Search

UNLABELLED: Identifying improved treatments for severe and refractory coccidioidomycosis (Valley fever) is needed. This endemic fungal disease is common in North and South America, and cases have increased substantially over the last 30 years. The current standard of care, oral daily fluconazole, often fails to completely eradicate Coccidioides infection; however, the high cost of identifying new compounds effective in treating Valley fever is a barrier to improving treatment. Therefore, repurposing existing pharmaceutical agents in combination with fluconazole therapy is an attractive option. We screened the Library of Pharmacologically Active Compounds (LOPAC) small molecule library for compounds that inhibited fungal growth in vitro and determined IC50 values for a subset of compounds. Based on these findings, we tested a small subset of these agents to validate the screen, as well as to test the performance of fluconazole in a combination therapy approach, as compared with fluconazole alone, in a murine model. We observed that combination therapy of tamoxifen:fluconazole and sertraline:fluconazole significantly reduced the burden of live fungus in the lung compared with fluconazole alone, and we observed reduced or nonexistent dissemination. These results suggest that tamoxifen and sertraline may be repurposed as adjunctive agents in the treatment of this important fungal disease. IMPORTANCE: Developing new drugs, especially for regional orphan diseases, such as Valley Fever, is a slow and costly endeavor. However, there is a wealth of FDA-approved drugs available for repurposing, offering a more economical and expedited approach to improve treatment. Those existing compounds with antifungal properties can become novel therapies with relative ease: a considerable advantage for patients in need of alternative treatment. Despite the scope of remaining tasks, our comprehensive screening of potential candidates has revealed promising combinations for further exploration. This effort outlines a practical pipeline for Valley fever drug screening and identifies viable drug combinations that could impact patients more rapidly than single drug development pathways.

INTRODUCTION: Bumetanide, a loop diuretic, was identified as a candidate drug for repurposing for Alzheimers disease (AD) based on its effects on transcriptomic apolipoprotein E signatures. Cross-sectional analyses of electronic health records suggest that bumetanide is associated with decreased prevalence of AD; however, temporality between bumetanide exposure and AD development has not been established. METHODS: We evaluated Medicare claims data using Cox proportional hazards regression to evaluate the association between time-dependent use of bumetanide and time to first AD diagnosis while controlling for patient characteristics. Multiple sensitivity analyses were conducted to test the robustness of the findings. RESULTS: We sampled 833,561 Medicare beneficiaries, 60.8% female, with mean (standard deviation) age of 70.4 (12). Bumetanide use was not significantly associated with AD risk (hazard ratio 1.05; 95% confidence interval, 0.99-1.10). DISCUSSION: Using a nationwide dataset and a retrospective cohort study design, we were not able to identify a time-dependent effect of bumetanide lowering AD risk. HIGHLIGHTS: Bumetanide was identified as a candidate for repurposing for Alzheimers disease (AD). We evaluated the association between bumetanide use and risk of AD. We used Medicare data and accounted for duration of bumetanide use. Bumetanide use was not significantly associated with risk of AD.

Senicapoc, a small molecule inhibitor of the calcium-activated potassium channel KCa3.1, was safe and well-tolerated in clinical trials for sickle cell anemia. We previously reported proof-of-concept data suggesting that both pharmacological inhibition and genetic deletion of KCa3.1 reduces infarction and improves neurologic recovery in rodents by attenuating neuroinflammation. Here we evaluated the potential of repurposing senicapoc for ischemic stroke. In cultured microglia, senicapoc inhibited KCa3.1 currents with an IC50 of 7 nM, reduced Ca2+ signaling induced by the purinergic agonist ATP, suppressed expression of pro-inflammatory cytokines and enzymes (iNOS and COX-2), and prevented induction of the inflammasome component NLRP3. When transient middle cerebral artery occlusion (tMCAO, 60 min) was induced in male C57BL/6 J mice, twice daily administration of senicapoc at 10 and 40 mg/kg starting 12 h after reperfusion dose-dependently reduced infarct area determined by T2-weighted magnetic resonance imaging (MRI) and improved neurological deficit on day 8. Ultra-high-performance liquid chromatography/mass spectrometry analysis of total and free brain concentrations demonstrated sufficient KCa3.1 target engagement. Senicapoc treatment significantly reduced microglia/macrophage and T cell infiltration and activation and attenuated neuronal death. A different treatment paradigm with senicapoc started at 3 h and MRI on day 3 and day 8 revealed that senicapoc reduces secondary infarct growth and suppresses expression of inflammation markers, including T cell cytokines in the brain. Lastly, we demonstrated that senicapoc does not impair the proteolytic activity of tissue plasminogen activator (tPA) in vitro. We suggest that senicapoc could be repurposed as an adjunctive immunocytoprotective agent for combination with reperfusion therapy for ischemic stroke.

PurposeTriple-negative breast cancer (TNBC) often metastasizes to the central nervous system (CNS) and has the highest propensity among breast cancer subtypes to develop leptomeningeal disease (LMD). LMD is a spread of cancer into leptomeningeal space that speeds up the disease progression and severely aggravates the prognosis. LMD has limited treatment options. We sought to test whether the common anti-helminthic drug mebendazole (MBZ) may be effective against murine TNBC LMD.MethodsA small-molecule screen involving TNBC cell lines identified benzimidazoles as potential therapeutic agents for further study. In vitro migration assays were used to evaluate cell migration capacity and the effect of MBZ. For in vivo testing, CNS metastasis was introduced into BALB/c athymic nude mice through internal carotid artery injections of brain-tropic MDA-MB-231-BR or MCF7-BR cells. Tumor growth and spread was monitored by bioluminescence imaging and immunohistochemistry. MBZ was given orally at 50 and 100 mg/kg doses. MBZ bioavailability was assayed by mass spectrometry.ResultsBioinformatic analysis and migration assays revealed higher migratory capacity of TNBC compared to other breast cancer subtypes. MBZ effectively slowed down migration of TNBC cell line MDA-MB-231 and its brain tropic derivative MDA-MB-231-BR. In animal studies, MBZ reduced leptomeningeal spread, and extended survival in brain metastasis model produced by MDA-MB-231-BR cells. MBZ did not have an effect in the non-migratory MCF7-BR model.ConclusionsWe demonstrated that MBZ is a safe and effective oral agent in an animal model of TNBC CNS metastasis. Our findings are concordant with previous efforts involving MBZ and CNS pathology and support the drug's potential utility to slow down leptomeningeal spread.

Inherited retinopathies are devastating diseases that in most cases lack treatment options. Disease-modifying therapies that mitigate pathophysiology regardless of the underlying genetic lesion are desirable due to the diversity of mutations found in such diseases. We tested a systems pharmacology-based strategy that suppresses intracellular cAMP and Ca2+ activity via G protein-coupled receptor (GPCR) modulation using tamsulosin, metoprolol, and bromocriptine coadministration. The treatment improves cone photoreceptor function and slows degeneration in Pde6βrd10 and RhoP23H/WT retinitis pigmentosa mice. Cone degeneration is modestly mitigated after a 7-month-long drug infusion in PDE6A-/- dogs. The treatment also improves rod pathway function in an Rpe65-/- mouse model of Leber congenital amaurosis but does not protect from cone degeneration. RNA-sequencing analyses indicate improved metabolic function in drug-treated Rpe65-/- and rd10 mice. Our data show that catecholaminergic GPCR drug combinations that modify second messenger levels via multiple receptor actions provide a potential disease-modifying therapy against retinal degeneration.

ABSTRACT Notch1 and Notch2, transmembrane receptors belonging to the Notch family, are pivotal mediators of intercellular communication and have profound implications including cell fate determination, embryonic development, and tissue homeostasis in various cellular processes. Despite their structural homology, Notch1 and Notch2 exhibit discrete phenotypic characteristics and functional nuances that necessitate their individualized targeting in specific medical scenarios. Aberrant Notch signaling, often driven by the dysregulated activity of one receptor over the other, is implicated under various pathological conditions. Notch1 dysregulation is frequently associated with T‐cell acute lymphoblastic leukemia, whereas Notch2 perturbations are linked to B‐cell malignancies and solid tumors, including breast cancer. Hence, tailored therapeutic interventions that selectively inhibit the relevant Notch receptor need to be devised to disrupt the signaling pathways driving the specific disease phenotype. In this review, we emphasize the importance of distinct tissue‐specific expression patterns, functional divergence, disease‐specific considerations, and the necessity to minimize off‐target effects that collectively underscore the significance of “individualized” targeting for Notch1 and Notch2. This comprehensive review sheds light on the receptor‐specific characteristics of Notch1 and Notch2, providing insights into their roles in cellular processes and offering opportunities for developing tailored therapeutic interventions in the fields of biomedical research and clinical practice. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) is considered the most aggressive form of breast cancer owing to the negative expression of targetable bioreceptors. Epithelial to mesenchymal transition (EMT) associated with metastatic abilities is its critical feature. As an attempt to target TNBC, nanotechnology was utilised to augment the effects of drug repurposing. Concerning that, a combination therapeutic module was structured with one of the aspects being a repurposed antihistamine, promethazine hydrochloride loaded PLGA nanoparticles. The as-synthesized nanoparticles were 217 nm in size and fluoresced at 522 nm, rendering them suitable for theranostic applications too. The second feature of the module was a common histone deacetylase inhibitor, suberoylanilide hydroxamic acid (SAHA), used as a form of pre-treatment. Experimental studies demonstrated efficient cellular internalisation and significant innate anti-proliferative potential. The use of SAHA sensitised the cells to the drug loaded nanoparticle treatment. Mechanistic studies showed increase in ROS generation, mitochondrial dysfunction followed by apoptosis. Investigations into protein expression also revealed reduction of mesenchymal proteins like vimentin by 1.90 fold; while increase in epithelial marker like E-Cadherin by 1.42 fold, thus indicating an altered EMT dynamics. Further findings also provided better insight into the benefits of SAHA potentiated targeting of tumor spheroids that mimic solid tumors of TNBC. Thus, this study paves the avenue to a more rational translational validation of combining nanotherapeutics with drug repurposing. [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]

Scorpion envenomation, a grave public health concern, is primarily driven by the potent neurotoxins chlorotoxin and leiurotoxin present in Leiurus species venom. Developing effective treatments is crucial to mitigate its impact. Utilizing a drug-repositioning bioinformatics-based approach, potential inhibitors of these neurotoxins were identified from Food and Drug Administration (FDA)-approved drugs. Through virtual screening and subsequent molecular dynamics simulations, their ability to stabilize the peptides over time was evaluated. Among the compounds scrutinized, bolazine emerged as a promising candidate, demonstrating significant affinity for both neurotoxins, indicating potential dual inhibitory activity. Molecular dynamics simulations further corroborated the enhanced stability of bolazine complexes compared to neurotoxins alone. These findings suggest the feasibility of repurposing existing drugs to develop new therapeutic strategies to treat scorpion envenomation. Such interventions hold promise in alleviating the severe health repercussions of scorpion stings and meeting the urgent demand for effective remedies in affected communities. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the most commonly occurring and most aggressive primary brain tumor. Transcriptomics-based tumor subtype classification has established the mesenchymal lineage of GBM (MES-GBM) as cancers with particular aggressive behavior and high levels of therapy resistance. Previously it was show that Trihexyphenidyl (THP), a market approved M1 muscarinic receptor-targeting oral drug can suppress proliferation and survival of GBM stem cells from the classical transcriptomic subtype. In a series of in vitro experiments, this study confirms the therapeutic potential of THP, by effectively suppressing the growth, proliferation and survival of MES-GBM cells with limited effects on non-tumor cells. Transcriptomic profiling of treated cancer cells identified genes and associated metabolic signaling pathways as possible underlying molecular mechanisms responsible for THP-induced effects. In vivo trials of THP in immunocompromised mice carry orthotopic MES-GBMs showed moderate response to the drug. This study further highlights the potential of THP repurposing as an anti-cancer treatment regimen but mode of action and d optimal treatment procedures for in vivo regimens need to be investigated further. [ABSTRACT FROM AUTHOR]

Biomarkers associated with the progression from gastric intestinal metaplasia (GIM) to gastric adenocarcinoma (GA), i.e., GA-related GIM, could provide valuable insights into identifying patients with increased risk for GA. The aim of this study was to utilize multi-bioinformatics to reveal potential biomarkers for the GA-related GIM and predict potential drug repurposing for GA prevention in patients. The multi-bioinformatics included gene expression matrix (GEM) by microarray gene expression (MGE), ScType (a fully automated and ultra-fast cell-type identification based solely on a given scRNA-seq data), Ingenuity Pathway Analysis, PageRank centrality, GO and MSigDB enrichments, Cytoscape, Human Protein Atlas and molecular docking analysis in combination with immunohistochemistry. To identify GA-related GIM, paired surgical biopsies were collected from 16 GIM-GA patients who underwent gastrectomy, yielding 64 samples (4 biopsies per stomach x 16 patients) for MGE. Co-analysis was performed by including scRNAseq and immunohistochemistry datasets of endoscopic biopsies of 37 patients. The results of the present study showed potential biomarkers for GA-related GIM, including GEM of individual patients, individual genes (such as RBP2 and CD44), signaling pathways, network of molecules, and network of signaling pathways with key topological nodes. Accordingly, potential treatment targets with repurposed drugs were identified including epidermal growth factor receptor, proto-oncogene tyrosine-protein kinase Src, paxillin, transcription factor Jun, breast cancer type 1 susceptibility protein, cellular tumor antigen p53, mouse double minute 2, and CD44. [ABSTRACT FROM AUTHOR]

Classical Zn2+-dependent deac(et)ylases play fundamental regulatory roles in life and are well characterized in eukaryotes regarding their structures, substrates and physiological roles. In bacteria, however, classical deacylases are less well understood. We construct a Generalized Profile (GP) and identify thousands of uncharacterized classical deacylases in bacteria, which are grouped into five clusters. Systematic structural and functional characterization of representative enzymes from each cluster reveal high functional diversity, including polyamine deacylases and protein deacylases with various acyl-chain type preferences. These data are supported by multiple crystal structures of enzymes from different clusters. Through this extensive analysis, we define the structural requirements of substrate selectivity, and discovered bacterial de-d-/l-lactylases and long-chain deacylases. Importantly, bacterial deacylases are inhibited by archetypal HDAC inhibitors, as supported by co-crystal structures with the inhibitors SAHA and TSA, and setting the ground for drug repurposing strategies to fight bacterial infections. Thus, we provide a systematic structure-function analysis of classical deacylases in bacteria and reveal the basis of substrate specificity, acyl-chain preference and inhibition. In bacteria Zn2+-dependent deacylases are underexplored. Here, the authors identify bacterial deacylases, providing systemic structure-function analyses to reveal the basis of substrate specificity, acyl-chain preference and inhibition. [ABSTRACT FROM AUTHOR]

Given that there is currently no clinically approved drug or vaccine for parainfluenza 3 (PIV3), we applied a drug repurposing method based on disease similarity and chemical similarity to screen 2,585 clinically approved chemical drugs using PIV3 potential drugs BCX-2798 and zanamivir as our controls. Twelve candidate drugs were obtained after being screened with good disease similarity and chemical similarity (S > 0.50, T > 0.56). When docking them with the PIV3 target protein, hemagglutinin-neuraminidase (HN), only oseltamivir was docked with a better score than BCX-2798, which indicates that oseltamivir has an inhibitory effect on PIV3. After the distance ( Z d c ) between the drug target of 14 drugs and the PIV3 disease target was measured by the network proximity method based on the PIV3 disease module, it was found that the Z d c values of amikacin, oseltamivir, ribavirin, and streptomycin were less than those of the control. Thus, oseltamivir is the best potential drug because it met all the above screening requirements. Additionally, to explore whether oseltamivir binds to HN stably, molecular dynamics simulation of the binding of oseltamivir to HN was carried out, and the results showed that the RMSD value of the complex tended to be stable within 100 ns, and the binding free energy of the complex was low (−10.60 kcal/mol). It was proved that oseltamivir screened by our drug repurposing method had the potential feasibility of treating PIV3. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, we applied translational informatics for intelligent medicine of acute myeloid leukemia, a type of cancer characterized by disease relapses even after seemingly successful treatments. Treatment failure is associated, at least in part, with the fact that targeting individual proteins often promotes rewiring of relevant networks and re-organization of interactions of, among others, non-targeted proteins to eventually evade single-target therapies. To develop efficient therapies, these dynamics should be taken into account and target whole network modules instead of singleton genes in order to prevent the establishment of compensating signaling circuits. Therefore, we integrated network-based methods, structural pharmacology, and molecular modeling to establish two complementary multitargeting strategies, one in the form of repurposable drug combinations and the other as a de novo synthesized triple-targeting agent. Of note, our study exploits, for the first time, a greedy algorithm to identify optimal combinations of drugs and therapeutic protein targets. Background/Objectives: Acute myeloid leukemia (AML) is characterized by therapeutic failure and long-term risk for disease relapses. As several therapeutic targets participate in networks, they can rewire to eventually evade single-target drugs. Hence, multi-targeting approaches are considered on the expectation that interference with many different components could synergistically hinder activation of alternative pathways and demolish the network one-off, leading to complete disease remission. Methods: Herein, we established a network-based, computer-aided approach for the rational design of drug combinations and de novo agents that interact with many AML network components simultaneously. Results: A reconstructed AML network guided the selection of suitable protein hubs and corresponding multi-targeting strategies. For proteins responsive to existing drugs, a greedy algorithm identified the minimum amount of compounds targeting the maximum number of hubs. We predicted permissible combinations of amiodarone, artenimol, fostamatinib, ponatinib, procaine, and vismodegib that interfere with 3–8 hubs, and we elucidated the pharmacological mode of action of procaine on DNMT3A. For proteins that do not respond to any approved drugs, namely cyclins A1, D2, and E1, we used structure-based de novo drug design to generate a novel triple-targeting compound of the chemical formula C15H15NO5, with favorable pharmacological and drug-like properties. Conclusions: Overall, by integrating network and structural pharmacology with molecular modeling, we determined two complementary strategies with the potential to annihilate the AML network, one in the form of repurposable drug combinations and the other as a de novo synthesized triple-targeting agent. These target–drug interactions could be prioritized for preclinical and clinical testing toward precision medicine for AML. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic is caused by the SARS-CoV-2 virus, whose internalization and infection are mediated by the angiotensin-converting enzyme 2 (ACE2). The identification of novel approaches to tackle this step is instrumental for the development of therapies for the management of COVID-19 and other diseases with a similar mechanism of infection. Thalidomide, a drug sadly known for its teratogenic effects, has potent immunomodulatory and anti-inflammatory properties. Treatment with this drug has been shown to improve the immune functions of COVID-19 patients and proposed for the management of COVID-19 in clinical practice through drug repositioning. Here, we investigated the molecular details linking thalidomide to ACE2 and COVID-19, showing that in conditions mimicking SARS-CoV-2-associated cytokine storm, the transcription factor ΔNp63α and ACE2 are stabilized, and IL-8 production is increased. In such conditions, we found p63 to bind to and regulate the expression of the ACE2 gene. We previously showed that ΔNp63α is degraded upon thalidomide treatment and now found that treatment with this drug—or with its analogue lenalidomide—downregulates ACE2 in a p63-dependent manner. Finally, we found that thalidomide treatment reduces in vitro infection by pseudo-SARS-CoV-2, a baculovirus pseudotyped with the SARS-CoV-2 spike protein. Overall, we propose the dual effect of thalidomide in reducing SARS-CoV-2 viral re-entry and inflammation through p63 degradation to weaken SARS-CoV-2 entry into host cells and mitigate lung inflammation, making it a valuable option in clinical management of COVID-19. Key messages: Thalidomide treatment results in p63-dependent ACE2 downregulation. ACE2 is a p63 transcriptional target. Thalidomide reduces the "cytokine storm" associated to COVID-19. Thalidomide prevents viral re-entry of SARS-CoV-2 by p63-dependent ACE2 downregulation. Thalidomide is a modulator of SARS-CoV-2 or other ACE2-dependent infections. ACE2 is modulated by a pharmacological substance. [ABSTRACT FROM AUTHOR]

Aberrant fucosylation is the hallmark of malignant cell transformation, leading to many cellular events, such as uncontrolled cell proliferation, angiogenesis, tumor cell invasion, and metastasis. This increased fucosylation is caused due to the over-expression of fucosyltransferases (FUTs) that catalyzes the transfer of the fucose (Fuc) residue from GDP-fucose (donor substrate) to various oligosaccharides, glycoproteins, and glycolipids (acceptor substrates). Hence, fucosyltransferases (FUTs) are considered as validated target for the drug discovery against on cancers. In the current study, a drug repurposing approach was deployed to identify new hits against fucosyltransferase 2 (FUT2), using computational and biophysical techniques. A library of 500 US-FDA approved drugs were screened in-silico against fucosyltransferase 2 (FUT2) donor and acceptor sites. Five drugs were predicted as hits, based on their significant docking scores (-5.8 to -8.2), and binding energies (-43 to -51.19 Kcal/mol). Furthermore, STD-NMR highlighted the epitope of these drugs in the binding site of fucosyltransferase 2 (FUT2). Simulation studies provided insights about the binding site of these drugs, and 4 of them, acarbose, ascorbic acid, ibuprofen, and enalaprilat dihydrate, were found as significant binders at the donor binding site of fucosyltransferase 2 (FUT2). Hence, the current study reports the repurposed drugs as potential hits against fucosyltransferase 2 (FUT2). These may be further studied through in-vitro and in-vivo inhibitory and mechanistic studies. [ABSTRACT FROM AUTHOR]

AbstractSince its emergence shortly after the discovery of penicillin, antibiotic resistance has escalated dramatically, posing a significant health threat and economic burden. Drug repositioning, or drug repurposing, involves identifying new therapeutic applications for existing drugs, utilising their established safety profiles and pharmacological data to swiftly provide effective treatments against resistant pathogens. Several drugs, including otilonium bromide, penfluridol, eltrombopag, ibuprofen, and ceritinib, have demonstrated potent antibacterial activity against multidrug-resistant (MDR) bacteria. These drugs can disrupt biofilms, damage bacterial membranes, and inhibit bacterial growth. The combination of repurposed drugs with conventional antibiotics can reduce the required dosage of individual drugs, mitigate side effects, and delay the development of resistance, making it a promising strategy against MDR bacteria such as Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Escherichia coli. Despite its promise, drug repurposing faces challenges such as potential off-target effects, toxicity, and regulatory and intellectual property issues, necessitating rigorous evaluations and strategic solutions. This article aims to explore the potential of drug repurposing as a strategy to combat antibiotic resistance, examining its benefits, challenges, and future prospects. We address the legal, economic, and practical challenges associated with repurposing existing drugs, highlight successful examples, and propose solutions to enhance the efficacy and viability of this approach in combating MDR bacterial infections. [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]

Accurately predicting drug-target affinity is crucial in expediting the discovery and development of new drugs, which is a complex and risky process. Identifying these interactions not only aids in screening potential compounds but also guides further optimization. To address this, we propose a multi-perspective feature fusion model, MFF-DTA, which integrates chemical structure, biological sequence, and other data to comprehensively capture drug-target affinity features. The MFF-DTA model incorporates multiple feature learning components, each of which is capable of extracting drug molecular features and protein target information, respectively. These components are able to obtain key information from both global and local perspectives. Then, these features from different perspectives are efficiently combined using specific splicing strategies to create a comprehensive representation. Finally, the model uses the fused features to predict drug-target affinity. Comparative experiments show that MFF-DTA performs optimally on the Davis and KIBA data sets. Ablation experiments demonstrate that removing specific components results in the loss of unique information, thus confirming the effectiveness of the MFF-DTA design. Improvements in DTA prediction methods will decrease costs and time in drug development, enhancing industry efficiency and ultimately benefiting patients. • The MFF-DTA model is proposed to accurately predict the affinity relationship between drugs and target proteins. • The model includes multiple feature extractors to capture global and local key features. • We create a comprehensive and information-rich representation. • The model has demonstrated strong performance on public datasets. [ABSTRACT FROM AUTHOR]

This study explores the repurposing of Food and Drug Administration (FDA)-approved drugs as potential inhibitors of SARS-CoV-2 papain-like protease (PLpro), a critical enzyme for viral replication. Initially, 3009 FDA approved drugs were screened to identify candidates structurally similar to the co-crystallized ligand XT7 in the SARS-CoV-2 PLpro complex (PDB ID: 7LBR). A fingerprint analysis narrowed the selection to the top 5%)150 drugs) most structurally akin to XT7, followed by a more refined structural similarity test that identified the top 1% (30 drugs). Molecular docking studies highlighted several compounds with strong binding affinities to the SARS-CoV-2 PLpro. Notably, Fedratinib exhibited a particularly robust binding energy of − 2 0. 5 4 kcal/mol and was chosen for further investigation. Subsequent molecular dynamics (MD) simulations over 100 ns confirmed the stability and efficacy of Fedratinib's binding, as evidenced by favorable energetic and dynamic profiles. The molecular mechanics-generalized born surface area (MM-GBSA) calculations corroborated these findings, revealing a binding energy of − 2 4. 3 6 kcal/mol. Additionally, PLIP, ProLIF, and PCAT analyses further validated the stability and interactions of the PLpro-Fedratinib complex observed during the MD simulations. Overall, our results indicate that Fedratinib, an FDA-approved drug, demonstrates promising potential as an inhibitor of SARS-CoV-2 PLpro, warranting further in vitro and in vivo experimental validation as well as potential clinical evaluation. 3009 FDA-approved drugs subjected to ligand-based computational studies to select the most similar 30 drugs to the co-crystallized ligand, XT7, in of SARS-CoV-2 PLpro (PDB ID: 7LBR). Molecular docking studies highlighted Fedratinib's robust binding energy and excellent binding mode. MD simulations, MM-GBSA, PLIP, ProLIF, and PCAT analyses validated the stability and interactions of the PLpro-Fedratinib complex [ABSTRACT FROM AUTHOR]

Alzheimer's disease is a devastating neurodegenerative condition that exerts a significant global burden. Despite recent efforts, disease modifying therapies remain extremely limited, with a tremendous proportion of patients having to rely on symptomatic treatment only. Epidemiological and pathological overlaps exist between Alzheimer's disease and diabetes mellitus type 2, with people with diabetes mellitus type 2 at a significantly increased risk of developing Alzheimer's disease in the future. Incretin mimetics, also known as GLP-1/GIP receptor agonists, are useful tools licensed for the treatment of diabetes mellitus type 2 which have recently been the subject of news coverage for their off-label use as weight loss medications. Emerging evidence highlights the possible neuroprotective function of incretin mimetics in models of Alzheimer's disease as well as in clinical studies. This review details the pre-clinical and clinical studies that have explored the effectiveness of incretin mimetics to alleviate Alzheimer's disease associated pathology and cognitive impairment, while also highlighting the progress made to examine the effectiveness of these molecules in Parkinson's disease. Should clinical trials prove effective, incretin mimetics may be able to be repurposed and become useful novel tools as disease-modifying treatments for Alzheimer's disease and other neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Drug repurposing is a methodology used to identify new clinical indications for existing drugs developed for other indications and has been successfully applied in the treatment of numerous conditions. Alzheimer's disease (AD) may be particularly well-suited to the application of drug repurposing methods given the absence of effective therapies and abundance of multi-omic data that has been generated in AD patients recently that may facilitate discovery of candidate AD drugs. A recent focus of drug repurposing has been in the application of pharmacoepidemiologic approaches to drug evaluation. Here, real-world clinical datasets with large numbers of patients are leveraged to establish observational efficacy of candidate drugs for further evaluation in disease models and clinical trials. In this review, we provide a selected overview of methods for drug repurposing, including signature matching, network analysis, molecular docking, phenotypic screening, semantic network, and pharmacoepidemiological analyses. Numerous methods have also been applied specifically to AD with the aim of nominating novel drug candidates for evaluation. These approaches, however, are prone to numerous limitations and potential biases that we have sought to address in the Drug Repurposing for Effective Alzheimer's Medicines (DREAM) study, a multi-step framework for selection and validation of potential drug candidates that has demonstrated the promise of STAT3 inhibitors and re-evaluated evidence for other drug candidates, such as phosphodiesterase inhibitors. Taken together, drug repurposing holds significant promise for development of novel AD therapeutics, particularly as the pace of data generation and development of analytical methods continue to accelerate. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a neurodegenerative disorder that is the most common form of dementia in the elderly. The drugs currently used to treat AD only have limited effects and are not able to cure the disease. Drug repositioning has increasingly become a promising approach to find potential drugs for diseases like AD. Objective: To screen potential drug candidates for AD based on the relationship between risk genes of AD and drugs. Methods: We collected the risk genes of AD and retrieved the information of known drugs from DrugBank. Then, the AD-related genes and the targets of each drug were mapped to the human protein-protein interaction network (PPIN) to represent AD and the drugs on the network. The network distances between each drug and AD were calculated to screen the drugs proximal to AD-related genes on PPIN, and the screened drug candidates were further analyzed by molecular docking and molecular dynamics simulations. Results: We compiled a list of 714 genes associated with AD. From 5,833 drugs used for human diseases, we identified 1,044 drugs that could be potentially used to treat AD. Then, amyloid-β (Aβ) protein, the key molecule involved in the pathogenesis of AD was selected as the target to further screen drugs that may inhibit Aβ aggregation by molecular docking. We found that ergotamine and RAF-265 could bind stably with Aβ. In further analysis by molecular dynamics simulations, both drugs exhibited reasonable stability. Conclusions: Our work indicated that ergotamine and RAF-265 may be potential candidates for treating AD. [ABSTRACT FROM AUTHOR]

Drug repurposing in glomerular disease can deliver opportunities for steroid-free regimens, enable personalized multi-target options for resistant or relapsing disease and enhance treatment options for understudied populations (for example, children) and in resource-limited settings. Identification of drug-repurposing candidates can be data driven, which utilizes existing data on disease pathobiology, drug features and clinical outcomes, or experimental, which involves high-throughput drug screens. Information from databases of approved drugs, clinical trials and PubMed registries suggests that at least 96 drugs on the market cover 49 targets with immunosuppressive potential that could be candidates for drug repurposing in glomerular disease. Furthermore, evidence to support drug repurposing is available for 191 immune drug target–glomerular disease pairs. Non-immunological drug repurposing includes strategies to reduce haemodynamic overload, podocyte injury and kidney fibrosis. Recommended strategies to expand drug-repurposing capacity in glomerular disease include enriching drug databases with glomeruli-specific information, enhancing the accessibility of primary clinical trial data, biomarker discovery to improve participant selection into clinical trials and improve surrogate outcomes and initiatives to reduce patent, regulatory and organizational hurdles. Drug repurposing could expand the therapeutic options available to patients with glomerular disease. Here, the authors examine different approaches to the identification of drug candidates, consider current immunosuppressive and non-immunological options and discuss strategies to maximize drug repurposing in glomerular disease. Key points: Drug repurposing can improve the treatment of glomerular disease by providing steroid-free regimens, enabling options for resistant or relapsing disease, enhancing treatment options for understudied populations and increasing therapy options in resource-limited settings. Contemporary methods of identifying drug-repurposing candidates can be data driven or experimental. At least 96 drugs on the market have targets with immunosuppressive potential that could be candidates for repurposing for glomerular disease treatment. Non-immunological drug repurposing for glomerular disease involves strategies to reduce haemodynamic overload, podocyte injury and kidney fibrosis. Strategies to expand drug-repurposing capacity need to enrich datasets with glomeruli-specific information, enhance the accessibility of clinical trial data, improve biomarker discovery and address patent, regulatory and organizational hurdles. [ABSTRACT FROM AUTHOR]

The Kirsten Rat Sarcoma (KRAS) G12D mutant protein is a primary driver of pancreatic ductal adenocarcinoma, necessitating the identification of targeted drug molecules. Repurposing of drugs quickly finds new uses, speeding treatment development. This study employs microsecond molecular dynamics simulations to unveil the binding mechanisms of the FDA‐approved MEK inhibitor trametinib with KRASG12D, providing insights for potential drug repurposing. The binding of trametinib was compared with clinical trial drug MRTX1133, which demonstrates exceptional activity against KRASG12D, for better understanding of interaction mechanism of trametinib with KRASG12D. The resulting stable MRTX1133‐KRASG12D complex reduces root mean square deviation (RMSD) values, in Switch I and II domains, highlighting its potential for inhibiting KRASG12D. MRTX1133's robust interaction with Tyr64 and disruption of Tyr96‐Tyr71‐Arg68 network showcase its ability to mitigate the effects of the G12D mutation. In contrast, trametinib employs a distinctive binding mechanism involving P‐loop, Switch I and II residues. Extended simulations to 1 μs reveal sustained network interactions with Tyr32, Thr58, and GDP, suggesting a role of trametinib in maintaining KRASG12D in an inactive state and impede the further cell signaling. The decomposition binding free energy values illustrate amino acids' contributions to binding energy, elucidating ligand–protein interactions and molecular stability. The machine learning approach reveals that van der Waals interactions among the residues play vital role in complex stability and the potential amino acids involved in drug–receptor interactions of each complex. These details provide a molecular‐level understanding of drug binding mechanisms, offering essential knowledge for further drug repurposing and potential drug discovery. [ABSTRACT FROM AUTHOR]

Investigating Drug-Target Interactions (DTI) is crucial for drug repositioning and discovery tasks. However, discovering DTIs through experimental approaches is time-consuming and requires substantial financial resources. To address these challenges, machine learning-based methodologies have been adopted to reduce costs and save time. Unfortunately, the effectiveness of these methods has been limited due to the binary classification approach and the lack of empirically validated negative samples. The availability of abundant DTI datasets and protein structure data has enabled the development of new approaches, such as redefining the DTI problem as a regression task. Given this context, we propose an innovative deep-learning approach to predict binding affinities between drugs and targets. Our model, named the Convolution Self-Attention Network with Attention-based Bidirectional Long Short-Term Memory Network (CSAN-BiLSTM-Att), integrates convolutional neural network (CNN) blocks with self-attention mechanisms to create an attention-based bidirectional long short-term memory (BiLSTM) model, followed by fully connected layers. Due to the model's complexity, proper hyperparameter tuning is essential. To optimize this, we employ the Differential Evolution (DE) technique to select the most suitable hyperparameters. Experimental results demonstrate that the DE-based CSAN-BiLSTM-Att model outperforms previous approaches. Specifically, the model achieved a concordance index of 0.898 and a mean square error of 0.228 on the DAVIS dataset, and a concordance value of 0.971 with a mean square error of 0.014 on the KIBA dataset. [ABSTRACT FROM AUTHOR]

This article discusses the rationale and design of the study "Methotrexate, blood pressure, and arterial function in rheumatoid arthritis". The recognition that immune activation and excess inflammation favor atherosclerosis has stimulated a significant body of research not only to identify new drugs targeting these pathways but also to repurpose (reposition) existing immunomodulatory medications as atheroprotective agents. Observational studies in patients with rheumatoid arthritis have reported that treatment with methotrexate, a traditional disease-modifying antirheumatic drug, is associated with a significantly lower risk of cardiovascular morbidity and mortality when compared with other disease-modifying antirheumatic drugs. One potential mechanism accounting for the reduced cardiovascular risk associated with methotrexate is the lowering effect on arterial blood pressure. However, such effect has only been observed in cross-sectional and observational studies. Given the established role of hypertension as a leading cardiovascular risk factor, these observations justify an intervention comparison study, the focus of this article, investigating the temporal effects of methotrexate on blood pressure and various surrogate markers of atherosclerosis in patients with rheumatoid arthritis. The results of this study might lead to the repurposing of methotrexate for cardiovascular prevention in patients with and without autoimmune disorders. Clinical Trial Registration:NCT03254589 (ClinicalTrials.gov). Plain Language Summary This article describes a research study looking at the effects of a well-established antirheumatic drug, methotrexate, on blood pressure and blood vessels in patients with rheumatoid arthritis, a disabling condition affecting the joints as well as other organs and tissues. Methotrexate is commonly used in rheumatoid arthritis, given its ability to suppress inflammation and the activation of the immune system. However, excessive inflammation and immune activation are linked to atherosclerosis, a condition characterised by the build-up of plaques in blood vessels and the development of clots. Therefore, methotrexate might also be helpful in combating atherosclerosis because of its ability to suppress inflammation and immune system activation. We have previously observed that patients with rheumatoid arthritis receiving methotrexate have lower blood pressure when compared with patients receiving other antirheumatic drugs. However, in this study we could not prove that methotrexate directly reduces blood pressure. Given that high blood pressure is well known to damage the blood vessels and promote atherosclerosis and its devastating manifestations, for example, heart attack and stroke, this article will discuss a new study that compares blood pressure for individuals assigned to different treatments to assess whether methotrexate can lower blood pressure over time and exert additional beneficial effects on blood vessels in patients with rheumatoid arthritis. The results of this study will be helpful in determining whether methotrexate can be routinely used to combat atherosclerosis and consequently reduce the risk of heart attack and stroke in patients with rheumatoid arthritis and, potentially, other patient groups. Article highlights There is an ongoing search for new drugs and the repurposing of marketed drugs with immunomodulatory effects conferring atheroprotection. The study "Methotrexate, blood pressure and arterial function in rheumatoid arthritis" will investigate whether methotrexate reduces blood pressure and markers of atherosclerosis in patients with rheumatoid arthritis. The results of this study will be helpful to determine whether methotrexate can be repurposed for cardiovascular prevention. [ABSTRACT FROM AUTHOR]

In the colorectal cancer (CRC) niche, the transcription factors signal transducer and activator of transcription 3 (STAT3) and nuclear factor‐κB (NF‐κB) are hyperactivated in both malignant cells and tumor‐infiltrating leukocytes (TILs) and cooperate to maintain cancer cell proliferation/survival and drive protumor inflammation. Through drug repositioning studies, the anthelmintic drug rafoxanide has recently emerged as a potent and selective antitumor molecule for different types of cancer, including CRC. Here, we investigate whether rafoxanide could negatively modulate STAT3/NF‐κB and inflammation‐associated CRC. The antineoplastic effect of rafoxanide was explored in a murine model of CRC resembling colitis‐associated disease. Cell proliferation and/or STAT3/NF‐κB activation were evaluated in colon tissues taken from mice with colitis‐associated CRC, human CRC cells, and CRC patient‐derived explants and organoids after treatment with rafoxanide. The STAT3/NF‐κB activation and cytokine production/secretion were assessed in TILs isolated from CRC specimens and treated with rafoxanide. Finally, we investigated the effects of TIL‐derived supernatants cultured with or without rafoxanide on CRC cell proliferation and STAT3/NF‐κB activation. The results showed that rafoxanide restrains STAT3/NF‐κB activation and inflammation‐associated colon tumorigenesis in vivo without apparent effects on normal intestinal cells. Rafoxanide markedly reduces STAT3/NF‐κB activation in cultured CRC cells, CRC‐derived explants/organoids, and TILs. Finally, rafoxanide treatment impairs the ability of TILs to produce protumor cytokines and promote CRC cell proliferation. We report the novel observation that rafoxanide negatively affects STAT3/NF‐κB oncogenic activity at multiple levels in the CRC microenvironment. Our data suggest that rafoxanide could potentially be deployed as an anticancer drug in inflammation‐associated CRC. [ABSTRACT FROM AUTHOR]

Biomedical network learning offers fresh prospects for expediting drug repositioning. However, traditional network architectures struggle to quantify the relationship between micro-scale drug spatial structures and corresponding macro-scale biomedical networks, limiting their ability to capture key pharmacological properties and complex biomedical information crucial for drug screening and therapeutic discovery. Moreover, challenges such as difficulty in capturing long-range dependencies hinder current network-based approaches. To address these limitations, we introduce the Spatial Hierarchical Network, modeling molecular 3D structures and biological associations into a unified network. We propose an end-to-end framework, SpHN-VDA, integrating spatial hierarchical information through triple attention mechanisms to enhance machine understanding of molecular functionality and improve the accuracy of virus-drug association identification. SpHN-VDA outperforms leading models across three datasets, particularly excelling in out-of-distribution and cold-start scenarios. It also exhibits enhanced robustness against data perturbation, ranging from 20% to 40%. It accurately identifies critical motifs for binding sites, even without protein residue annotations. Leveraging reliability of SpHN-VDA, we have identified 25 potential candidate drugs through gene expression analysis and CMap. Molecular docking experiments with the SARS-CoV-2 spike protein further corroborate the predictions. This research highlights the broad potential of SpHN-VDA to enhance drug repositioning and identify effective treatments for various diseases. The Spatial Hierarchical Network model enhances drug repositioning by quantifying and integrating 3D spatial network with biomedical network information and offers interpretations from biological relationships down to atomic interactions. [ABSTRACT FROM AUTHOR]

In the crucial process of drug discovery and repurposing, precise prediction of drug-target interactions (DTIs) is paramount. This study introduces a novel DTI prediction approach—Multi-Layer Graph Attention Neural Network (MLGANN), through a groundbreaking computational framework that effectively harnesses multi-source information to enhance prediction accuracy. MLGANN not only strides forward in constructing a multi-layer DTI network by capturing both direct interactions between drugs and targets as well as their multi-level information but also amalgamates Graph Convolutional Networks (GCN) with a self-attention mechanism to comprehensively integrate diverse data sources. This method exhibited significant performance surpassing existing approaches in comparative experiments, underscoring its immense potential in elevating the efficiency and accuracy of DTI predictions. More importantly, this study accentuates the significance of considering multi-source data information and network heterogeneity in the drug discovery process, offering new perspectives and tools for future pharmaceutical research. [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]

DPAGT1-CDG is a Congenital Disorder of Glycosylation (CDG) that lacks effective therapies. It is caused by mutations in the gene DPAGT1 which encodes the first enzyme in N-linked glycosylation. We used a Drosophila rough eye model of DPAGT1-CDG with an improperly developed, small eye phenotype. We performed a drug repurposing screen on this model using 1,520 small molecules that are 98% FDA/EMA-approved to find drugs that improved its eye. We identified 42 candidate drugs that improved the DPAGT1-CDG model. Notably from this screen, we found that pharmacological and genetic inhibition of the dopamine D2 receptor partially rescued the DPAGT1-CDG model. Loss of both dopamine synthesis and recycling partially rescued the model, suggesting that dopaminergic flux and subsequent binding to D2 receptors is detrimental under DPAGT1 deficiency. This links dopamine signaling to N-glycosylation and represents a new potential therapeutic target for treating DPAGT1-CDG. We also genetically validate other top drug categories including acetylcholine-related drugs, COX inhibitors, and an inhibitor of NKCC1. These drugs and subsequent analyses reveal novel biology in DPAGT1 mechanisms, and they may represent new therapeutic options for DPAGT1-CDG. Author summary: Some proteins require the attachment of sugars—like mannose and galactose—in order to perform their function. The process that attaches these sugars is called "glycosylation". Genetic mutations in glycosylation pathways cause Congenital Disorders of Glycosylation ("CDGs"). CDGs are devastating disorders causing a multitude of symptoms, including seizures and developmental delay, and they have few treatment options. We wanted to find new potential treatment options for the CDG called DPAGT1-CDG. We use a model of DPAGT1-CDG that has inhibited glycosylation resulting in impaired eye development. We used a "drug repurposing screen", where we screened 1,520 drugs that are 99% FDA- or EMA-approved, to find drugs that improved its eye. We found 42 drug hits, including classes like dopamine receptor inhibitors, NSAIDs, and antihistamines. We found that the dopamine receptor inhibitors caused the strongest improvement. In addition, genetically impairing multiple parts of the dopamine pathway (e.g. how dopamine is made or recycled) also improved the model. This suggests that dopamine signaling is important in DPAGT1-CDG, and it could represent a new therapeutic option for patients. Overall, we present validation of several of our drugs, and these represent potential new treatments while also improving our understanding of glycosylation. [ABSTRACT FROM AUTHOR]

Metals have been used in medicine for centuries. However, it was not until much later that the effects of inorganic drugs could be rationalized from a mechanistic point of view. Today, thanks to the technologies available, this approach has been functionally developed and implemented. It has been found that there is probably no single biological target for the pharmacological effects of most inorganic drugs. Herein, we present an overview of some integrated and multi‐technique approaches to elucidate the molecular interactions underlying the biological effects of metallodrugs. On this premise, selected examples are used to illustrate how the information obtained on metal‐based drugs and their respective mechanisms can become relevant for applications in fields other than medicine. For example, some well‐known metallodrugs, which have been shown to bind specific amino acid residues of proteins, can be used to solve problems related to protein structure elucidation in crystallographic studies. Diruthenium tetraacetate can be used to catalyze the conversion of hydroxylamines to nitrones with a high selectivity when bound to lysozyme. Finally, a case study is presented in which an unprecedented palladium/arsenic‐mediated catalytic cycle for nitrile hydration was discovered thanks to previous studies on the solution chemistry of the anticancer compound arsenoplatin‐1 (AP‐1). [ABSTRACT FROM AUTHOR]

Treating bacterial infections triggered by multidrug‐resistant bacteria is a global priority. Issue of multidrug resistance can be managed by inhibiting bacterial quorum sensing mechanism. Quorum‐sensing inhibitors (QSIs) are promising alternatives to antibiotics. Herein, a library of FDA‐approved anthelmintic medications was screened using in silico techniques for LuxR protein associated with the quorum‐sensing (QS) mechanism of Staphylococcus aureus. Drug repurposing can reduce the time and financial risk of drug development. Seven FDA‐approved drugs (Fenbendazole, Mebendazole, Flubendazole, Praziquantel, Oxyclozanide, Rafoxanide, and Albendazole) showed strong binding affinity to the LuxR protein with binding free energy less than −6.00 kcal/mol. Molecular dynamic simulation (100 ns) of the docked complexes revealed that Fenbendazole and Rafoxanide remain at the binding pocket of the LuxR protein most of the time. During the whole simulation period, backbone of all seven complexes displayed small fluctuation in the RMSD and Rg. The free energy landscape of LuxR–Rafoxanide and LuxR–Fenbendazole complexes showed promising stability compared to the rest of the complexes. Both the complexes showed excellent MMPBSA binding free energy: −92.882 ± 15.636 kJ/mol (LuxR–Rafoxanide) and −74.873 ± 9.233 kJ/mol (LuxR–Fenbendazole). The reactivity of the ligands was ascertained from their DFT‐based various descriptors. [ABSTRACT FROM AUTHOR]

Transforming growth factor β1 (TGF‐β) is a cytokine with pleiotropic biological functions. Recently, its signaling pathway has been highlighted for its implicative paradoxical roles in prostate cancer (PCa). Suppressing downstream effects of this pathway by interfering with receptor complex formation through inhibition of the TGF‐β1 leads to its antitumor effects, illuminating the TGF‐β1 as a viable therapeutic target for PCa. Our compound library—established by a literature‐based approach that identified phytochemicals with published evidence against the TGF‐β1—was screened by employing molecular docking, density functional theory (DFT), and molecular dynamic (MD) simulations to identify TGF‐β1 inhibitors. Eight of the 24 phytochemicals docked from our compound library had a good binding affinity (ranging from −11.7 to −10 kcal/mol) to the TGF‐β1 (PDB: 1PY5). The phytochemicals displayed good stability and reactivity as revealed by the DFT analysis and a desirable pharmacokinetic profile. The top four phytochemical complexes with high binding energies maintained stability throughout the 100 ns simulation. Qualitative studies on the drug repurposing attributes of bisindolylmaleimide, flavopiridol, baicalin, and gefitinib as inhibitors of TGF‐β1 are recommended; most importantly, suggest further wet‐lab studies to corroborate these phytochemicals—SB 202190, SB 203580, silymarin, and cryptotanshinone—in TGF‐β1 targeted drug development. [ABSTRACT FROM AUTHOR]

Transcriptome-wide association study (TWAS) is a popular approach to dissect the functional consequence of disease associated non-coding variants. Most existing TWAS use bulk tissues and may not have the resolution to reveal cell-type specific target genes. Single-cell expression quantitative trait loci (sc-eQTL) datasets are emerging. The largest bulk- and sc-eQTL datasets are most conveniently available as summary statistics, but have not been broadly utilized in TWAS. Here, we present a new method EXPRESSO (EXpression PREdiction with Summary Statistics Only), to analyze sc-eQTL summary statistics, which also integrates 3D genomic data and epigenomic annotation to prioritize causal variants. EXPRESSO substantially improves existing methods. We apply EXPRESSO to analyze multi-ancestry GWAS datasets for 14 autoimmune diseases. EXPRESSO uniquely identifies 958 novel gene x trait associations, which is 26% more than the second-best method. Among them, 492 are unique to cell type level analysis and missed by TWAS using whole blood. We also develop a cell type aware drug repurposing pipeline, which leverages EXPRESSO results to identify drug compounds that can reverse disease gene expressions in relevant cell types. Our results point to multiple drugs with therapeutic potentials, including metformin for type 1 diabetes, and vitamin K for ulcerative colitis. The authors describe a new transcriptome-wide association study (TWAS) method that integrates single cell eQTL summary statistics with GWAS data to identify cell type-specific risk genes, together with a cell type-aware drug repurposing pipeline. [ABSTRACT FROM AUTHOR]

Depression and Parkinson's disease (PD) are devastating psychiatric and neurological disorders that require the development of novel therapeutic interventions. Drug repurposing targeting predefined pharmacological targets is a widely use approach in modern drug discovery. Monoamine oxidase B (MAOB) is a critical protein implicated in Depression and PD. In this study, we undertook a systematic exploration of repurposed drugs as potential inhibitors of MAO-B. Exploring a library of 3,648 commercially available drug molecules, we conducted virtual screening using a molecular docking approach to target the MAO-B binding pocket. Two promising drug molecules, Brexpiprazole and Trifluperidol, were identified based on their exceptional binding potential and drug profiling. Subsequently, all-atom molecular dynamics (MD) simulations were performed on the MAO-B-ligand complexes for a trajectory of 300 nanoseconds (ns). Simulation results demonstrated that the binding of Brexpiprazole and Trifluperidol induced only minor structural alterations in MAO-B and showed significant stabilization throughout the simulation trajectory. Overall, the finding suggests that Brexpiprazole and Trifluperidol exhibit strong potential as repurposed inhibitors of MAO-B that might be explored further in experimental investigations for the development of targeted therapies for depression and PD. [ABSTRACT FROM AUTHOR]

Repurposing generic drugs as new treatments for life-threatening diseases such as cancer is an exciting yet largely overlooked opportunity due to a lack of market-driven incentives. Nonprofit organizations and other non-manufacturers have been ramping up efforts to repurpose widely available generic drugs and rapidly expand affordable treatment options for patients. However, these nonmanufacturers find it difficult to obtain regulatory approval in the U.S. Without a straightforward path for approval and updating drug labeling, non-manufacturers have relied on off-label use of repurposed drugs. This limits the broad clinical adoption of these drugs and patient access. In this paper, we explore the regulatory landscape for repurposing of small molecule generic drugs within the U.S. We describe case studies of repurposed drugs that have been successfully incorporated into clinical treatment guidelines for cancer without regulatory approval. To encourage greater adoption of generic drugs in clinical practice-that is, to encourage the repurposing of these drugs-we examine existing Food and Drug Administration (FDA) pathways for approval of new uses or indications for generic drugs. We show how non-manufacturers, who are generally more active in generic drug repurposing than manufacturers, could utilize existing regulatory authorities and pathways, and we describe the challenges they face. We propose an extension of the existing 505(b)(2) new drug application (NDA) approval pathway, called a "labeling-only" 505(b)(2) NDA, that would enable non-manufacturers to seek approval of new indications for well-established small molecule drugs when multiple generic products are already available. It would not require new chemistry, manufacturing, and controls (CMC) data or introducing new drug products into the marketplace. This pathway would unlock innovation broadly and enable patients to benefit from the enormous potential of low-cost generic drugs. [ABSTRACT FROM AUTHOR]

Glioblastoma remains the most prevalent and aggressive primary malignant brain tumor in adults, characterized by limited treatment options and a poor prognosis. Previous drug repurposing efforts have yielded only marginal survival benefits, particularly those involving inhibitors targeting receptor tyrosine kinase and cyclin-dependent kinase-retinoblastoma pathways. This limited efficacy is likely due to several critical challenges, including the tumor's molecular heterogeneity, the dynamic evolution of its genetic profile, and the restrictive nature of the blood-brain barrier that impedes effective drug delivery. Emerging diagnostic tools, such as circulating tumor DNA and extracellular vesicles, offer promising non-invasive methods for real-time tumor monitoring, potentially enabling the application of targeted therapies to more selected patient populations. Moreover, innovative drug delivery strategies, including focused ultrasound, implantable drug-delivery systems, and engineered nanoparticles, hold potential for enhancing the bioavailability and therapeutic efficacy of treatments. [ABSTRACT FROM AUTHOR]

Investigator-initiated clinical studies (IICSs), also referred to as non-commercial, academic or independent clinical studies, address important research questions that are usually neglected by industry despite their high societal value. Indeed, industry may direct their focus and resources on studies that will yield results and products that can ultimately generate revenue for the company. Conversely, IICS research questions include (a) refining or getting new indications of available treatments (drug repurposing); (b) optimisation, by comparing various health products or treatment regimens; and (c) innovation, especially for advanced therapies. Multinational IICSs increase the scientific quality of the data by exchange of research ideas, scientific techniques and tools. Participation of patients from different geographical, social and ethnic backgrounds equally adds to the value of study results and yields more generalisable evidence than a study confined to a single geographical location. Multinational IICSs are generally sponsored by non-profit/academic organisations and publicly funded. Funding has been already identified as a main challenge for the conduct IICS and especially for clinical trials (IICTs, IICS where a medical intervention is directly tested). Main barriers to the conduct of multinational IICTs with public funding include: Limitations of budget and duration of the eligibility of costs Lack of flexibility to move funds transnationally Tendering rules Complexity in the reporting of the eligible costs to funders We describe why there is a need to support multinational IICS, what should be their objectives and what are the current funding mechanisms in Europe. Strategies for funding multinational IICS should evolve to mitigate identified barriers, thus facilitating research that can provide answers to highly relevant questions in healthcare which are less likely to be answered by studies funded by the pharmaceutical and medical device industry. [ABSTRACT FROM AUTHOR]

Proteins are the primary targets of almost all small molecule drugs. However, even the most selectively designed drugs can potentially target several unknown proteins. Identification of potential drug targets can facilitate design of new drugs and repurposing of existing ones. Current state-of-the-art proteomics methodologies enable screening of thousands of proteins against a limited number of drug molecules. Here we report the development of a label-free quantitative proteomics approach that enables proteome-wide screening of small organic molecules in a scalable, reproducible, and rapid manner by streamlining the proteome integral solubility alteration (PISA) assay. We used rat organs ex-vivo to determine organ specific targets of medical drugs and enzyme inhibitors to identify drug targets for common drugs such as Ibuprofen. Finally, global drug profiling revealed overarching trends of how small molecules affect the proteome through either direct or indirect protein interactions. Many drug targets remain unknown for small molecules. Here, the authors develop a label-free Proteome Integral Solubility Alteration (PISA) workflow to automate target identification and analysis. Applied to rat organs, the authors identify previously unknown drug targets for common medication. [ABSTRACT FROM AUTHOR]

Drug‐target binding affinity (DTA) prediction is vital for drug repositioning. The accuracy and generalizability of DTA models remain a major challenge. Here, we develop a model composed of BERT‐Trans Block, Multi‐Trans Block, and DTI Learning modules, referred to as Molecular Representation Encoder‐based DTA prediction (MREDTA). MREDTA has three advantages: (1) extraction of both local and global molecular features simultaneously through skip connections; (2) improved sensitivity to molecular structures through the Multi‐Trans Block; (3) enhanced generalizability through the introduction of BERT. Compared with 12 advanced models, benchmark testing of KIBA and Davis datasets demonstrated optimal performance of MREDTA. In case study, we applied MREDTA to 2034 FDA‐approved drugs for treating non‐small‐cell lung cancer (NSCLC), all of which act on mutant EGFRT790M protein. The corresponding molecular docking results demonstrated the robustness of MREDTA. [ABSTRACT FROM AUTHOR]

Background and Aims: Anti‐angiogenic therapies prolong patient survival in some malignancies but not glioblastoma. We focused on the relationship between the differentiation of glioma stem like cells (GSCs) into tumor derived endothelial cells (TDECs) and, anti‐angiogenic therapy resistance. Especially we aimed to elucidate the mechanisms of drug resistance of TDECs to anti‐angiogenic inhibitors and identify novel anti‐angiogenic drugs with clinical applications. Results: The mouse GSCs, 005, were differentiated into TDECs under hypoxic conditions, and TDECs had endothelial cell characteristics independent of the vascular endothelial growth factor (VEGF) pathway. In vivo, inhibition of the VEGF pathway had no anti‐tumor effect and increased the percentage of TDECs in the 005 mouse model. Novel anti‐angiogenic drugs for glioblastoma were evaluated using a tube formation assay and a drug repositioning strategy with existing blood–brain barrier permeable drugs. Drug screening revealed that the antidepressant sertraline inhibited tube formation of TDECs. Sertraline was administered to differentiated TDECs in vitro and 005 mouse models in vivo to evaluate genetic changes by RNA‐Seq and tumor regression effects by immunohistochemistry and MRI. Sertraline reduced Lama4 and Ang2 expressions of TDEC, which play an important role in non‐VEGF‐mediated angiogenesis in tumors. The combination of a VEGF receptor inhibitor axitinib, and sertraline improved survival and reduced tumor growth in the 005 mouse model. Conclusion: Collectively, our findings showed the diversity of tumor vascular endothelial cells across VEGF and non‐VEGF pathways led to anti‐angiogenic resistance. The combination of axitinib and sertraline can represent an effective anti‐angiogenic therapy for glioblastoma with safe, low cost, and fast availability. [ABSTRACT FROM AUTHOR]

Simple Summary: Drug repurposing offers a valuable approach for utilizing FDA-approved drugs to address new diseases, including cancer, while significantly reducing the time and cost associated with drug development. In this review, we highlight the anticancer potential of anthelmintic benzimidazole derivatives, such as mebendazole (MBZ), fenbendazole (FBZ), flubendazole (FLBZ), and albendazole (ABZ), with a particular focus on their efficacy against blood cancers. These compounds operate through multiple mechanisms, including disrupting microtubule formation, regulating the cell cycle, inducing cellular differentiation, and modulating key signaling pathways involved in cancer progression. The ability of benzimidazoles to exert these diverse effects on malignant cells suggests their promise as therapeutic agents for hematological cancers. Furthermore, investigating their use in combination with standard-of-care treatments may lead to the development of novel, more effective therapeutic strategies, offering new avenues of hope for patients with blood malignancies. Drug repurposing is a strategy to discover new therapeutic uses for existing drugs, which have well-established toxicity profiles and are often more affordable. This approach has gained significant attention in recent years due to the high costs and low success rates associated with traditional drug development. Drug repositioning offers a more time- and cost-effective path for identifying new treatments. Several FDA-approved non-chemotherapy drugs have been investigated for their anticancer potential. Among these, anthelmintic benzimidazoles (such as albendazole, mebendazole, and flubendazole) have garnered interest due to their effects on microtubules and oncogenic signaling pathways. Blood cancers, which frequently develop resistance and have high mortality rates, present a critical need for effective therapies. This review highlights the recent advances in repurposing benzimidazoles for blood malignancies. These compounds induce cell cycle arrest, differentiation, tubulin depolymerization, loss of heterozygosity, proteasomal degradation, and inhibit oncogenic signaling to exert their anticancer effects. We also discuss current limitations and strategies to overcome them, emphasizing the potential of combining benzimidazoles with standard therapies for improved treatment of hematological cancers. [ABSTRACT FROM AUTHOR]

Despite recent advances in chronic obstructive pulmonary disease (COPD) research, few studies have identified the potential therapeutic targets systematically by integrating multiple-omics datasets. This project aimed to develop a systems biology pipeline to identify biologically relevant genes and potential therapeutic targets that could be exploited to discover novel COPD treatments via drug repurposing or de novo drug discovery. A computational method was implemented by integrating multi-omics COPD data from unpaired human samples of more than half a million subjects. The outcomes from genome, transcriptome, proteome, and metabolome COPD studies were included, followed by an in silico interactome and drug-target information analysis. The potential candidate genes were ranked by a distance-based network computational model. Ninety-two genes were identified as COPD signature genes based on their overall proximity to signature genes on all omics levels. They are genes encoding proteins involved in extracellular matrix structural constituent, collagen binding, protease binding, actin-binding proteins, and other functions. Among them, 70 signature genes were determined to be druggable targets. The in silico validation identified that the knockout or over-expression of SPP1, APOA1, CTSD, TIMP1, RXFP1, and SMAD3 genes may drive the cell transcriptomics to a status similar to or contrasting with COPD. While some genes identified in our pipeline have been previously associated with COPD pathology, others represent possible new targets for COPD therapy development. In conclusion, we have identified promising therapeutic targets for COPD. This hypothesis-generating pipeline was supported by unbiased information from available omics datasets and took into consideration disease relevance and development feasibility. [ABSTRACT FROM AUTHOR]

The pursuit of novel therapeutics is a complex and resource-intensive endeavor marked by significant challenges, including high costs and low success rates. In response, drug repositioning strategies leverage existing FDA-approved compounds to predict their efficacy across diverse diseases. Peptidyl arginine deiminase 4 (PAD4) plays a pivotal role in protein citrullination, a process implicated in the autoimmune pathogenesis of rheumatoid arthritis (RA). Targeting PAD4 has thus emerged as a promising therapeutic approach. This study employs computational and enzyme inhibition strategies to identify potential PAD4-targeting compounds from a library of FDA-approved drugs. In silico docking analyses validated the binding interactions and orientations of screened compounds within PAD4's active site, with key residues such as ASP350, HIS471, ASP473, and CYS645 participating in crucial hydrogen bonding and van der Waals interactions. Molecular dynamics simulations further assessed the stability of top compounds exhibiting high binding affinities. Among these compounds, Saquinavir (SQV) emerged as a potent PAD4 inhibitor, demonstrating competitive inhibition with a low IC50 value of 1.21 ± 0.04 μM. In vitro assays, including enzyme kinetics and biophysical analyses, highlighted significant changes in PAD4 conformation upon SQV binding, as confirmed by circular dichroism spectroscopy. SQV induced localized alterations in PAD4 structure, effectively occupying the catalytic pocket and inhibiting enzymatic activity. These findings underscore SQV's potential as a therapeutic candidate for RA through PAD4 inhibition. Further validation through in vitro and in vivo studies is essential to confirm SQV's therapeutic benefits in autoimmune diseases associated with dysregulated citrullination. [ABSTRACT FROM AUTHOR]

GPR119 agonists are being developed to safeguard the function of pancreatic β‐cells, especially in the context of non‐alcoholic fatty pancreas disease (NAFPD) that is closely associated with β‐cell dysfunction. This study aims to employ a drug repurposing strategy to screen GPR119 agonists and explore their potential molecular mechanisms for enhancing β‐cell function in the context of NAFPD. MIN6 cells were stimulated with palmitic acid (PA), and a NAFPD model was established in GPR119−/− mice fed with a high‐fat diet (HFD). Terazosin, identified through screening, was utilized to assess its impact on enhancing β‐cell function via the MST1‐Foxo3a pathway and mitophagy. Terazosin selectively activated GPR119, leading to increased cAMP and ATP synthesis, consequently enhancing insulin secretion. Terazosin administration improved high blood glucose, obesity, and impaired pancreatic β‐cell function in NAFPD mice. It inhibited the upregulation of MST1‐Foxo3a expression in pancreatic tissue and enhanced damaged mitophagy clearance, restoring autophagic flux, and improving mitochondrial quantity and structure in β‐cells. Nevertheless, GPR119 deficiency negated the positive impact of terazosin on pancreatic β‐cell function in NAFPD mice and abolished its inhibitory effect on the MST1‐Foxo3a pathway. Terazosin activates GPR119 on the surface of pancreatic β‐cells, enhancing mitophagy and alleviating β‐cell dysfunction in the context of NAFPD by suppressing the MST1‐Foxo3a signalling pathway. Terazosin could be considered a priority treatment for patients with concomitant NAFPD and hypertension. [ABSTRACT FROM AUTHOR]

Background and Purpose Experimental Approach Key Results Conclusion and Implications Drug repurposing (DR) offers a compelling alternative to traditional drug discovery's lengthy, resource‐intensive process. DR is the process of identifying alternative clinical applications for pre‐approved drugs as a low‐risk and low‐cost strategy. Computational approaches are crucial during the early hypothesis‐generating stage of DR. However, ‘large‐scale’ data retrieval remains a significant challenge. A computational workflow addressing such limitations might improve hypothesis generation, ultimately benefit patients and advance DR research.We introduce a novel computational workflow (combining free‐accessible computational platforms) to provide ‘proof‐of‐concept’ of the pre‐approved drug's suitability for repurposing. Three key phases are included: target fishing (via reverse pharmacophore mapping), target identification (via disease‐ and drug‐target pathway identification) and retrospective literature and drug‐like analysis (via in silico ADMET properties determination). Istradefylline is a Parkinson's disease‐approved drug with literature‐attributed antidepressant properties remaining unclear. Practically applied, istradefylline's antidepressant activity was assessed in the context of major depressive disorder (MDD).Data mining aided by target identification resulted in istradefylline potentially representing a novel antidepressant drug class. Retrieved drug targets (KYNU, MAO‐B, ALOX12 and PLCB2) associated with selected MDD pathways (tryptophan metabolism and serotonergic synapse) generated a hypothesis that istradefylline increased extracellular 5‐HT levels (MAO‐B inhibition) and reduced inflammation (KYNU, ALOX12 and PLCB2 inhibition).The practically applied workflow's generated hypothesis aligns with known experimental data, validating the effectiveness of this novel computational workflow. It is a low‐risk and low‐cost DR computational tool providing a bird's‐eye view for exploring alternative clinical applications of pre‐approved drugs. [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]

We have shown that briefly inhaled isoflurane rapidly halts convulsions and protects the central nervous system (CNS) from organophosphate-induced neuronal loss when administered at 5% for 5 min, even as late as 1 h after organophosphate exposure. In the current study we investigated if an injectable form of isoflurane was as effective as inhaled isoflurane. We used a mixture of 10% isoflurane dissolved in an IV-compatible lipid-water emulsion for intravenous administration. Rats with an implanted jugular vein cannula were infused with 1,000 µL of the 10% isoflurane-lipid emulsion (ILE) mixture at a rate of 200 µL per minute, which achieved full anesthesia lasting approximately 10 min. When administered 30 min after a highly lethal dose of the organophosphate insecticide paraoxon (POX), the short-duration administration halted convulsions over the course of the study and prevented the great majority of neuronal loss as shown by Fluoro-Jade B staining (FJB). Our results indicate that injectable isoflurane is very effective for treating organophosphate poisoning, negating the need for vaporizer equipment and enabling intravenous therapy. [ABSTRACT FROM AUTHOR]