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Identifying drug–target interactions (DTIs) is a critical step in both drug repositioning. The labor-intensive, time-consuming, and costly nature of classic DTI laboratory studies makes it imperative to create efficient computer algorithms to forecast possible DTIs. However, current computational approaches that predict potential drug–target interactions (DTIs) suffer from some limitations, like finding the best similarity measures or negative samples, and thus require substantial performance improvement. This study proposes an integrated approach based on feature representation and deep learning to predict DTIs. We extract the relevant features of drugs and proteins from heterogeneous networks using graph mining techniques. The proposed approach constructs a heterogeneous graph from the known drug–protein interactions, protein–protein, and drug–drug similarities. Then applying two feature extraction techniques to extract the features, then utilizing these features in training a deep learning model to predict the potential DTIs. Also, a novel algorithm is proposed to find the negative samples based on the drug and protein similarity matrices. Four Benchmark datasets are used to evaluate the proposed approach. Our approach achieves the highest AUC (area under the ROC curve) across all datasets (0.98) with around 2% increases over the existing methods. Experimental results demonstrate that our proposed approach outperforms the baseline methods in predicting DTI, and our negative sample-identifying algorithm could be established as a competitive solution. [ABSTRACT FROM AUTHOR]

The global spread of monkeypox, caused by the double-stranded DNA monkeypox virus (MPXV), has underscored the urgent need for effective antiviral treatments. In this study, we aim to identify a potent inhibitor for MPXV DNA polymerase (DNAP), a critical enzyme in the virus replication process. Using a computational drug repurposing approach, we performed a virtual screening of 1615 FDA-approved drugs based on drug-likeness and molecular docking against DNAP. Among these, 1430 compounds met Lipinski's rule of five for drug-likeness, with Doxycycline emerging as the most promising competitive inhibitor, binding strongly to the DNAP active site with a binding affinity of − 9.3 kcal/mol. This interaction involved significant hydrogen bonds, electrostatic interactions, and hydrophobic contacts, with Doxycycline demonstrating a stronger affinity than established antivirals for smallpox, including Cidofovir, Brincidofovir, and Tecovirimat. Stability and flexibility analyses through a 200 ns molecular dynamics simulation and normal mode analysis confirmed the robustness of Doxycycline binding to DNAP. Overall, our results suggest Doxycycline as a promising candidate for monkeypox treatment, though additional experimental and clinical studies are needed to confirm its therapeutic potential and clinical utility. [ABSTRACT FROM AUTHOR]

Hepatocellular Carcinoma (HCC) is a malignancy with high mortality rates and limited treatment options. This study aimed to unearth the repurposable potential of FDA-approved drugs against specific genetic targets governing the HCC pathological pathways. The transcriptomics microarray datasets were explored to retrieve the HCC specific differentially expressed genes, and the significant genes were fed in Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database to capture the protein-protein interactions, which were visualized in Cytoscape. This revealed CCNA2, a cell cycle regulator, as a potential target, which mediates its action by interacting with CDK1 and CDK2. Further, with the intention of identifying inhibitors for CDK1 and CDK2, a drug library was created, and the drugs were virtually screened against their respective targets via molecular docking and dynamics studies. This captured the binding affinity of Steviolbioside towards CDK1 and Etravirine and Fludarabine towards CDK2. In vitro, validation confirmed the cytotoxic potential of Etravirine and Fludarabine in Huh-7 cell lines. Further, enzymatic assays, gene expression analysis, and cell cycle analysis signified the anti-proliferative potential of Etravirine in Huh-7 cells via inhibition of CDK2. In this drug repurposing venture, Etravirine, a non-nucleoside reverse transcriptase inhibitor indicated for the treatment of HIV, emerged as a promising candidate for HCC treatment. The findings warrant further preclinical and clinical investigations to ascertain the repurposable potential of Etravirine against HCC, particularly in patients with viral infections. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a slow brain degeneration disorder in which the accumulation of beta-amyloid precursor plaque and an intracellular neurofibrillary tangle of hyper-phosphorylated tau proteins in the brain have been implicated in neurodegeneration. In this study, we identified the most important genes that are unique and sensitive in the entorhinal region of the brain to target AD effectively. At first, microarrays data are selected and constructed protein-protein interaction network (PPIN) and gene regulatory network (GRN) from differentially expressed genes (DEGs) using Cytoscape software. Then, networks analysis was performed to determine hubs, bottlenecks, clusters, and signaling pathways in AD. Finally, critical genes were selected as targets for repurposing drugs. Analyzing the constructed PPIN and GRN identified CD44, ELF1, HSP90AB1, NOC4L, BYSL, RRP7A, SLC17A6, and RUVBL2 as critical genes that are dysregulated in the entorhinal region of AD suffering patients. The functional enrichment analysis revealed that DEG nodes are involved in the synaptic vesicle cycle, glutamatergic synapse, PI3K-Akt signaling pathway, retrograde endocannabinoid signaling, endocrine and other factor-regulated calcium reabsorption, ribosome biogenesis in eukaryotes, and nicotine addiction. Gentamicin, isoproterenol, and tumor necrosis factor are repurposing new drugs that target CD44, which plays an important role in the development of AD. Following our model validation using the existing experimental data, our model based on previous experimental reports suggested critical molecules and candidate drugs involved in AD for further investigations in vitro and in vivo. [ABSTRACT FROM AUTHOR]

Introduction: Drug repositioning offers numerous advantages, such as faster development timelines, reduced costs, and lower failure rates in drug development. Supervised machine learning is commonly used to score drug candidates but is hindered by the lack of reliable negative data—drugs that fail due to inefficacy or toxicity— which is difficult to access, lowering their prediction accuracy and generalization. Positive-Unlabeled (PU) learning has been used to overcome this issue by either randomly sampling unlabeled drugs or identifying probable negatives but still suffers from misclassification or oversimplified decision boundaries. Results: We proposed a novel strategy using Large Language Models (GPT-4) to analyze all clinical trials on prostate cancer and systematically identify true negatives. This approach showed remarkable improvement in predictive accuracy on independent test sets with a Matthews Correlation Coefficient of 0.76 (± 0.33) compared to 0.55 (± 0.15) and 0.48 (± 0.18) for two commonly used PU learning approaches. Using our labeling strategy, we created a training set of 26 positive and 54 experimentally validated negative drugs. We then applied a machine learning ensemble to this new dataset to assess the repurposing potential of the remaining 11,043 drugs in the DrugBank database. This analysis identified 980 potential candidates for prostate cancer. A detailed review of the top 30 revealed 9 promising drugs targeting various mechanisms such as genomic instability, p53 regulation, or TMPRSS2-ERG fusion. Conclusion: By expanding our negative data labeling approach to all diseases within the ClinicalTrials.gov database, our method could greatly advance supervised drug repositioning, offering a more accurate and data-driven path for discovering new treatments. Scientific Contributions: In a drug repositioning context, machine learning algorithms trained on true negative data are consistently more accurate and generalizable compared to commonly used PU learning approaches. Large Language Models can enhance machine learning datasets by extracting relevant biological and medical data from online databases. [ABSTRACT FROM AUTHOR]

Computational approaches can speed up the drug discovery process by predicting drug-target affinity, otherwise it is time-consuming. In this study, we developed a convolutional neural network (CNN)-based model named SMILES2DTA (Simplified Molecular Input Line Entry System to Drug-Target Affinity) for predicting the binding affinity between a drug and a target protein. The model utilizes CNNs to process sequences of both drug SMILES and target proteins. SMILES2DTA generates multiple sequences from a single drug SMILES sequence, validates them based on Lipinski's rule of five, and assesses their binding affinity against a target protein sequence. We evaluated our model using publicly available datasets and compared its performance to state-of-the-art methods. The results showed that SMILES2DTA outperformed the existing methods and demonstrated improved accuracy, mean squared error, and area under the precision-recall curve. SMILES2DTA has the potential to speed up the drug discovery process by reducing the time and cost complexity of identifying effective drugs. [ABSTRACT FROM AUTHOR]

Carbonyl stress refers to the excessive accumulation of advanced glycation end products (AGEs) in mammalian tissues. This phenomenon plays a significant role in the pathogenesis of various diseases, including diabetes, chronic renal failure, arteriosclerosis, and central nervous system (CNS) disorders. We have previously demonstrated that an increase in glutathione concentration, dependent on the nuclear factor erythroid 2–related factor 2 (Nrf2) system, provides a potent cytoprotective effect against Methylglyoxal (MGO)-induced carbonyl stress. Meanwhile, dimethyl fumarate (DMF), known for its Nrf2-activating effects, was recently approved as a treatment for multiple sclerosis (MS), a neurodegenerative disease. DMF is a first line therapy for relapsing–remitting MS and may also be effective for other neurodegenerative conditions. However, the detailed mechanisms by which DMF mitigates neurodegenerative pathologies remain unclear. This study investigates the impact of DMF on anticarbonyl activity and its underlying mechanism focusing on the accumulation of carbonyl protein in the cell. MGO, a glucose metabolite, was used to induce carbonylation in the neuronal cell line. MGO is a typical carbonyl compound that readily reacts with arginine and lysine residues to form AGE-modified proteins. Methylglyoxal-derived hydroimidazolone 1 (MG-H1) often forms uncharged, hydrophobic residues on the protein surface, which can affect protein distribution and lead to misfolding. Our findings indicate that DMF increases levels of glutathione (GSH), glutamate cysteine ligase modifier subunit (GCLM), and nuclear Nrf2 in SH-SY5Y cells. Importantly, DMF pretreatment significantly reduced the accumulation of MG-H1-modified proteins. Furthermore, this effect of DMF was diminished when Nrf2 expression was suppressed and when GCL, a rate-limiting enzyme in GSH synthesis, was inhibited. Thus, the increase in GSH levels, leading to the activation of the Nrf2 pathway, a key factor in DMF’s ability to suppress the accumulation of MG-H1-modified proteins. This study is the first to demonstrate that DMF possesses strong anticarbonyl stress activity in neuronal cells. Therefore, future research may extend the application of DMF to other CNS diseases associated with carbonyl stress, such as Alzheimer’s and Parkinson’s disease. [ABSTRACT FROM AUTHOR]

Camel mastitis especially caused by Staphylococcus aureus (S. aureus), is a major risk to animal health and milk production. The current investigation evaluated the antibiotic susceptibility and virulence factors of S. aureus isolates from subclinical mastitis in camels. A total of 384 milk samples were collected and submitted to isolate S. aureus. The S. aureus isolates exhibiting resistance to Penicillin and Cefoxitin disc on Kirby-Bauer disc diffusion method were considered as β-lactam resistant S. aureus (BRSA) and methicillin-resistant S. aureus (MRSA) which were further confirmed by PCR targeting blaZ and mecA genes, respectively. The results showed that S. aureus was found in 57.06% of subclinical (SCM) positive camel milk samples. A high molecular prevalence of BRSA and MRSA were found to be 48.51% and 46.53% respectively depicting that treating these infections is challenging due to their high resistance levels. The phylogenetic analysis revealed a significant resemblance of the study isolates with each other and with already reported sequences from different countries which shows the potential for the spread of pathogen. Virulence profiling of antibiotic resistance strains showed the presence of virulence markers (nuc and coag genes), intercellular adhesion genes (icaA, icaD), Panton-Valentine leukocidin (pvl) gene, and enterotoxin-producing genes including sea, seb, sec, and sed. In-vitro antibiotic susceptibility testing revealed that the most resistant antibiotic group was penicillin followed by aminoglycosides and cephalosporins. Drug repurposing analysis of different non-antibiotics for combination therapies with resistant antibiotics was done to combat the S. aureus isolates harboring the mecA and blaZ genes. The results revealed the synergistic effect of amoxicillin, sulfamethoxazole, gentamicin, and doxycycline with ketoprofen, amikacin with flunixin meglumine, and gentamicin with N-acetylcysteine (NAC) against study isolates. The current investigation provides the status of antibiotic-resistant strains and virulence factors of S. aureus in the udder of dromedary camels. The combinational therapy of resistant antibiotics with non-antibiotics provides a potential therapeutic option for the treatment of resistant strains. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease that is characterized by memory loss and cognitive impairment. Evidence shows that depression is a common co-occurrence in AD patients, and major depressive disorder (MDD) is considered a risk factor for AD. The crosstalk between the biological procedures related to the two disorders makes it very difficult to treat the comorbid conditions caused by them. Considering the common pathophysiological mechanisms underlying AD and MDD, antidepressant drugs may have beneficial therapeutic effects against their concurrence. In this study, we aimed to explore the potential drug candidates for the prevention and treatment of the comorbidity of AD and MDD. First, we screened the potential drugs for treating MDD by evaluating the distances of drug targets to MDD-related genes on the human protein–protein interaction network (PPIN) via a network-based algorithm. Then, the drugs were further screened to identify those that may be effective for AD treatment by analyzing their affinities with tau protein and Aβ42 peptide via molecular docking. Furthermore, the most stable binding modes were identified via molecular dynamics simulations, and the regulatory effects of drug candidates on genes involved in the pathogenesis of AD and MDD were analyzed. A total of 506 MDD-related genes were retrieved, and 831 drug candidates for MDD treatment were screened via the network-based approach. The results from molecular docking and molecular dynamics simulations indicated dihydroergotamine had the lowest binding affinity with tau protein and bromocriptine could form the most stable binding mode with Aβ42 peptide. Further analyses found that both dihydroergotamine and bromocriptine could regulate the expression of genes involved in the pathogenesis of AD and/or MDD in the brain. The exact mechanisms of the two drugs in treating AD and MDD, as well as their comorbidity, are still unclear, and further exploration is needed to evaluate their roles and mechanisms, both in vitro and in vivo. This study revealed that dihydroergotamine and bromocriptine may be the potential drug candidates for the treatment of the comorbidity of AD and MDD, and the therapeutic effects may be achieved by inhibiting the accumulation and aggregation of Aβ42 and tau protein and regulating the expression of disease-related genes in the brain. [ABSTRACT FROM AUTHOR]

The area of wound healing presents a promising field of interest for clinicians as well as the scientific community. A major concern for physicians is the rising number of elderly people suffering from diabetes, leprosy, tuberculosis and the associated chronic wounds. While traditional therapies target basic wound care, innovative strategies that accelerate wound healing are needed. V-RAF murine sarcoma viral oncogene homolog B1 (BRAF) inhibitors are anti-cancer drugs used primarily for melanoma. They also exhibit paradoxical activity, a phenomenon characterized by unintended activation of the Mitogen-Activated Protein Kinase (MAPK) signalling pathway leading to skin hyperproliferation. Studies have demonstrated that BRAF inhibitors can be repurposed to accelerate the healing of acute and chronic wounds by exploiting their paradoxical activity. This review evaluates studies on BRAF inhibitors by employing a systematic search strategy using databases such as PubMed, Scopus, Google Scholar, and Web of Science. Articles were screened based on relevance to the paradoxical activity of BRAF inhibitors, their mechanisms, and applications in wound healing. Evidence from in vitro, in vivo, and clinical studies demonstrates that BRAF inhibitors can enhance processes such as epithelialization and angiogenesis, essential for wound repair. This review summarizes the reports on the paradoxical activity of BRAF inhibitors, the predicted mechanisms behind the paradoxical activity, and their potential use in wound healing. [ABSTRACT FROM AUTHOR]

Background: Current treatment strategies for hormone-dependent breast cancers, including adjuvant endocrine therapy, often fail due to persistence of breast cancer stem cells (brCSCs), which are significant contributors to tumor recurrence and treatment resistance. Therefore, gaining deeper insights into the molecular regulators driving breast cancer aggressiveness is important. Moreover, given the complexities and expenses involved in developing new pharmacological agents, the strategic repurposing of existing FDA-approved drugs to target these key molecular pathways presents a compelling approach for identifying novel therapeutic interventions aimed at mitigating tumor refractoriness. Methods: The study employs survival analysis from TCGA database, protein expression analyses alongside aldefluor assays, sphere formation efficiency tests to evaluate cellular stemness, and DCFDA analysis combined with antioxidant enzyme assays to investigate redox imbalance in brCSCs. These analyses were conducted following the genetic deletion of YAP/TAZ and pharmacological treatment with verteporfin. Results: The study demonstrated that transcriptional co-activators YAP/TAZ are significantly upregulated in chemotreated ER+ patient breast tumors and MCF-7 mammospheres, where it was found to interact with the transcription factor SOX2 within the nuclear compartment. Genetic ablation and pharmacological inhibition of YAP/TAZ markedly impaired stemness properties and disrupted redox homeostasis in the mammospheres. Additionally, treatment with verteporfin led to a substantial reduction in the frequency and viability of brCSCs, suggesting their effective eradication. Conclusion: This study highlights the potential of repurposing verteporfin, an FDA-approved drug originally formulated for age-related macular degeneration, as a therapeutic agent for targeting YAP/TAZ-mediated stemness and redox balance in brCSCs, thereby reducing their viability in ER-positive breast cancers. [ABSTRACT FROM AUTHOR]

Background: Thyroid carcinoma (THCA) is the most common cancer of the endocrine system. Natural killer (NK) cell play an important role in tumor immune surveillance. The aim of this study was to explore the possible molecular mechanisms involved in NK cell in THCA to help the management and treatment of the disease. Methods: All data were downloaded from public databases. Candidate hub genes associated with NK cell in THCA were identified by limma, WGCNA and singleR packages. Functional enrichment analysis was performed on the candidate hub genes. Hub genes associated with NK cell were identified by Pearson correlation analysis. The mRNA-miRNA-lncRNA and transcription factors (TF) networks were constructed and the drug was predicted. Results: The infiltration level of NK cell in THCA tissues was higher than that in paracancerous tissues. KEGG functional enrichment analysis only obtained two signaling pathways, thyroid hormone synthesis and mineral absorption. CTSC, FN1, SLC34A2 and TMSB4X identified by Pearson correlation analysis were considered as the hub genes. Receiver operating characteristic analysis suggested that hub genes may be potential diagnostic biomarkers. In mRNA-miRNA-lncRNA network, FN1 had the highest correlation with IQCH-AS1, and IQCH-AS1 was also correlated with hsa-miR-543. In addition, FN1 and RUNX1 were also found to have the highest correlation in TF network. Finally, NK cell-related drugs belinostat and vorinostat were identified based on ASGARD. Conclusion: The identification of important signaling pathways, molecules and drugs provides potential research directions for further research in THCA and contributes to the development of diagnostic and therapeutic approaches for this disease. [ABSTRACT FROM AUTHOR]

Wnt signaling is a critical pathway implicated in cancer development, with Frizzled proteins, particularly FZD10, playing key roles in tumorigenesis and recurrence. This study focuses on the potential of repurposed FDA-approved drugs targeting FZD10 as a therapeutic strategy for nasopharyngeal carcinoma (NPC). The tertiary structure of human FZD10 was constructed using homology modeling, validated by Ramachandran plot and ProQ analysis. Virtual screening of 1,094 FDA-approved drugs identified 17 potential inhibitors, with prazosin, rilpivirine, doxazosin, and nicergoline demonstrating significant cytotoxicity against NPC cells. Further molecular dynamics simulations and binding energy analyses confirmed the stable binding of these drugs to FZD10. The results suggest that these repurposed drugs could serve as promising candidates for targeted NPC therapy, warranting further investigation. [ABSTRACT FROM AUTHOR]

Antibiotic resistance by methicillin-resistant Staphylococcus aureus (MRSA) is an urgent threat to human health. The biofilm and persister cells formation ability of MRSA and Staphylococcus epidermidis often companied with extremely high antimicrobial resistance. Pinaverium bromide (PVB) is an antispasmodic compound mainly used for irritable bowel syndrome. Here we demonstrate that PVB could rapidly kill MRSA and S. epidermidis planktonic cells and persister cells avoiding resistance occurrence. Moreover, by crystal violet staining, viable cells counting and SYTO9/PI staining, PVB exhibited strong biofilm inhibition and eradication activities on the 96-well plates, glass surface or titanium discs. And the synergistic antimicrobial effects were observed between PVB and conventional antibiotics (ampicillin, oxacillin, and cefazolin). Mechanism study demonstrated the antimicrobial and antibiofilm effects by PVB were mainly mediated by proton motive force disrupting as well as reactive oxygen species inducing. Although, relatively poor pharmacokinetics were observed by systemic use, PVB could significantly reduce the viable bacterial cell loads and inflammatory infiltration in abscess in vivo caused by the biofilm forming strain ATCC 43,300. In all, our results indicated that PVB could be an alternative antimicrobial reagent for the treatment of MRSA, S. epidermidis and its biofilm related skin and soft tissue infections. Key points: Pinaverium bromide (PVB) exhibited strong antimicrobial effects against Staphylococcus planktonic cells. Significant biofilm inhibitory and eradicating activities by PVB. Proton motive force disrupting and reactive oxygen species inducing are the main antimicrobial and antibiofilm mechanisms. PVB reduce the viable bacterial cell loads and inflammatory infiltration in vivo. [ABSTRACT FROM AUTHOR]

Drug repurposing is necessary to accelerate drug discovery and meet the drug needs. This study investigated the possibility of using fluvoxamine to inhibit the cellular metabolizing enzyme NUDT5 in breast cancer. Computational and experimental techniques were used to evaluate the structural flexibility, binding stability, and chemical reactivity of the drugs. These findings indicated that fluvoxamine effectively suppressed the activity of NUDT5, as evidenced by a binding score of − 8.514 kcal/mol. Furthermore, the binding positions of fluvoxamine and NUDT5 were optimized. Fluvoxamine attachment to the active sites of Trp28, Trp46, Glu47, Arg51, Arg84, and Leu98 in NUDT5 has been shown to alter the metabolism of ADPr. These alterations play a role in ATP production in the breast cancer cells. In addition, an MTT assay conducted on the MCF-7 cell line using fluvoxamine revealed an IC50 value of 53.86 ± 0.05 µM. Fluvoxamine-induced apoptosis was confirmed as evidenced by AO/EtBr and DAPI staining. [ABSTRACT FROM AUTHOR]

In this study, we investigated a novel anti-cancer drug design approach by revisiting diclofenac-based carborane-substituted prodrugs. The redesigned compounds combine the robust carborane scaffold with the oxindole framework, resulting in four carborane-derivatized oxindoles and a unique zwitterionic amidine featuring a nido-cluster. We tested the anti-cancer potential of these prodrugs against murine colon adenocarcinoma (MC38), human colorectal carcinoma (HCT116), and human colorectal adenocarcinoma (HT29). The tests showed that diclofenac and the carborane-substituted oxindoles exhibited no cytotoxicity, the dichlorophenyl-substituted oxindole had moderate anti-cancer activity, while with the amidine this effect was strongly potentiated with activity mapping within low micromolar range. Compound 3 abolished the viability of selected colon cancer cell line MC38 preferentially through strong inhibition of cell division and moderate apoptosis accompanied by ROS/RNS depletion. Our findings suggest that carborane-based prodrugs could be a promising direction for new anti-cancer therapies. Inhibition assays for COX-1 and COX-2 revealed that while diclofenac had strong COX inhibition, the re-engineered carborane compounds demonstrated a varied range of anti-cancer effects, probably owing to both, COX inhibition and COX-independent pathways. [ABSTRACT FROM AUTHOR]

Inflammation is a defensive mechanism that safeguards the human body against detrimental stimuli. Within this intricate process, ADAM17, a zinc-dependent metalloprotease, emerges as an indispensable element, fostering the activation of diverse inflammatory and growth factors within the organism. Nonetheless, ADAM17 malfunctions can augment the rate of growth, inflammatory factors, and subsequent damage. Thus, in this study, we examined and repurposed drugs to suppress the activity of ADAM17. To this end, we employed bioinformatics techniques such as molecular docking, molecular dynamics, and pharmacokinetic studies. Five FDA-approved drugs including Raltegravir, Conivaptan, Paclitaxel, Saquinavir, and Venetoclax with the ability to impede the activity of the ADAM17 metalloenzyme were identified. Moreover, these drugs did not include strong zinc-binding functional groups when verified by the ACE functional group finder. However, further in silico analysis has indicated that Raltegravir demonstrates a commendable interaction with the active site amino acids and exhibits the most favorable pharmacokinetic properties compared to others. Considering the results of bioinformatics tools, it can be concluded that Raltegravir as an antiviral drug could be repurposed to prevent severe inflammatory response and tumorigenesis resulting from ADAM17 malfunction. [ABSTRACT FROM AUTHOR]

Despite the long history of experimental trials to combat schistosomiasis, it remains a significant burden due to drug resistance and the effectiveness of the standard treatment only against the mature stage, while skipping other early developmental stages thus leading to severe permanent pathological sequelae. Therefore, repurposing a commonly used well-known safe drug would be a wise alternative. We investigated the potential anti-schistosomal drug activity of Daflon® (DAF) against different schistosomal developmental stages. DAF was administrated at a dose of 100 mg/kg/mouse on days zero, 21, and 42 post-infection towards the invasive, immature, and mature stages of Schistosoma mansoni respectively in comparison to the standard anti-schistosomal drug (Praziquantel). All mice were sacrificed on day 49 post-infection. DAF induced a significant reduction in the total and female worm count, hepatic granuloma size, and number, the extent of liver parenchymal injury and fibrosis as well as intestinal and hepatic egg count compared to the infected untreated control. Liver malondialdehyde (MDA) levels significantly decreased in all DAF-treated groups. Scanning electron microscope findings revealed edema, tegumental blebs, cracks, and fissures in male tegument in all DAF-treated groups with distortion of the ventral suckers and disarrangement of the spines of the oral sucker. The female worm from DAF-treated groups showed tegumental edema with loss of the spines at the posterior end. Compared to the documented reduction of testosterone levels and distortion of testicular architecture in the S. mansoni-infected untreated group, DAF significantly restored testosterone levels and testicular architecture. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease characterized by excessive collagen deposition and fibrosis of the lung parenchyma, leading to respiratory failure. The molecular mechanisms underlying IPF pathogenesis remain incompletely understood, hindering the development of effective therapeutic strategies. We have used a network medicine approach to comprehensively analyze molecular interactions and identify novel molecular signatures and potential therapeutics associated with IPF progression. Our integrative analysis revealed dysregulated molecular networks that are central to IPF pathophysiology. We have highlighted key molecular players and signaling pathways that are implicated in aberrant fibrotic processes. This systems-level understanding enables the identification of new biomarkers and therapeutic targets for IPF, providing potential avenues for precision medicine. Drug repurposing analysis revealed several drug candidates with anti-fibrotic, anti-inflammatory, and anti-cancer activities that could potentially slow fibrotic progression and improve patient outcomes. This study offers new insights into the molecular underpinnings of IPF and highlights network medicine approaches in uncovering complex disease mechanisms. The molecular signatures and therapeutic targets identified hold promise for developing precision therapies tailored to individual patients, ultimately advancing the management of this debilitating lung disease. [ABSTRACT FROM AUTHOR]

Background: The rise in Plasmodium resistant strains, decreasing susceptibility to first-line combination therapies, and inadequate efficacy shown by vaccines developed to date necessitate innovative approaches to combat malaria. Drug repurposing refers to finding newer indications for existing medications that provide significant advantages over de novo drug discovery, leading to rapid treatment options. Growing evidence suggests that drugs could regulate the expression of disease-associated microRNAs (miRNAs), implying the potential of miRNAs as attractive targets of therapy for several diseases. Methods: We aimed to computationally predict drug-disease relationships through miRNAs for the potential repurposing of the drugs as antimalarials. To achieve this, we created a model that combines experimentally validated miRNA-drug interactions and miRNA-disease correlations, assuming that drugs will be linked to disease if they share significant miRNAs. The first step involved constructing a network of drug–drug interactions using curated drug-miRNA relations from the Pharmaco-miR and SM2miR databases. Additionally, the drug-disease relations were acquired from the comparative toxicogenomics database (CTD), and the random walk with restart (RWR) algorithm was applied to the interaction network to anticipate newer drug indications. Further, experimentally verified miRNA-disease associations were procured from the human microRNA disease database (HMDD), followed by an evaluation of the model's performance by examining case studies retrieved from the literature. Results: Topological network analysis revealed that beta-adrenergic drugs in the network that are closely linked may have a tendency to be used as antimalarials. Case studies retrieved from the literature demonstrated acceptable model performance. A few of the predicted drugs, namely, propranolol, metoprolol, epinephrine, and atenolol, have been evaluated for their association with malaria, thereby indicating the adequacy of our model and offering experimental leads for alternative drugs. Conclusion: The study puts forth a computational model for forecasting potential connections between beta-adrenergic receptor targeting drugs and malaria to suggest potential for future drug repurposing. This takes into account the concept of commonly associated miRNA partners and providing a mechanistic basis for targeting diseases, elucidating the implication of miRNAs in novel drug-disease relations. [ABSTRACT FROM AUTHOR]

Endometrial cancer (EC) is the 6th most common cancer in women around the world. Alone in the United States (US), 66,200 new cases and 13,030 deaths are expected to occur in 2023 which needs the rapid development of potential therapies against EC. Here, a network-based drug-repurposing strategy is developed which led to the identification of 16 FDA-approved drugs potentially repurposable for EC as potential immune checkpoint inhibitors (ICIs). A network of EC-associated immune checkpoint proteins (ICPs)-induced protein interactions (P-ICP) was constructed. As a result of network analysis of P-ICP, top key target genes closely interacting with ICPs were shortlisted followed by network proximity analysis in drug–target interaction (DTI) network and pathway cross-examination which identified 115 distinct pathways of approved drugs as potential immune checkpoint inhibitors. The presented approach predicted 16 drugs to target EC-associated ICPs-induced pathways, three of which have already been used for EC and six of them possess immunomodulatory properties providing evidence of the validity of the strategy. Classification of the predicted pathways indicated that 15 drugs can be divided into two distinct pathway groups, containing 17 immune pathways and 98 metabolic pathways. In addition, drug–drug correlation analysis provided insight into finding useful drug combinations. This fair and verified analysis creates new opportunities for the quick repurposing of FDA-approved medications in clinical trials. [ABSTRACT FROM AUTHOR]

Summary: Cryptococcosis is an invasive mycosis caused mainly by Cryptococcus gattii and C. neoformans and is treated with amphotericin B (AMB), fluconazole and 5-fluorocytosine. However, antifungal resistance, limited and toxic antifungal arsenal stimulate the search for therapeutic strategies such as drug repurposing. Among the repurposed drugs studied, the selective serotonin reuptake inhibitors (SSRIs) have shown activity against Cryptococcus spp. However, little is known about the antifungal effect of duloxetine hydrochloride (DH), a selective serotonin and norepinephrine reuptake inhibitor (SSNRI), against C. neoformans and C. gattii. In this study, DH inhibited the growth of several C. neoformans and C. gattii strains at concentrations ranging from 15.62 to 62.50 µg/mL. In addition, DH exhibited fungicidal activity ranging from 15.62 to 250 µg/mL. In biofilm, DH treatment reduced Cryptococcus spp. biomass at a level comparable to AMB, with a significant reduction (85%) for C. neoformans biofilms. The metabolic activity of C. neoformans and C. gattii biofilms decreased significantly (99%) after treatment with DH. Scanning electron micrographs confirmed the anti-biofilm activity of DH, as isolated cells could be observed after treatment. In conclusion, DH showed promising antifungal activity against planktonic cells and biofilms of C. neoformans and C. gattii, opening perspectives for further studies with DH in vivo. [ABSTRACT FROM AUTHOR]

Pertussis toxin (PT) is a virulent factor produced by Bordetella pertussis, the causative agent of whooping cough. PT exerts its pathogenic effects by ADP-ribosylating heterotrimeric G proteins, disrupting cellular signaling pathways. Here, we investigate the potential of two antiarrhythmic drugs, amiodarone and dronedarone, in mitigating PT-induced cellular intoxication. After binding to cells, PT is endocytosed, transported from the Golgi to the endoplasmic reticulum where the enzyme subunit PTS1 is released from the transport subunit of PT. PTS1 is translocated into the cytosol where it ADP-ribosylates inhibitory α-subunit of G-protein coupled receptors (Gαi). We showed that amiodarone and dronedarone protected CHO cells and human A549 cells from PT-intoxication by analyzing the ADP-ribosylation status of Gαi. Amiodarone had no effect on PT binding to cells or in vitro enzyme activity of PTS1 but reduced the signal of PTS1 in the cell suggesting that amiodarone interferes with intracellular transport of PTS1. Moreover, dronedarone mitigated the PT-mediated effect on cAMP signaling in a cell-based bioassay. Taken together, our findings underscore the inhibitory effects of amiodarone and dronedarone on PT-induced cellular intoxication, providing valuable insights into drug repurposing for infectious disease management. [ABSTRACT FROM AUTHOR]

The dreaded nosocomial pathogen Clostridioides difficile causes diarrhea and severe inflammation of the colon, especially after the use of certain antibiotics. The bacterium releases two deleterious toxins, TcdA and TcdB, into the gut, which are mainly responsible for the symptoms of C. difficile-associated diseases (CDADs). Both toxins are capable of entering independently into various host cells, e.g., intestinal epithelial cells, where they mono-O-glucosylate and inactivate Rho and/or Ras GTPases, important molecular switches for various cellular functions. We have shown recently that the cellular uptake of the Clostridioides difficile toxins TcdA and TcdB (TcdA/B) is inhibited by the licensed class III antiarrhythmic drug amiodarone (Schumacher et al. in Gut Microbes 15(2):2256695, 2023). Mechanistically, amiodarone delays the cellular uptake of both toxins into target cells most likely by lowering membrane cholesterol levels and by interfering with membrane insertion and/or pore formation of TcdA/B. However, serious side effects, such as thyroid dysfunction and severe pulmonary fibrosis, limit the clinical use of amiodarone in patients with C. difficile infection (CDI). For that reason, we aimed to test whether dronedarone, an amiodarone derivative with a more favorable side effect profile, is also capable of inhibiting TcdA/B. To this end, we tested in vitro with various methods the impact of dronedarone on the intoxication of Vero and CaCo-2 cells with TcdA/B. Importantly, preincubation of both cell lines with dronedarone for 1 h at concentrations in the low micromolar range rendered the cells less sensitive toward TcdA/B-induced Rac1 glucosylation, collapse of the actin cytoskeleton, cell rounding, and cytopathic effects, respectively. Our study points toward the possibility of repurposing the already approved drug dronedarone as the preferable safer-to-use alternative to amiodarone for inhibiting TcdA/B in the (supportive) therapy of CDADs. [ABSTRACT FROM AUTHOR]

Imiquimod (IMQ), a drug from aminoquinoline group, is the toll-like receptor 7 (TLR7) agonist. It acts as an immunostimulant and radio-sensitizing agent. IMQ stimulates both innate and adaptive immune response. Despite studies conducted, there are no unambiguous data showing how IMQ affects the condition of tumor blood vessels. Tumor vasculature plays the main role in tumor progression. Formation of abnormal blood vessels increases area of hypoxia which recruits suppressor cells, blocks tumor infiltration by CD8+ T lymphocytes, inhibits efficacy of chemoterapeutic drug and leads to cancer relapse. Normalization is a type of therapy targeted at abnormal tumor blood vessels. Here, we demonstrated that 50 µg of IMQ inhibits the growth of melanoma tumors more efficiently, compared to other tested doses and the control group. Dose escalation did not improve the therapeutic antitumor potential of TLR7 agonist. A dose of 50 µg of IMQ most effectively reduced tumor blood vessel density. Imiquimod normalized tumor vasculature both structurally (by reducing vessel tortuosity and increasing pericyte coverage) and functionally (by improving tumor perfusion) in a dose-dependent manner. Hypoxia regions in tumors of treated mice were significantly reduced after IMQ administration. A dose of 50 µg of IMQ had also the greatest impact on the changes in tumor-infiltrating T lymphocytes levels. TLR7 agonist inhibited angiogenesis in treated mice. Functional vascular normalization by IMQ increases the effectiveness of low dose of doxorubicin. Higher dose of IMQ showed worse effects than lower doses including decreased tumor perfusion, increased tumor hypoxia and immunosuppression. This knowledge may help to optimize the combination of the selected IMQ dose with e.g. chemotherapy or radiotherapy to elicit synergistic effect in cancer treatment. To conclude, we outline IMQ repurposing as a vascular normalizing agent. Our research results may contribute to expanding the therapeutic indications for the use of IMQ in anticancer therapy in the future. [ABSTRACT FROM AUTHOR]

Computational systems biology employs computational algorithms and integrates diverse data sources, such as gene expression profiles, molecular interactions, and network modeling, to identify promising drug candidates through repurposing existing compounds in response to urgent healthcare needs. This study tackles the urgent need for rapid therapeutic development against emerging infectious diseases. We introduce a novel analytic expression for sensitivity analysis based on the Kronecker product and enhance model prediction performance using Graph Convolutional Networks (GCNs) with sensitivity-based graph reduction. Our algorithm refines prediction performance by leveraging sensitivity-based graph reduction. By integrating RNA-seq data, molecular interactions, and GCNs, we identify disease-related genes and pathways, construct heterogeneous graph models, and predict potential drugs. This approach involves novel analytical expressions that assess sensitivity to model loss, employing the Kronecker product approach. Subgraph analysis identifies nodes for removal, leading to a refined graph used for model retraining. This cost-effective pipeline focuses on computational methods for drug repurposing, targeting infectious diseases such as Zika virus and COVID-19 infection. Applied to these infections, our methodology integrates 659 proteins and 703 drugs for Zika virus, and 495 proteins and 468 drugs for COVID-19, along with their interactions derived from gene expression profiles. Top candidate drugs, such as Betamethasone phosphate and Bizelesin for Zika virus, and Chloroquine, Heparin Disaccharide, and Resveratrol for COVID-19, were validated through literature review or docking analysis. This scalable approach demonstrates promise in repurposing drugs for urgent healthcare challenges. [ABSTRACT FROM AUTHOR]

Cellular plasticity and the ability to avoid terminal differentiation are hallmarks of cancer. Here, we review the evidence that tumor cells themselves can take on properties of neurons of the central nervous system, which can regulate tumor growth and metastasis. We discuss recent evidence that axon guidance molecules and regulators of electrical activity and synaptic transmission, such as ion channels and neurotransmitters, can drive the oncogenic and invasive properties of tumor cells from a range of cancers. We also review how FDA-approved treatments for neurological disorders are being tested in pre-clinical models and clinical trials for repurposing as anti-cancer agents, offering the potential for new therapies for cancer patients that can be accessed more quickly. [ABSTRACT FROM AUTHOR]

Progress in developing therapies for the maintenance of endogenous insulin secretion in, or the prevention of, type 1 diabetes has been hindered by limited animal models, the length and cost of clinical trials, difficulties in identifying individuals who will progress faster to a clinical diagnosis of type 1 diabetes, and heterogeneous clinical responses in intervention trials. Classic placebo-controlled intervention trials often include monotherapies, broad participant populations and extended follow-up periods focused on clinical endpoints. While this approach remains the 'gold standard' of clinical research, efforts are underway to implement new approaches harnessing the power of artificial intelligence and machine learning to accelerate drug discovery and efficacy testing. Here, we review emerging approaches for repurposing agents used to treat diseases that share pathogenic pathways with type 1 diabetes and selecting synergistic combinations of drugs to maximise therapeutic efficacy. We discuss how emerging multi-omics technologies, including analysis of antigen processing and presentation to adaptive immune cells, may lead to the discovery of novel biomarkers and subsequent translation into antigen-specific immunotherapies. We also discuss the potential for using artificial intelligence to create 'digital twin' models that enable rapid in silico testing of personalised agents as well as dose determination. To conclude, we discuss some limitations of artificial intelligence and machine learning, including issues pertaining to model interpretability and bias, as well as the continued need for validation studies via confirmatory intervention trials. [ABSTRACT FROM AUTHOR]

In the realm of epigenetic regulation, Protein arginine deiminase 2 (PAD2) stands out as a therapeutic target due to its significant role in neurological disorders, rheumatoid arthritis (RA), multiple sclerosis (MS), and various cancers. To date, no in silico studies have focused on PAD2 for lead compound identification. Therefore, we conducted structure-based pharmacophore modeling, virtual screening, molecular docking, molecular dynamics (MD) simulations, and essential dynamics studies using PCA and free energy landscape analyses to identify repurposed drugs and selective inhibitors against PAD2. The best pharmacophore model, 'Pharm_01,' had a selectivity score of 10.485 and an excellent ROC curve quality of 0.972. Pharm1 consisted of three hydrogen bond donors (HBD) and two hydrophobic (Hy) features (DDDHH). A virtual screening of about 9.2 million compounds yielded 2575 hits using a fit value threshold of 2.5 and drug-likeness criteria. Molecular docking identified the top ten molecules, which were verified using MD simulations. Stability was verified using MM-PBSA studies, whereas conformational differences were investigated using PCA and free energy landscape analyses. Two hits (Leads 1 and 2) from the DrugBank dataset showed promise for repurposing as PAD2 inhibitors, while one hit compound (Lead 8) from the ZINC database emerged as a novel PAD2 inhibitor. These findings indicate that the discovered compounds may be potent PAD2 inhibitors, necessitating additional preclinical and clinical research to produce viable treatments for cancer and neurological disorders. [ABSTRACT FROM AUTHOR]

Background: Chronic inflammation is an increasing global healthcare challenge with limited effective treatment options. Developing medications for chronic diseases requires high financial investment and a long duration. Given these challenges, alternative strategies are needed. Here, we focus on one such strategy that holds great promise: drug repurposing, which involves identifying new therapeutic uses for existing drugs. Main body: Here, we discuss the importance of two key transcription factors: nuclear factor kappa B (NF-κB) and activator protein 1 (AP-1), in orchestrating complex pathophysiological signaling networks involved in chronic inflammatory diseases. Dysregulation of the NF-κB and AP1 signaling pathways have been associated with various diseases, such as cancer, inflammatory disease, and autoimmune disorders. This review emphasized that repurposed small-molecule inhibitors of these pathways have proven successful as therapeutic interventions. These compounds exhibit high degrees of specificity and efficacy in modulating NF-κB or AP-1 signaling, making them appealing candidates for treating chronic inflammatory conditions. This review discusses the therapeutic potential and action mechanisms of several repurposed small-molecule inhibitors for combating diseases caused by abnormal activation or inhibition of NF-κB and AP-1. Conclusion: This concise review highlights the potential of repurposing small-molecule inhibitors targeting the NF-κB and AP-1 pathways as effective therapies for various chronic inflammatory diseases. While further experimental validation is needed, drug repurposing offers a promising strategy to bypass the existing lengthy and expensive new drug development processes, providing a faster and more economical route to novel treatments. [ABSTRACT FROM AUTHOR]

Functional genomics, a multidisciplinary subject, investigates the functions of genes and their products in biological systems to better understand diseases and find new drugs. Drug repurposing is an economically efficient approach that entails discovering novel therapeutic applications for already-available medications. Genomics enables the identification of illness and therapeutic molecular characteristics and interactions, which in turn facilitates the process of drug repurposing. Techniques like gene expression profiling and Mendelian randomization are helpful in identifying possible medication candidates. Progress in computer science allows for the investigation and modeling of gene expression networks that involve large amounts of data. The amalgamation of data concerning DNA, RNA, and protein functions bears similarity to pharmacogenomics, a crucial aspect in crafting cancer therapeutics. Functional genomics in drug discovery, particularly for cancer, is still not thoroughly investigated, despite the existence of a significant amount of literature on the subject. Next-generation sequencing and proteomics present highly intriguing opportunities. Publicly available databases and mining techniques facilitate the development of cancer treatments based on functional genomics. Broadening the exploration and utilization of functional genomics holds significant potential for advancing drug discovery and repurposing, particularly within the realm of oncology. [ABSTRACT FROM AUTHOR]

A large fraction of the world's population is directly impacted by acute or chronic viral infections, many of which have high mortality. As was brought home to us in 2020, viruses also have great potential to generate global pandemics that have killed millions and caused massive damage to economies. Clearly, we need cost-effective and rapid methods for finding drug treatments for poorly met infectious diseases and for responding effectively to the current and future pandemics. Repurposing or off-label use of existing drugs, whose safety and pharmacokinetics are well understood, is one useful way to provide fast drug therapies for patients. Computational methods have an important role to play because of their increasing effectiveness, high speed, and relatively low cost. Here we review the application of the main types of computational drug repurposing methods to discovery of therapies for viral diseases and for future pandemics highly likely to be caused by viral pathogens. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the highest grade of glioma for which no effective therapy is currently available. Despite extensive research in diagnosis and therapy, there has been no significant improvement in GBM outcomes, with a median overall survival continuing at a dismal 15–18 months. In recent times, glioblastoma stem cells (GSCs) have been identified as crucial drivers of treatment resistance and tumor recurrence, and GBM therapies targeting GSCs are expected to improve patient outcomes. We used a multistep in silico screening strategy to identify repurposed candidate drugs against selected therapeutic molecular targets in GBM with potential to concomitantly target GSCs. Common differentially expressed genes (DEGs) were identified through analysis of multiple GBM and GSC datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). For identification of target genes, we selected the genes with most significant effect on overall patient survival. The relative mRNA and protein expression of the selected genes in TCGA control versus GBM samples was also validated and their cancer dependency scores were assessed. Drugs targeting these genes and their corresponding proteins were identified from LINCS database using Connectivity Map (CMap) portal and by in silico molecular docking against each individual target using FDA-approved drug library from the DrugBank database, respectively. The molecules thus obtained were further evaluated for their ability to cross blood brain barrier (BBB) and their likelihood of resulting in drug resistance by acting as p-glycoprotein (p-Gp) substrates. The growth inhibitory effect of these final shortlisted compounds was examined on a panel of GBM cell lines and compared with temozolomide through the drug sensitivity EC50 values and AUC from the PRISM Repurposing Secondary Screen, and the IC50 values were obtained from GDSC portal. We identified RPA3, PSMA2, PSMC2, BLVRA, and HUS1 as molecular targets in GBM including GSCs with significant impact on patient survival. Our results show GSK-2126458/omipalisib, linifanib, drospirenone, eltrombopag, nilotinib, and PD198306 as candidate drugs which can be further evaluated for their anti-tumor potential against GBM. Through this work, we identified repurposed candidate therapeutics against GBM utilizing a GSC inclusive targeting approach, which demonstrated high in vitro efficacy and can prospectively evade drug resistance. These drugs have the potential to be developed as individual or combination therapy to improve GBM outcomes. [ABSTRACT FROM AUTHOR]

The cell cycle is the sequence of events orchestrated by a complex network of cell cycle proteins. Unlike normal cells, mature neurons subsist in a quiescent state of the cell cycle, and aberrant cell cycle activation triggers neuronal death accompanied by neurodegeneration. The periodicity of cell cycle events is choreographed by various mechanisms, including DNA damage repair, oxidative stress, neurotrophin activity, and ubiquitin-mediated degradation. Given the relevance of cell cycle processes in cancer and neurodegeneration, this review delineates the overlapping cell cycle events, signaling pathways, and mechanisms associated with cell cycle aberrations in cancer and the major neurodegenerative disorders. We suggest that dysregulation of some common fundamental signaling processes triggers anomalous cell cycle activation in cancer cells and neurons. We discussed the possible use of cell cycle inhibitors for neurodegenerative disorders and described the associated challenges. We propose that a greater understanding of the common mechanisms driving cell cycle aberrations in cancer and neurodegenerative disorders will open a new avenue for the development of repurposed drugs. Cell cycle activation and cell cycle re-entry are the two critical cellular phenomena associated with cancer and neurodegeneration, respectively. Various regulatory proteins, such as cyclin-dependent kinases (CDKs), cyclins, and checkpoint kinases, control the cell cycle dynamics at different phases. Further, the integrity of cell cycle is controlled by different mechanisms like DNA damage response, oxidative stress, neurotrophin activity, and the ubiquitin–proteasome system (UPS), the alterations which play an essential role in the pathogenesis of both cancer and neurodegenerative disorders. Pharmacological targeting of important cell cycle regulatory molecules like the application of CDK inhibitors, PARP inhibitors, checkpoint kinase inhibitors, and microtubule inhibitors holds great promise for treating various human cancers and can be repurposed for different neurodegenerative disorders. [ABSTRACT FROM AUTHOR]

In recent decades, RNA has emerged as an attractive target for the discovery of new small molecules with a wide range of pharmacological activities. Notably, long noncoding RNAs (lncRNAs) have been widely implicated in cancer development. Among these, the overexpression of the lncRNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) has been linked to various types of cancer. In light of this, we carried out a structure-based virtual screening (SBVS) of the FDA-approved drug database towards the crystallographic structure of the triple-helical stability element at the 3'-end of MALAT1. Hence, the thermodynamic analysis led to the selection of five drugs for their evaluation through Molecular Dynamics simulations (MDs). Chlorhexidine and kanamycin emerged as the most promising molecules due to their optimal free energy of binding. In particular, during the MDs, chlorhexidine exhibited the most unstable behavior, demonstrating the ability to explore a wide range of conformations. [ABSTRACT FROM AUTHOR]

Radiation-induced morphea (RIM) is a rare complication of radiotherapy presenting as inflammatory fibrosis, most commonly reported in breast cancer patients. As underlying disease mechanisms are not well understood, targeted therapies are lacking. Since fibroblasts are the key mediators of all fibroproliferative diseases, this study aimed to characterize patient-derived fibroblasts to identify therapeutic targets. We studied primary human control and RIM-fibroblasts on a functional and molecular basis, analyzed peripheral blood and tissue samples and conducted, based on our findings, a treatment attempt in one patient. In RIM, we identified a distinct myofibroblast phenotype reflected by increased alpha-smooth-muscle-actin (αSMA) expression, reduced proliferation and migration rates, and overexpression of osteopontin (OPN). Our RNA sequencing identified aberrant Myc activation as a potential disease driver in RIM fibroblasts, similar to previous findings in systemic sclerosis. Treatment with the anti-inflammatory drug mesalazine reversed the myofibroblast phenotype by targeting Myc. Based on these findings, a patient with RIM was successfully treated with mesalazine, resulting in reduced inflammation and pain and tissue softening, while serum OPN was halved. The present study provides a comprehensive characterization of RIM fibroblasts, suggests a disease-driving role for Myc, demonstrates promising antifibrotic effects of mesalazine and proposes OPN as a biomarker for RIM. [ABSTRACT FROM AUTHOR]

Breast cancer remains a leading cause of mortality among women worldwide, with drug resistance driven by transcription factors and mutations posing significant challenges. To address this, we present ResisenseNet, a predictive model for drug sensitivity and resistance. ResisenseNet integrates transcription factor expression, genomic markers, drugs, and molecular descriptors, employing a hybrid architecture of 1D-CNN + LSTM and DNN to effectively learn long-range and temporal patterns from amino acid sequences and transcription factor data. The model demonstrated exceptional predictive accuracy, achieving a validation accuracy of 0.9794 and a loss value of 0.042. Comprehensive validation included comparisons with state-of-the-art models and ablation studies, confirming the robustness of the developed architecture. ResisenseNet has been applied to repurpose existing anticancer drugs across 14 different cancers, with a focus on breast cancer. Among the malignancies studied, drugs targeting Low-grade Glioma (LGG) and Lung Adenocarcinoma (LUAD) showed increased sensitivity to breast cancer as per ResisenseNet's assessment. Further evaluation of the predicted sensitive drugs revealed that 14 had no prior history of anticancer activity against breast cancer. These drugs target key signaling pathways involved in breast cancer, presenting novel therapeutic opportunities. ResisenseNet addresses drug resistance by filtering ineffective compounds and enhancing chemotherapy for breast cancer. In vitro studies on sensitive drugs provide valuable insights into breast cancer prognosis, contributing to improved treatment strategies. [ABSTRACT FROM AUTHOR]

Marketed valproic acid formulations use its solid salt forms, which are hygroscopic and difficult to handle. The current study focuses on developing valproic acid nanoemulsion using the physically most stable liquid form of the drug and evaluating its anticancer potential. Valproic acid is a histone deacetylase inhibitor having anticancer potential.The valproic acid nanoemulsion was formulated using a facile and scalable homogenization process. The emulsion stabilization was achieved through viscosity-enhancing polymer polyvinylpyrrolidone K-30 and tween 80. The formulation was optimized using the Box-Behnken model of design of experiments and was evaluated for efficacy and safety in cancer and fibroblast cell lines, respectively.The optimized emulsion showed particle size below 150 nm, polydispersity index below 0.3, zeta potential near − 8.5 mV, density 0.9923 g/cm3, viscosity 2.06 poise, creaming index below 20, drug content 100.37%w/v and acceptable stability at accelerated environmental conditions. Overall, under all the studied conditions of in vitro dissolution and ex vivo permeability, drug release from emulsion was found better than the free drug and comparable to the marketed solution of sodium valproate. The cytotoxicity studies demonstrated improved IC50 values for breast and lung cancer cell lines, with selectivity for cancer cells.The valproic acid nanoemulsion was prepared using its physically stable liquid form. The combination of polymer polyvinylpyrrolidone K-30 and tween 80 demonstrated the desired stabilization of the dispersed phase of the emulsion. The formulated nanoemulsion effectively potentiated valproic acid's anticancer activity in cell culture assays. [ABSTRACT FROM AUTHOR]

Dengue is an emerging, mosquito-borne viral disease of international public health concern. Dengue is endemic in more than 100 countries across the world. However, there are no clinically approved antivirals for its cure. Drug repurposing proves to be an efficient alternative to conventional drug discovery approaches in this regard, as approved drugs with an established safety profile are tested for new indications, which circumvents several time-consuming experiments. In the present study, eight approved RNA-dependent RNA polymerase inhibitors of Hepatitis C virus were virtually screened against the Dengue virus polymerase protein, and their antiviral activity was assessed in vitro. Schrödinger software was used for in silico screening, where the compounds were passed through several hierarchical filters. Among the eight compounds, dasabuvir was finally selected for in vitro cytotoxicity and antiviral screening. Cytotoxicity profiling of dasabuvir in Vero cells revealed changes in cellular morphology, cell aggregation, and detachment at 50 μM. Based on these results, four noncytotoxic concentrations of dasabuvir (0.1, 0.25, 0.5, and 1 µM) were selected for antiviral screening against DENV-2 under three experimental conditions: pre-infection, co-infection, and post-infection treatment, by plaque reduction assay. Viral plaques were reduced significantly (p < 0.05) in the co-infection and post-infection treatment regimens; however, no reduction was observed in the pretreatment group. This indicated a possible interference of dasabuvir with NS5 RdRp, as seen from in silico interaction studies, translating into a reduction in virus plaques. Such studies reiterate the usefulness of drug repurposing as a viable strategy in antiviral drug discovery. In this drug repurposing study, dasabuvir, a known anti-hepatitis C drug, was selected through virtual screening and assessed for its anti-dengue activity. [ABSTRACT FROM AUTHOR]

Management of cancer is challenging due to non-targeting and high side effect issues. Drug repurposing is an innovative method for employing medications for other disease therapy in addition to their original use. Simvastatin, a 3-hydroxy-3-methylglutaryl coenzyme-A reductase inhibitor, is a lipid-lowering drug that is being studied for the treatment of cancer in various in vitro and in vivo models. Nanotechnology offers a potential platform for incorporation of drugs with enhanced pharmaceutical (solubility, release characteristics, stability, etc.) and biological characteristics (targeting, pharmacokinetic, pharmacodynamic). Utilizing a variety of resources such as Scopus, Springer, Web of Science, Elsevier, Bentham Science, Taylor & Francis, and PubMed, a thorough literature search was carried out by looking through electronic records published between 2003 and 2024. The keywords used were simvastatin, drug repurposing, anti-cancer simvastatin, pharmaceutical properties of simvastatin, simvastatin nanoformulations, simvastatin patents, clinical trials, etc. Numerous articles were looked for, filtered, checked out, and incorporated. Pure simvastatin has been researched as a repurposed medication for the treatment of cancer in several in vitro and in vivo models, such as carcinoma of the lung, colon, liver, prostate, breast, and skin. Simvastatin also incorporated into different nanocarriers (nanosuspensions, microparticles/nanoparticles, liposomes, and nanostructured lipid carriers) and showed improvement in solubility, bioavailability, drug loading, release kinetics, and targeting. Clinical trial and patent reports suggest potential of simvastatin in cancer therapy. The preclinical studies of pure simvastatin in in vitro and in vivo models showed the potential for its ability to inhibit cancer cell growth and further incorporation into nanoformulations strengthened its preclinical and pharmaceutical characteristics. [ABSTRACT FROM AUTHOR]

Background: Uncontrolled cell proliferation is a major cause of cancer development and progression. Inflammation along with inflammatory mediators and cells play a significant role in cancer. Cancer ranks in second in mortality rates, following cardiac diseases. Phytochemicals from medicinal plants offer a natural and effective approach for treating Inflammation and cancer. Animal studies provide evidence that phytochemicals present in food acts as antioxidants, anti-aging molecules, and health promoters, thereby extending lifespan. These natural compounds include quercetin, epicatechin, resveratrol, curcumin, kaempferol, vitamin C and carotenoids. However, clinical data on humans is still awaited. Conventional allopathic cancer therapies often have severe side effects. Recently, drug repurposing has emerged as an alternative strategy offering lower costs, shorter development times and the advantage of existing clinical data. The primary goal of drug repurposing is to discover new uses for approved or experimental drugs. Short conclusion: The current review elucidates the side effects of synthetic drugs and the beneficial effects of phytochemicals and non-oncological drugs along with their mechanisms of action for treating cancer. Additionally, it highlights clinical trial data for various cancers focusing on molecular targets. By integrating natural products, drug repurposing and molecular targets, we can develop multifaceted therapies that maximize efficacy and minimize adverse effects. This integrated approach promises more personalized and effective treatments, improving patient outcomes and quality of life. Future research should identifying novel natural compounds, explore repurposing opportunities for existing drugs, and elucidate molecular targets for precise therapy. Additionally, clinical trials should be conducted to validate the efficacy and safety of these combined strategies in cancer patients. [ABSTRACT FROM AUTHOR]

Drug repurposing in cancer taps into the capabilities of existing drugs, initially designed for other ailments, as potential cancer treatments. It offers several advantages over traditional drug discovery, including reduced costs, reduced development timelines, and a lower risk of adverse effects. However, not all drug classes align seamlessly with a patient's condition or long-term usage. Hence, repurposing of chronically used drugs presents a more attractive option. On the other hand, metabolic reprogramming being an important hallmark of cancer paves the metabolic regulators as possible cancer therapeutics. This review emphasizes the importance and offers current insights into the repurposing of antidiabetic drugs, including metformin, sulfonylureas, sodium-glucose cotransporter 2 (SGLT2) inhibitors, dipeptidyl peptidase 4 (DPP-4) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), thiazolidinediones (TZD), and α-glucosidase inhibitors, against various types of cancers. Antidiabetic drugs, regulating metabolic pathways have gained considerable attention in cancer research. The literature reveals a complex relationship between antidiabetic drugs and cancer risk. Among the antidiabetic drugs, metformin may possess anti-cancer properties, potentially reducing cancer cell proliferation, inducing apoptosis, and enhancing cancer cell sensitivity to chemotherapy. However, other antidiabetic drugs have revealed heterogeneous responses. Sulfonylureas and TZDs have not demonstrated consistent anti-cancer activity, while SGLT2 inhibitors and DPP-4 inhibitors have shown some potential benefits. GLP-1RAs have raised concerns due to possible associations with an increased risk of certain cancers. This review highlights that further research is warranted to elucidate the mechanisms underlying the potential anti-cancer effects of these drugs and to establish their efficacy and safety in clinical settings. [ABSTRACT FROM AUTHOR]

Visceral cestodiases, like cysticercoses and echinococcoses, are caused by cystic larvae from parasites of the Cestoda class and are endemic or hyperendemic in many areas of the world. Current therapeutic approaches for these diseases are complex and present limitations and risks. Therefore, new safer and more effective treatments are urgently needed. The Niemann-Pick C1 (NPC1) protein is a cholesterol transporter that, based on genomic data, would be the solely responsible for cholesterol uptake in cestodes. Considering that human NPC1L1 is a known target of ezetimibe, used in the treatment of hypercholesterolemia, it has the potential for repurposing for the treatment of visceral cestodiases. Here, phylogenetic, selective pressure and structural in silico analyses were carried out to assess NPC1 evolutive and structural conservation, especially between cestode and human orthologs. Two NPC1 orthologs were identified in cestode species (NPC1A and NPC1B), which likely underwent functional divergence, leading to the loss of cholesterol transport capacity in NPC1A. Comparative interaction analyses performed by molecular docking of ezetimibe with human NPC1L1 and cestode NPC1B pointed out to similarities that consolidate the idea of cestode NPC1B as a target for the repurposing of ezetimibe as a drug for the treatment of visceral cestodiases. [ABSTRACT FROM AUTHOR]

Statins, widely used cardiovascular drugs that lower cholesterol by inhibiting HMG-CoA reductase, have been increasingly recognized for their potential anticancer properties. This study elucidates the underlying mechanism, revealing that statins exploit Synthetic Lethality, a principle where the co-occurrence of two non-lethal events leads to cell death. Our computational analysis of approximately 37,000 SL pairs identified statins as potential drugs targeting genes involved in SL pairs with metastatic genes. In vitro validation on various cancer cell lines confirmed the anticancer efficacy of statins. This data-driven drug repurposing strategy provides a molecular basis for the anticancer effects of statins, offering translational opportunities in oncology. [ABSTRACT FROM AUTHOR]

Purpose: Pancreatic cancer remains a significant public health challenge, with poor long-term outcomes due to the lack of effective treatment options. Repurposing commonly used clinical drugs, such as ACE inhibitors, ARBs, CCBs, and metformin, may enhance the efficacy of chemotherapy and offer a promising therapeutic strategy for improving patient outcomes. Methods: A retrospective analysis of concomitant treatment with ACE-Is, ARBs, CCBs, and metformin alongside gemcitabine chemotherapy in patients with pancreatic cancer was conducted. Treatment responses were evaluated, with overall survival (OS) estimated using the Kaplan–Meier method. Additionally, the Cox proportional hazards model was employed to assess the impact of these specific agents on patient survival. Results: 4628 patients with various stages of pancreatic cancer were identified in the database between 2007 and 2016. The estimated overall survival (OS) in the analyzed group was 6.9 months (95% CI 6.4–7). The use of any of the analyzed drugs was associated with a significant improvement in mOS of 7.5 months (95% CI 6.8–7.8) vs. 6.7 months (95% CI 6.4–7.0) for patients who did not have additional treatment (p < 0.0001). ARBs, ACE-Is, CCBs, and metformin varied in their effectiveness in prolonging mOS among patients. The longest mOS of 8.9 months (95% CI 7.7–11.6) was observed in patients receiving additional therapy with ARBs, while the shortest mOS of 7.7 months (95% CI 6.5–8.9) was achieved by patients receiving metformin. In the adjusted Cox analysis, metformin was associated with a significantly weaker effect on mOS (p = 0.029). A particularly interesting trend in prolonging 5-year survival was demonstrated by ARBs and CCBs with 14.1% (95% CI 9–22%) and 14.8% (95% CI 11.1–19.6%), respectively, compared to patients not taking these drugs, who achieved a 5-year OS of 3.8% (95% CI 3.2–4.4%). Conclusion: Our results demonstrate a significant positive impact of ARBs, ACE inhibitors, and CCBs on survival in patients with pancreatic cancer treated with gemcitabine. The addition of these inexpensive and relatively safe drugs in patients with additional comorbidities may represent a potential therapeutic option in this indication. However, prospective clinical trials to evaluate the optimal patient population and further studies to determine the potential impact of these agents on chemotherapy are necessary. [ABSTRACT FROM AUTHOR]

Antibiotics are the super drugs that have revolutionized modern medicine by curing many infectious diseases caused by various microbes. They efficiently inhibit the growth and multiplication of the pathogenic microbes without causing adverse effects on the host. However, prescribing suboptimal antibiotic and overuse in agriculture and animal husbandry have led to the emergence of antimicrobial resistance, one of the most serious threats to global health at present. The efficacy of a new antibiotic is high when introduced; however, a small bacterial population attains resistance gradually and eventually survives. Understanding the mode of action of these miracle drugs, as well as their interaction with targets is very complex. However, it is necessary to fulfill the constant need for novel therapeutic alternatives to address the inevitable development of resistance. Therefore, considering the need of the hour, this article has been prepared to discuss the mode of action and recent advancements in the field of antibiotics. Efforts has also been made to highlight the current scenario of antimicrobial resistance and drug repurposing as a fast-track solution to combat the issue. [ABSTRACT FROM AUTHOR]

Background: Obstructive sleep apnea (OSA) is one of the foremost potential severe disorders, with frequent episodes of complete or partial obstructions of the upper airway during sleep. Therefore, several attempts to find an effective pharmacotherapy by repurposing several drugs such as serotonin reuptake inhibitors (SRIs) and norepinephrine and dopamine reuptake inhibitors (NDRIs) were recently considered as alternative therapeutic strategy. So, in this review, we will present non-conventional pharmacological approaches for managing OSA via either repurposing selected natural products or traditional medicine. Evidence acquisition: Scientific databases and literature reviewed in the last twenty years were screened using different keywords related to OSA; exclusion criteria were applied based on the accessibility and the ability of the sources to follow evidence-based approaches. The eligible resources were classified into two main categories: clinical-based studies and preclinical studies. The findings of these studies were analyzed and discussed in light of current evidence derived from recent studies. Findings: Several natural components and traditional formulas were found to regulate several molecular targets involved in OSA pathogenesis, supported by several in-vitro and in-vivo studies. Also, natural products subjected to clinical trials give promising results. Still, there are some limitations, such as involving a small number of patients depending on subjective yet acceptable scores rather than objective scores, a lack of positive control groups, or a small number of patients. Conclusion: Therapeutic protocols should consider non-conventional polypharmacological strategies targeting all OSA aspects. Hence, there is an opportunity to reposition some well-defined natural products, such as cinnamic acid derivatives, isoflavones, and lignans, as several evidences from in-vitro, in-vivo, and clinical trials support their potential efficacy in the management of OSA. [ABSTRACT FROM AUTHOR]

Bladder cancer is a common malignancy worldwide, posing a substantial healthcare challenge. Current standard treatment regimens are primarily based on cisplatin, but their success is often limited by cisplatin resistance and associated toxicities. Therefore, there is an urgent need to develop effective and less toxic therapies as alternatives to cisplatin. We screened the activity of FDA-approved anti-cancer drugs on a panel of cisplatin-resistant bladder cancer cell lines. Based on initial responses, cabazitaxel was selected for further evaluation of its inhibitory effects on the phenotypic properties of these cells. Cabazitaxel, primarily used for metastatic castration-resistant prostate cancer, demonstrated remarkable efficacy in inhibiting colony formation, proliferation, and migration of cisplatin-resistant bladder cancer cells. This study highlights the potential of drug repurposing as a cost-effective and efficient strategy to overcome drug resistance in bladder cancer. [ABSTRACT FROM AUTHOR]

Context: Computational drug repurposing methods have been continuously developed in recent years to alleviate the high costs associated with drug development. As drug targets or the products of disease-related genes, proteins play an important role in drug repurposing. Although the potential has been demonstrated, heterogeneous graphs with proteins as independent nodes have yet to be studied, where extracting high-quality protein features from heterogeneous graphs poses a significant challenge. A novel drug repurposing model based on the feature construction of multi-layer ensemble (DRML-Ensemble) is proposed in this study. The performance of DRML-Ensemble, as evaluated on publicly available datasets, achieves an AUPR value of 0.93 and an AUROC value of 0.92, surpassing those of existing state-of-the-art methods. Additionally, DRML-Ensemble demonstrates its notable ability for drug repurposing in Alzheimer's disease. Methods: DRML-Ensemble is primarily composed of multiple layers of heterogeneous graph feature construction (HGFC). Each HGFC can extract protein features by leveraging the relationships between drugs, diseases, and proteins. These protein features are then utilized in subsequent layers to build drug and disease features, facilitating drug repurposing. By stacking multiple layers, optimal protein features can be obtained from the heterogeneous graph, consequently improving the accuracy of drug repurposing. However, an excessive· stacking of layers usually affect the model's training process, for example, causing problems such as overfitting; a multi-layer ensemble prediction module is designed to further improve the model's performance. [ABSTRACT FROM AUTHOR]

Uric acid has been linked to various disease outcomes. However, it remains unclear whether uric acid-lowering therapy could be repurposed as a treatment for conditions other than gout. We first performed both observational phenome-wide association study (Obs-PheWAS) and polygenic risk score PheWAS (PRS-PheWAS) to identify associations of uric acid levels with a wide range of disease outcomes. Then, trajectory analysis was conducted to explore temporal progression patterns of the observed disease outcomes. Finally, we investigated whether uric acid-lowering drugs could be repurposed using a factorial Mendelian randomization (MR) study design. A total of 41 overlapping phenotypes associated with uric acid levels were identified by both Obs- and PRS- PheWASs, primarily cardiometabolic diseases. The trajectory analysis illustrated how elevated uric acid levels contribute to cardiometabolic diseases, and finally death. Meanwhile, we found that uric acid-lowering drugs exerted a protective role in reducing the risk of coronary atherosclerosis (OR = 0.96, 95%CI: 0.93, 1.00, P = 0.049), congestive heart failure (OR = 0.64, 95%CI: 0.42, 0.99, P = 0.043), occlusion of cerebral arteries (OR = 0.93, 95%CI: 0.87, 1.00, P = 0.044) and peripheral vascular disease (OR = 0.60, 95%CI: 0.38, 0.94, P = 0.025). Furthermore, the combination of uric acid-lowering therapy (e.g. xanthine oxidase inhibitors) with antihypertensive treatment (e.g. calcium channel blockers) exerted additive effects and was associated with a 6%, 8%, 8%, 10% reduction in risk of coronary atherosclerosis, heart failure, occlusion of cerebral arteries and peripheral vascular disease, respectively. Our findings support a role of elevated uric acid levels in advancing cardiovascular dysfunction and identify potential repurposing opportunities for uric acid-lowering drugs in cardiovascular treatment. [ABSTRACT FROM AUTHOR]