free energy changes of -17.93 and -19.61 kcal/mol, respectively, highlighting its ability to suppress tumor cell proliferation. With doxorubicin (DOX) loading and reloading efficiencies of 88% and 87.5%, Zn4O(BDC)3 exhibited superior drug delivery capabilities. The anti-diabetic potential was validated by the formation of human insulin (HI) hexamers with ΔG values of 0.8 ± 0.1 and a significant decrease in absorption intensity (5.8 to 0.05 at 250 nm). Molecular docking studies revealed moderate to high binding affinities (-10.0 to -5.3 kcal/mol) with biomolecular targets, supported by molecular dynamics simulations over 100 ns and MM-GBSA calculations indicating robust stability (ΔG = -33.31 kcal/mol). CONCLUSION:These in-silico and in-vitro analyses underscore the significant pharmacological promise of Zn4O(BDC)3 as a multifunctional agent for anticancer, antidiabetic, and drug delivery applications.

The entry and infectivity of a virus are determined by its interaction with the host. SARS-CoV-2, the virus responsible for COVID-19, utilizes the spike (S) protein to attach to and enter host cells. Recent studies have identified neuropilin-1 (NRP1) as a crucial facilitator for the entry of SARS-CoV-2. The binding of the spike protein to the b1 domain of NRP1 has been shown to enhance viral infection twofold. Consequently, targeting NRP1 to disrupt this interaction represents a promising strategy to mitigate viral infection. In this study, a small molecule library of approximately 10,000 compounds was screened to identify those that could inhibit the interaction between NRP1 and the spike protein by targeting the b1 domain of NRP1. The crystallographic structure of the b1 domain of human NRP1 (PDB entry: 7JJC) was used for this purpose. Following virtual screening, docking studies, and evaluation of binding affinity and ADMET properties, 10 compounds were shortlisted. The top two candidates, AZD3839 and LY2090314, were selected for molecular dynamics simulation studies over 100 ns to assess binding stability. MM/GBSA calculations indicated that both AZD3839 and LY2090314 exhibited strong and stable binding to the b1 domain of NRP1. Computational modeling of the interaction between the b1 domain of NRP1 and the receptor-binding domain of the spike protein suggested that AZD3839 and LY2090314 could effectively hinder the NRP1-spike interaction. Therefore, these compounds may serve as potential drug candidates to reduce SARS-CoV-2 infectivity.

Renal carcinoma is a lethal cancer, researched by several studies to get insights into the molecular causes of disease, in order to come up with advanced therapeutic treatments. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), is an anticancer cytokine posing therapeutic effects to treat cancer. However, certain cancer types including renal cell carcinoma developed resistance towards TRAIL, hence limiting its usefulness in cancer treatment. Recently, synergistic approach has been emerged in clinical settings to sensitize cancer cells towards TRAIL treatment by combining with natural antioxidants and anti-inflammatory compounds for providing chemo-sensitizing effects. Hence, this study has used chemo-sensitizing effect of chrysoeriol for the very first time to sensitize renal carcinoma cell lines for treatment with TRAIL by synergistic treatment approach, in vitro. The effects of 20 μM chrysoeriol, 50 ng/mL TRIAL and their synergistic combination were investigated deeply by adopting different experimental strategies in vitro. Synergistic combination of 20 μM chrysoeriol/50 ng/mL TRIAL provided apoptosis of TRAIL resistant cell lines which was confirmed by increasing the expressions of caspases including caspase-3 and caspase-8 and caspase-9, increasing the expression of interleukins 10, while decreasing the expression of interleukins 6, triggering cellular apoptosis, inhibiting proteasome activity, lossing mitochondrial membrane potential and triggering cytchrome C release. Meanwhile, rise in death receptor 4 expression as well as up-regulation of pro-apoptotic and down-regulation of anti-apoptotic genes further provided evidence for chemo-sensitizing effect of chrysoeriol on TRAIL resistant renal carcinoma cells to trigger apoptosis. Hence, chrysoeriol could be employed in the anticancer drug development for therapeutic treatment of renal cancer.

Prostate cancer remains a significant oncological challenge, driven by molecular factors such as KLK3 (kallikrein-related peptidase 3). Text mining of 237,357 PubMed articles identified KLK3 as the most frequently cited protein (10,477 mentions in titles; 162,619 in abstracts), with strong co-mentions of AR, TMPRSS2, and ERG (χ2, *p* < 0.001). Structural modeling of KLK3 (PDB: 2ANY) using I-TASSER yielded a high-confidence 3D structure (C-score: 0.73), validated by Ramachandran analysis, with 99.5

The review focuses on the ways that ontologies are revolutionising precision medicine in their effort to understand neurodegenerative illnesses. Ontologies, which are structured frameworks that outline the relationships between concepts in a certain field, offer a crucial foundation for combining different biological data. Novel insights into the construction of a precision medicine approach to treat neurodegenerative diseases (NDDs) are given by growing advancements in the area of pharmacogenomics. Affected parts of the central nervous system may develop neurological disorders, including Alzheimer's, Parkinson's, autism spectrum, and attention-deficit/hyperactivity disorder. These models allow for standard and helpful data marking, which is needed for crossdisciplinary study and teamwork. With case studies, you can see how ontologies have been used to find biomarkers, understand how sicknesses work, and make models for predicting how drugs will work and how the disease will get worse. For example, problems with data quality, meaning variety, and the need for constant changes to reflect the growing body of scientific knowledge are discussed in this review. It also looks at how semantic data can be mixed with cutting-edge computer methods such as artificial intelligence and machine learning to make brain disease diagnostic and prediction models more exact and accurate. These collaborative networks aim to identify patients at risk, identify patients in the preclinical or early stages of illness, and develop tailored preventative interventions to enhance patient quality of life and prognosis. They also seek to identify new, robust, and effective methods for these patient identification tasks. To this end, the current study has been considered to examine the essential components that may be part of precise and tailored therapy plans used for neurodegenerative illnesses.

Central nervous system tumors are abnormal proliferations of neuronal cells within the brain and spinal cord. They can be primary or secondary and place a heavy financial, psychological, and physical burden on individuals. The highly selective blood-brain barrier, which only permits specific molecules to flow into the brain parenchyma, inhibits the efficacy of pharmacological medicines. Treatment options include surgery, chemoradiotherapy, and targeted therapy. Despite advances in therapy over the past few decades, the overall morbidity and mortality rates are still high, emphasizing the need for improved therapeutic choices to improve survival and quality of life further. Nano pharmaceuticals have demonstrated encouraging outcomes in in vivo trials using microscopic particles to enhance bioavailability and selectivity. The most successful clinical results to date have been achieved by liposomes, extracellular vesicles, and biomimetic nanoparticles; nevertheless, clinical trials are required to confirm their safety, efficacy, affordability, longterm impact, and success in patients from various demographics. Nano pharmaceuticals have the potential to change the paradigm of therapy for brain tumors, allowing better outcomes as primary and adjunctive therapy.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), remains a critical global health challenge, particularly with the rise of multidrug-resistant (MDR) strains. This study employed a comprehensive computational approach to identify and optimize inhibitors targeting the PptT-ACP complex, a key enzyme in MTB lipid biosynthesis. Virtual screening of FDA-approved compounds identified Mk3207 as a promising candidate. Stability analysis through molecular dynamics (MD) simulations validated its selection for derivative design. Three chemically tractable regions suitable for structural modification were identified, and the second region was selected for derivative design due to its favorable structural properties and binding interactions. One hundred derivatives were designed using ADMEopt and screened virtually, resulting in three top derivatives selected alongside Mk3207 for further evaluation. All compounds underwent 200 ns MD simulations in triplicate, with Compound_36 exhibiting the highest binding stability, as indicated by low root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values, followed by Compound_98 and Compound_60. Free energy landscape (FEL) and principal component analysis (PCA) confirmed the thermodynamic stability of these derivatives. Predicted biological activity using machine learning (Random Forest Regression) indicated pIC50 values of 25.64, 22.43, 22.32, and 26.26 for Compound_36, Compound_98, Compound_60, and Mk3207, respectively. This study demonstrates the potential of derivative design and machine learning in designing potent MTB inhibitors, providing strong candidates for experimental validation to combat drug-resistant TB effectively.

Various ailments have been treated with pineapple (Ananas comosus (L.) Merr.) throughout medicinal history. Pineapple and its bioactive compound bromelain possess health-promoting benefits. Detailed information on the chemotherapeutic activities of pineapple and its bioactive compound bromelain is provided in this review, which analyses the current literature regarding their therapeutic potential in cancer. Research on disease models in cell cultures is the focus of much of the existing research. Several studies have demonstrated the benefits of pineapple extract and bromelain for in vitro and in vivo cancer models. Preliminary animal model results show promise, but they must be translated into the clinical setting. Research on these compounds represents a promising future direction and may be well-tolerated.