J Pharm Pharmacol. 2025 Jan 20:rgaf002. doi: 10.1093/jpp/rgaf002. Online ahead of print.

ABSTRACT

OBJECTIVES: Chronic kidney disease (CKD) is a serious health issue with rising morbidity and mortality rates. Despite advances in understanding its pathophysiology, effective therapeutic options are limited, necessitating innovative treatment approaches. Also, current frontline treatments that are available against CKD are not uniformly effective and often come with significant side effects. Therefore, identifying new therapeutic targets or improving existing treatments for CKD is crucial. Drug repurposing is a promising strategy in the drug discovery process that involves screening existing approved drugs for new therapeutic applications.

KEY FINDINGS: This review discusses the pharmacological mechanisms and clinical evidence that support the efficacy of these repurposed drugs. Various drugs classes such as inodilators, endothelin-1 type A (ET-1A) receptor antagonists, bisphosphonates, mineralocorticoid receptor (MR) antagonists, DNA demethylating agents, nuclear factor erythroid 2-related factor 2 (NRF2) activators, P2X7 inhibitors, autophagy modulators, hypoxia-inducible factor-prolyl hydroxylase inhibitors (HIF-PHI) are discussed that could remarkably contribute against CKD.

SUMMARY: The review critically examines the potential for repurposing well-established drugs to slow the progression of CKD and enhance patient outcomes. This review emphasizes the importance of a multidisciplinary approach in advancing the field of drug repurposing, ultimately paving the way for innovative and effective therapies for patients suffering from CKD.

PMID:39832316 | DOI:10.1093/jpp/rgaf002

medRxiv [Preprint]. 2025 Jan 9:2025.01.08.25320199. doi: 10.1101/2025.01.08.25320199.

ABSTRACT

BACKGROUND: Analyzing disease-linked genetic variants via expression quantitative trait loci (eQTLs) is important for identifying potential disease-causing genes. Previous research prioritized genes by integrating Genome-Wide Association Study (GWAS) results with tissue- level eQTLs. Recent studies have explored brain cell type-specific eQTLs, but they lack a systematic analysis across various Alzheimer's disease (AD) GWAS datasets, nor did they compare effects between tissue and cell type levels or across different cell type-specific eQTL datasets. In this study, we integrated brain cell type-specific eQTL datasets with AD GWAS datasets to identify potential causal genes at the cell type level.

METHODS: To prioritize disease-causing genes, we used Summary Data-Based Mendelian Randomization (SMR) and Bayesian Colocalization (COLOC) to integrate AD GWAS summary statistics with cell-type-specific eQTLs. Combining data from five AD GWAS, three single-cell eQTL datasets, and one bulk tissue eQTL meta-analysis, we identified and confirmed both novel and known candidate causal genes. We investigated gene regulation through enhancer activity using H3K27ac and ATAC-seq data, performed protein-protein interaction and pathway enrichment analyses, and conducted a drug/compound enrichment analysis with the Drug Signatures Database (DSigDB) to support drug repurposing for AD.

RESULTS: We identified 27 candidate causal genes for AD using cell type-specific eQTL datasets, with the highest numbers in microglia, followed by excitatory neurons, astrocytes, inhibitory neurons, oligodendrocytes, and oligodendrocyte precursor cells (OPCs). PABPC1 emerged as a novel astrocyte-specific gene. Our analysis revealed protein-protein interaction (PPI) networks for these causal genes in microglia and astrocytes. We found the "regulation of aspartic-type peptidase activity" pathway being the most enriched among all the causal genes. AD-risk variants associated with candidate causal gene PABPC1 is located near or within enhancers only active in astrocytes. We classified the genes into three drug tiers and identified druggable interactions, with imatinib mesylate emerging as a key candidate. A drug-target gene network was created to explore potential drug targets for AD.

CONCLUSIONS: We systematically prioritized AD candidate causal genes based on cell type- specific molecular evidence. The integrative approach enhances our understanding of molecular mechanisms of AD-related genetic variants and facilitates the interpretation of AD GWAS results.

PMID:39830273 | PMC:PMC11741481 | DOI:10.1101/2025.01.08.25320199

Commun Biol. 2025 Jan 18;8(1):85. doi: 10.1038/s42003-025-07519-9.

ABSTRACT

Phosphodiesterase-5 (PDE5) inhibitors have shown promise as anti-cancer agents in malignancies. However, their specific effects on gastric cancer (GC) and the underlying mechanisms remain elusive. Our aim was to investigate this by combining evidence from population-based studies with data obtained from in vivo and in vitro experiments. By combing a couple of nationwide Swedish registers, GC patients who received PDE5 inhibitors were compared to matched controls while adjusting for confounding factors. The anti-tumor effect and mechanism of the PDE5 inhibitor sildenafil were evaluated via using tumor cells, patient-derived tumor organoids and xenograft animal models in GC. A total of 161 Swedish GC patients from a nationwide population-based cohort who received post-diagnostic PDE5 inhibitors demonstrated lower cancer-specific mortality compared to the controls (HR = 0.66, 95% CI = 0.47-0.92, P = 0.016). Functionally, the PDE5 inhibitor sildenafil exhibited the suppressive ability to prevent oncogenic growth in GC. Mechanistically, sildenafil restrained GC growth by directly activating PKG through PDE5 inhibition for regulating c-MYC expression via its phosphorylation and ubiquitination degradation, thereby suppressing c-MYC stability for IL-6 transcription within the downstream IL-6/JAK/STAT3 signalling pathway. The PDE5 inhibitor sildenafil may serve as a promising adjuvant for GC therapy if further randomized clinical trials confirm its efficacy.

PMID:39827331 | DOI:10.1038/s42003-025-07519-9

Cancer Lett. 2025 Jan 16:217437. doi: 10.1016/j.canlet.2025.217437. Online ahead of print.

NO ABSTRACT

PMID:39826666 | DOI:10.1016/j.canlet.2025.217437

Comput Methods Programs Biomed. 2025 Jan 13;261:108604. doi: 10.1016/j.cmpb.2025.108604. Online ahead of print.

ABSTRACT

BACKGROUND: Alzheimer's disease (AD), the most prevalent form of dementia, remains enigmatic in its origins despite the widely accepted "amyloid hypothesis," which implicates amyloid-beta peptide aggregates in its pathogenesis and progression. Despite advancements in technology and healthcare, the incidence of AD continues to rise. The traditional drug development process remains time-consuming, often taking years to bring an AD treatment to market. Drug repurposing has emerged as a promising strategy for developing cost-effective and efficient therapeutic options by identifying new uses for existing approved drugs, thus accelerating drug development.

OBJECTIVES: This study aimed to examine two key drug repurposing methodologies in general diseases and specifically in AD, which are artificial intelligent (AI) approach and molecular docking approach. In addition, the hybrid approach that integrates AI with molecular docking techniques will be explored too.

METHODOLOGY: This study systematically compiled a comprehensive collection of relevant academic articles, scientific papers, and research studies which were published up until November 2024 (as of the writing of this review paper). The final selection of papers was filtered to include studies related to Alzheimer's disease and general diseases, and then categorized into three groups: AI articles, molecular docking articles, and hybrid articles.

RESULTS: As a result, 331 papers were identified that employed AI for drug repurposing in general diseases, and 58 papers focused specifically in AD. For molecular docking in drug repurposing, 588 papers addressed general diseases, while 46 papers were dedicated to AD. The hybrid approach combining AI and molecular docking in drug repurposing has 52 papers for general diseases and 9 for AD. A comparative review was done across the methods, results, strengths, and limitations in those studies. Challenges of drug repurposing in AD are explored and future prospects are proposed.

DISCUSSION AND CONCLUSION: Drug repurposing emerges as a compelling and effective strategy within AD research. Both AI and molecular docking methods exhibit significant potential in this domain. AI algorithms yield more precise predictions, thus facilitating the exploration of new therapeutic avenues for existing drugs. Similarly, molecular docking techniques revolutionize drug-target interaction modelling, employing refined algorithms to screen extensive drug databases against specific target proteins. This review offers valuable insights for guiding the utilization of AI, molecular docking, or their hybrid in AD drug repurposing endeavors. The hope is to speed up the timeline of drug discovery which could improve the therapeutic approach to AD.

PMID:39826482 | DOI:10.1016/j.cmpb.2025.108604

J Med Virol. 2025 Jan;97(1):e70180. doi: 10.1002/jmv.70180.

ABSTRACT

An unprecedented global outbreak caused by the monkeypox virus (MPXV) prompted the World Health Organization to declare a public health emergency of international concern on July 23, 2022. Therapeutics and vaccines for MPXV are not widely available, necessitating further studies, particularly in drug repurposing area. To this end, the standardization of in vitro infection systems is essential. The most robust in vitro studies on poxviruses concern the Vaccinia virus, and there are significant gaps in understanding the replicative cycle of MPXV. Herein, we conducted ultrastructural studies using transmission and scanning electron microscopies and 3D reconstruction to describe and elucidate the step-by-step morphogenesis of MPXV. Vero cells, derived from the kidney lineage of Cercopithecus aethiops monkeys, were infected with a strain isolated from an oropharyngeal swab of a patient with suspected Mpox, collected during an observational cohort study conducted between June 12 and August 19, 2022, in Rio de Janeiro, Brazil. Infected Vero cells exhibited several morphological alterations, including cell lysis plaque formation, nuclei with altered chromatin profiles, thickening of the rough endoplasmic reticulum (RER), presence of myelin figures, disorganization of mitochondrial cristae, and the formation of a granular and fibrous matrix (viral factory) surrounded by mitochondria and RER cisternae in a perinuclear space. Viral entry into cells occurred via endocytosis MPXV particles were observed adhering to cytoskeletal filaments, and viral progeny extrusion occurred through exocytosis. This article presents novel data on the morphogenesis of MPXV that have not been previously documented in the literature.

PMID:39825732 | DOI:10.1002/jmv.70180

Mov Disord Clin Pract. 2025 Jan 18. doi: 10.1002/mdc3.14326. Online ahead of print.

ABSTRACT

BACKGROUND: The cerebral Renin-Angiotensin System might have a role in anxiety and depression development.

OBJECTIVE: We explored the effects of Angiotensin II Type 1 receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACE-Is) on anxiety and depression in Parkinson's Disease (PD).

METHODS: Four hundred and twenty-three newly diagnosed drug-naïve PD patients were evaluated using the State-Trait Anxiety Inventory (STAI) and Geriatric Depression Scale (GDS-15) tests and were monitored at baseline and for up to 3 years.

RESULTS: Twelve patients were treated with ARBs and 42 with ACE-Is. ARB-treated patients had lower anxiety STAI scores than those on ACE-Is or drug-free at baseline (17.2 ± 1.3 vs. 21.3 ± 1.3, or 23.8 ± 0.5, respectively, P = 0.021) and during the follow-up (P < 0.01). Depression scores were unaffected by any of the drugs throughout the study.

CONCLUSION: This small sample of ARB-treated PD patients displayed lower levels of anxiety. Randomized clinical trials are warranted.

PMID:39825674 | DOI:10.1002/mdc3.14326

NAR Cancer. 2025 Jan 15;7(1):zcae047. doi: 10.1093/narcan/zcae047. eCollection 2025 Mar.

ABSTRACT

Cancer is a complex disease with heterogeneous mutational and gene expression patterns. Subgroups of patients who share a phenotype might share a specific genetic architecture including protein-protein interactions (PPIs). We developed the Atlas of Protein-Protein Interactions in Cancer (APPIC), an interactive webtool that provides PPI subnetworks of 10 cancer types and their subtypes shared by cohorts of patients. To achieve this, we analyzed publicly available RNA sequencing data from patients and identified PPIs specific to 26 distinct cancer subtypes. APPIC compiles biological and clinical information from various databases, including the Human Protein Atlas, Hugo Gene Nomenclature Committee, g:Profiler, cBioPortal and Clue.io. The user-friendly interface allows for both 2D and 3D PPI network visualizations, enhancing the usability and interpretability of complex data. For advanced users seeking greater customization, APPIC conveniently provides all output files for further analysis and visualization on other platforms or tools. By offering comprehensive insights into PPIs and their role in cancer, APPIC aims to support the discovery of tumor subtype-specific novel targeted therapeutics and drug repurposing. APPIC is freely available at https://appic.brown.edu.

PMID:39822275 | PMC:PMC11734624 | DOI:10.1093/narcan/zcae047

Naunyn Schmiedebergs Arch Pharmacol. 2025 Jan 16. doi: 10.1007/s00210-024-03753-w. Online ahead of print.

ABSTRACT

The selective estrogen receptor modulator (SERM) raloxifene hydrochloride (RLH) is used extensively in the management and prevention of breast cancer and osteoporosis. Recent clinical studies show the repurposing of RLH in various diseases based on its structure and some clinical trials studies. Optimizing the clinical effectiveness of this important drug requires a thorough review of the formulation techniques, patent environment, and analytical procedures. The purpose of this study is to give a thorough understanding of dug repurposing with the most recent formulation strategies, patents, and analytical methods related to RLH. Highlighting recent developments, pointing out current issues, and suggesting future lines of inquiry and development are the objectives. A thorough literature analysis was carried out with an emphasis on repurposing of RLH for various diseases and analytical techniques employed in the measurement and quality control of RLH. These techniques included spectroscopic, chromatographic, and electrochemical approaches. Key advancements and trends were found by analyzing patent databases. The evaluation also looked into formulation techniques intended to improve the medicine's therapeutic efficacy and bioavailability, notably cutting-edge drug delivery methods. For the study of RLH, the review identifies several sophisticated analytical techniques that provide increased accuracy and robustness. Significant innovation has been revealed by the patent landscape, particularly in formulations targeted at enhancing solubility and bioavailability. Notable formulation techniques that overcome the drawbacks of conventional techniques include transdermal patches, nanoparticulate systems, and various drug delivery techniques.

PMID:39820645 | DOI:10.1007/s00210-024-03753-w

Curr Pharm Biotechnol. 2025 Jan 15. doi: 10.2174/0113892010335576241202061139. Online ahead of print.

ABSTRACT

BACKGROUND: Dilated Cardiomyopathy (DCM) is a debilitating cardiovascular disorder that challenges current therapeutic strategies. The exploration of novel drug repositioning opportunities through gene expression analysis offers a promising avenue for discovering effective treatments.

OBJECTIVE: This study aims to identify potential drug repositioning opportunities and lead compounds for DCM treatment by optimizing gene expression characteristics using published data.

METHODS: Our approach involved analyzing DCM expression profiles from the Gene Expression Omnibus database and identifying differentially expressed genes with GEO2R. A protein interaction network was constructed using the STRING database and visualized with Cytoscape. Enrichment analyses were conducted on these genes through the Omicshare platform, followed by the identification of candidate compounds via the Connectivity Map (CMAP) and validation through molecular docking. The Coremine Medical database was utilized to predict potential herbal medicines.

RESULTS: We identified 29 differentially expressed genes, highlighting MYH6, NPPA, and NPPB as central to DCM pathology. Enrichment analyses indicated significant impacts on biological processes, such as organ morphogenesis and inflammatory responses. The AGE-RAGE signaling pathway was notably affected. From over 6,100 compounds analyzed, tenoxicam emerged as a promising candidate, with Radix Salviae Miltiorrhizae (Danshen) being suggested as a potential herbal treatment.

CONCLUSION: This study underscores the utility of bioinformatics in uncovering new therapeutic candidates for DCM, offering a foundational step towards novel drug development.

PMID:39819398 | DOI:10.2174/0113892010335576241202061139

Front Parasitol. 2024 Dec 10;3:1508167. doi: 10.3389/fpara.2024.1508167. eCollection 2024.

ABSTRACT

Nematode parasitic infections continue to be a major health problem for humans and animals. Drug resistance to currently available treatments only worsen the problem. Drug discovery is expensive and time-consuming, making drug repurposing an enticing option. Emodepside, a broad-spectrum anthelmintic, has shown efficacy in the treatment of nematode parasitic infections in cats and dogs. It is now being considered and trialed for the treatment of onchocerciasis, trichuriasis (whipworm), and hookworm infections in humans. Its unique mechanism of action distinguishes it from traditional anthelmintics, positioning it as a promising candidate for combating resistance to other current drugs. Here, we provide a brief review of the available information on emodepside's pharmacokinetics, safety, and tolerability. We highlight the potential benefits and risks associated with its use, examining key toxicity effects. By exploring the literature, we aim to provide insights into the risks associated with emodepside that may impact its application in veterinary and human medicine. Although emodepside demonstrates a favorable safety profile, continued monitoring of its toxicity is crucial, particularly in vulnerable populations. This mini-review serves as a concise resource for researchers and clinicians interested in anthelmintic therapy.

PMID:39817180 | PMC:PMC11732007 | DOI:10.3389/fpara.2024.1508167

Narra J. 2024 Dec;4(3):e968. doi: 10.52225/narra.v4i3.968. Epub 2024 Oct 7.

ABSTRACT

The most common type of liver cancer is hepatocellular carcinoma (HCC), accounting for 75-85% of cases. Despite its associated side effects, sorafenib remains the standard treatment for HCC. Given the critical need to improve therapeutic efficacy while minimizing adverse effects, alternative drugs must be thoroughly investigated. Numerous studies indicate that combining sorafenib with metformin results in a more favorable treatment profile. The aim of this study was to employ bioinformatics methodologies to elucidate the molecular pathways and genetic underpinnings of metformin's efficacy in HCC treatment. Genes associated with metformin and its action against HCC (Huh-7 and HepG2 cells) were acquired from the NCBI-GEO data collection by utilizing pre-determined keywords. Subsequently, pathways implicated in metformin-mediated HCC treatment were analyzed through the Kyoto Encyclopedia of Genes and Genomes (KEGG). Our analysis revealed the involvement of multiple pathways, with metabolic pathways implicated in 80% of the total cases. Neurodegenerative pathways were involved in only around 60% of the total cases. These findings align with the multifaceted mechanisms of metformin's action, encompassing adenosine monophosphate-activated protein kinase activation, apoptosis induction, insulin regulation, anti-inflammatory responses, and modulation of cell proliferation. This comprehensive investigation sheds light on the intricate molecular landscape underpinning metformin's therapeutic efficacy in HCC, thereby informing potential avenues for optimizing treatment strategies.

PMID:39816125 | PMC:PMC11731935 | DOI:10.52225/narra.v4i3.968

Narra J. 2024 Dec;4(3):e938. doi: 10.52225/narra.v4i3.938. Epub 2024 Dec 12.

ABSTRACT

Cervical cancer is the fourth most common cancer among women globally, and studies have shown that genetic variants play a significant role in its development. A variety of germline and somatic mutations are associated with cervical cancer. However, genomic data derived from these mutations have not been extensively utilized for the development of repurposed drugs for cervical cancer. The objective of this study was to identify novel potential drugs that could be repurposed for cervical cancer treatment through a bioinformatics approach. A comprehensive genomic and bioinformatics database integration strategy was employed to identify potential drug target genes for cervical cancer. Using the GWAS and PheWAS databases, a total of 232 genes associated with cervical cancer were identified. These pharmacological target genes were further refined by applying a biological threshold of six functional annotations. The drug target genes were then cross-referenced with cancer treatment candidates using the DrugBank database. Among the identified genes, LTA, TNFRSF1A, PRKCZ, PDE4B, and PARP were highlighted as promising targets for repurposed drugs. Notably, these five target genes overlapped with 12 drugs that could potentially be repurposed for cervical cancer treatment. Among these, talazoparib, a potent PARP inhibitor, emerged as a particularly promising candidate. Interestingly, talazoparib is currently being investigated for safety and tolerability in other cancers but has not yet been studied in the context of cervical cancer. Further clinical trials are necessary to validate this finding and explore its potential as a repurposed drug for cervical cancer.

PMID:39816079 | PMC:PMC11731801 | DOI:10.52225/narra.v4i3.938

Discov Oncol. 2025 Jan 16;16(1):53. doi: 10.1007/s12672-025-01763-5.

ABSTRACT

OBJECTIVES: Leflunomide (LEF) is a conventional synthetic disease-modifying antirheumatic drug and suppresses T-cell proliferation and activity by inhibiting pyrimidine synthesis using dihydroorotase dehydrogenase (DHODH); however, several studies have demonstrated that LEF possesses anticancer and antiangiogenic effects in some malignant tumors. Therefore, we investigated the anticancer and antiangiogenic effects of LEF on oral squamous cell carcinoma (OSCC).

METHODS: To evaluate the inhibitory effect of LEF on OSCC, cell proliferation and wound-healing assays using human OSCC cell lines were performed. The DHODH inhibitory effect of LEF was evaluated by Western blot. To assess the suppression of pyrimidine biosynthesis induced by LEF on OSCC, cell proliferation assays with or without uridine supplementation were performed. The antiangiogenic effect of LEF was evaluated by in vitro tube formation assay using immortalized human umbilical vein endothelial cells, which were electroporatically transfected with hTERT. The tumor-suppressive effect of LEF in vivo was examined in both immunodeficient and syngeneic mice by implanting mouse OSCC cells. Tumor vascularization was evaluated by immunohistochemistry of the tumor extracted from syngeneic mice.

RESULTS: LEF dose-dependently inhibited OSCC proliferation and migration. LEF significantly inhibited DHODH expression, and uridine supplementation rescued the inhibitory effect of LEF. LEF dose-dependently suppressed endothelial tube formation. In the animal study, LEF significantly suppressed tumor growth in both immunodeficient and syngeneic mice. Histologically, LEF decreased DHODH expression and tumor vascularization.

CONCLUSION: LEF is a potent anticancer agent with antiangiogenic effects on OSCC and might be clinically applicable to OSCC by drug repositioning.

PMID:39815040 | DOI:10.1007/s12672-025-01763-5

Sci Rep. 2025 Jan 15;15(1):2093. doi: 10.1038/s41598-025-85947-7.

ABSTRACT

Alzheimer's Disease (AD) significantly aggravates human dignity and quality of life. While newly approved amyloid immunotherapy has been reported, effective AD drugs remain to be identified. Here, we propose a novel AI-driven drug-repurposing method, DeepDrug, to identify a lead combination of approved drugs to treat AD patients. DeepDrug advances drug-repurposing methodology in four aspects. Firstly, it incorporates expert knowledge to extend candidate targets to include long genes, immunological and aging pathways, and somatic mutation markers that are associated with AD. Secondly, it incorporates a signed directed heterogeneous biomedical graph encompassing a rich set of nodes and edges, and node/edge weighting to capture crucial pathways associated with AD. Thirdly, it encodes the weighted biomedical graph through a Graph Neural Network into a new embedding space to capture the granular relationships across different nodes. Fourthly, it systematically selects the high-order drug combinations via diminishing return-based thresholds. A five-drug lead combination, consisting of Tofacitinib, Niraparib, Baricitinib, Empagliflozin, and Doxercalciferol, has been selected from the top drug candidates based on DeepDrug scores to achieve the maximum synergistic effect. These five drugs target neuroinflammation, mitochondrial dysfunction, and glucose metabolism, which are all related to AD pathology. DeepDrug offers a novel AI-and-big-data, expert-guided mechanism for new drug combination discovery and drug-repurposing across AD and other neuro-degenerative diseases, with immediate clinical applications.

PMID:39814937 | DOI:10.1038/s41598-025-85947-7

J Chem Inf Model. 2025 Jan 15. doi: 10.1021/acs.jcim.4c02073. Online ahead of print.

ABSTRACT

Accurate prediction of drug-target interactions (DTIs) is pivotal for accelerating the processes of drug discovery and drug repurposing. MVCL-DTI, a novel model leveraging heterogeneous graphs for predicting DTIs, tackles the challenge of synthesizing information from varied biological subnetworks. It integrates neighbor view, meta-path view, and diffusion view to capture semantic features and employs an attention-based contrastive learning approach, along with a multiview attention-weighted fusion module, to effectively integrate and adaptively weight the information from the different views. Tested under various conditions on benchmark data sets, including varying positive-to-negative sample ratios, conducting hard negative sampling experiments, and masking known DTIs with different ratios, as well as redundant DTIs with various similarity metrics, MVCL-DTI exhibits strong robust generalization. The model is then employed to predict novel DTIs, with a particular focus on COVID-19-related drugs, highlighting its practical applicability. Ultimately, through features visualization and computational properties analysis, we've pinpointed critical elements, including Gene Ontology and substituent nodes, along with a proper initialization strategy, underscoring their vital role in DTI prediction tasks.

PMID:39812134 | DOI:10.1021/acs.jcim.4c02073

Curr Pharm Des. 2025 Jan 13. doi: 10.2174/0113816128346655241112104045. Online ahead of print.

ABSTRACT

AIMS: This study aims to identify and evaluate promising therapeutic proteins and compounds for breast cancer treatment through a comprehensive database search and molecular docking analysis.

BACKGROUND: Breast cancer (BC), primarily originating from the terminal ductal-lobular unit of the breast, is the most prevalent form of cancer globally. In 2020, an estimated 2.3 million new cases were reported, resulting in approximately 685,000 deaths. Mutations in the BRCA1 and BRCA2 genes are well-established in hereditary breast cancer. The identification of effective therapeutic proteins for BC remains a complex and evolving area of research.

OBJECTIVE: This study aims to identify and evaluate promising therapeutic proteins and compounds specific to breast cancer through a comprehensive database search and molecular docking analysis.

METHODS: A rigorous search was conducted within the National Cancer Institute (NCI), NCI Metathesaurus, SIGnaling Network Open Resource (SIGNOR), Human Protein Atlas (HPA), and the Human Phenotype Ontology (HPO) to shortlist proteins linked to BC (CUI C0678222). Recent studies were reviewed to understand the administration of CDK4/6 inhibitors (palbociclib, ribociclib, abemaciclib) combined with endocrine therapy for HR-positive and HER2-negative breast cancer. Anticancer compound libraries available at ZINC and PubChem were analyzed. Compounds were evaluated based on their binding energies with CDK4 protein, a rationally selected druggable target.

RESULTS: Key proteins linked to breast cancer were identified through database searches. Proliferation, apoptosis, and G1/S transition pathways were frequently found dysregulated in breast cancer. ZINC13152284 exhibited the strongest binding energy at -10.9 Kcal/mol, followed by ZINC05492794 with a binding energy of -10.4 Kcal/mol. Preexisting drugs showed lower binding energies with the CDK4 protein.

CONCLUSION: The study highlights the importance of drug repurposing as a strategy for the safe and effective treatment of breast cancer. Synthetic inhibitors often cause severe side effects, emphasizing the need for novel targets and compounds with better therapeutic profiles. Molecular docking identified promising compounds from the ZINC database, suggesting potential new avenues for breast cancer therapy.

PMID:39812054 | DOI:10.2174/0113816128346655241112104045

Curr Drug Discov Technol. 2024 Dec 31. doi: 10.2174/0115701638329824241220055621. Online ahead of print.

ABSTRACT

Repurposing of drugs through nanocarriers (NCs) based platforms has been a recent trend in drug delivery research. Various routine drugs are now being repurposed to treat challenging neurodegenerative disorders including Alzheimer disease (AD). AD, at present is one of the challenging neurodegenerative disorders characterized by extracellular accumulation of amyloid-β and intracellular accumulations of neurofibrillary tangles. In spite of catchy progress in drug development, effective treatment outcome in AD patients is far-fetched dream. Out of several proposed hypothesis in the development and progression of AD, potential role of microorganisms causing dementia and AD cannot be ruled out. Several recent researches have been documented a clear correlation in between microbial infection and neuronal damage leading to progression of AD. Thus, antimicrobial drugs repurposing has been emerged as alternate, potential, cost-effective strategy to check progression of AD. Further, for efficient delivery of antimicrobial drugs to brain tissue, novel NCs based platforms are the preferred option to bypass blood-brain barrier. Several polymeric and lipid NCs have been extensively studied over the past years to improve antimicrobial drug delivery to brain. The present review encompasses various repurposing strategy of antimicrobial drugs delivered through various NCs to target AD. Evidence-based research outcome compiled from authentic database like Scopus, PubMed, Web of science have been pooled to provide an updated review. Side by side some light has been thrown on the practical problems faced by nanodrug carriers during technology transfer.

PMID:39810446 | DOI:10.2174/0115701638329824241220055621

Cell Death Dis. 2025 Jan 14;16(1):15. doi: 10.1038/s41419-025-07337-1.

ABSTRACT

The orphan nuclear receptor NR2E3 has emerged as a potential tumor suppressor, yet its precise mechanisms in tumorigenesis require further investigation. Here, we demonstrate that the full-length protein isoform of NR2E3 instead of its short isoform activates wild-type p53 and is capable of rescuing certain p53 mutations in various cancer cell lines. Importantly, we observe a higher frequency of NR2E3 mutations in three solid tumors compared to the reference population, highlighting its potential significance in tumorigenesis. Specifically, we identify a cancer-associated NR2E3R97H mutation, which not only fails to activate p53 but also impedes NR2E3WT-mediated p53 acetylation. Moreover, we show that the small-molecule agonist of NR2E3, 11a, penetrates tumor mass of uterine cancer patients and increases p53 activation. Additionally, both NR2E3 and 11a exhibit similar multifaceted anti-cancer properties, underscoring NR2E3 as a novel molecular vulnerability in cancer cells. We further explore drug repurposing screens of FDA-approved anti-cancer drugs to develop NR2E3-targeted combinatorial treatments, such as the 11a-Romidepsin combination in HeLa cells. The underlying molecular mechanisms of these drug synergies include the activation of p53 pathway and inhibition of oncogenic pathway like MYC. Overall, our findings suggest that NR2E3 holds promise as a therapeutic target for cancer treatment, offering new avenues for effective anti-cancer strategies.

PMID:39809731 | DOI:10.1038/s41419-025-07337-1

Comput Biol Med. 2025 Jan 13;186:109665. doi: 10.1016/j.compbiomed.2025.109665. Online ahead of print.

ABSTRACT

BACKGROUND: Effective drugs for tendinopathy are lacking, resulting in significant morbidity and re-tearing rate after operation. Applying systems biology to identify new applications for current pharmaceuticals can decrease the duration, expenses, and likelihood of failure associated with the development of new drugs.

METHODS: We identify tendinopathy signature genes employing a transcriptomics database encompassing 154 clinical tendon samples. We then proposed a systems biology based drug prediction strategy that encompassed multiplex transcriptional drug prediction, systematic review assessment, deep learning based efficacy prediction and Mendelian randomization (MR). Finally, we evaluated the effects of drug target using gene knockout mice.

RESULTS: We demonstrate that sirolimus is a repurposable drug for tendinopathy, supported by: 1) Sirolimus achieves top ranking in drug-gene signature-based multiplex transcriptional drug efficacy prediction, 2) Consistent evidence from systematic review substantiates the efficacy of sirolimus in the management of tendinopathy, 3) Genetic prediction indicates that plasma proteins inhibited by mTOR (the target of sirolimus) are associated with increased tendinopathy risk. The effectiveness of sirolimus is further corroborated through in vivo testing utilizing tendon tissue-specific mTOR gene knockout mice. Integrative pathway enrichment analysis suggests that mTOR inhibition can regulate heterotopic ossification-related pathways to ameliorate clinical tendinopathy.

CONCLUSIONS: Our study assimilates knowledge of system-level responses to identify potential drugs for tendinopathy, and suggests sirolimus as a viable candidate. A systems biology approach could expedite the repurposing of drugs for human diseases that do not have well-defined targets.

PMID:39809087 | DOI:10.1016/j.compbiomed.2025.109665