Int J Mol Sci. 2024 Jun 7;25(12):6314. doi: 10.3390/ijms25126314.

ABSTRACT

Drug repurposing, rebranding an existing drug for a new therapeutic indication, is deemed a beneficial approach for a quick and cost-effective drug discovery process by skipping preclinical, Phase 1 trials and pharmacokinetic studies. Several psychotropic drugs, including selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs), were studied for their potential application in different diseases, especially in cancer therapy. Fluoxetine (FLX) is one of the most prescribed psychotropic agents from the SSRIs class for the treatment of several neuropsychiatric disorders with a favorable safety profile. FLX exhibited different oncolytic effects via mechanisms distinct from its main serotonergic activity. Taking advantage of its ability to rapidly penetrate the blood-brain barrier, FLX could be particularly useful in brain tumors. This was proved by different in vitro and in vivo experiments using FLX as a monotherapy or combination with temozolomide (TMZ) or radiotherapy. In this review of the literature, we summarize the potential pleiotropic oncolytic roles of FLX against different cancers, highlighting the multifaceted activities of FLX and its ability to interrupt cancer proliferation via several molecular mechanisms and even surmount multidrug resistance (MDR). We elaborated on the successful synergistic combinations such as FXR/temozolomide and FXR/raloxifene for the treatment of glioblastoma and breast cancer, respectively. We showcased beneficial pharmaceutical trials to load FLX onto carriers to enhance its safety and efficacy on cancer cells. This is the first review article extensively summarizing all previous FLX repurposing studies for the management of cancer.

PMID:38928021 | DOI:10.3390/ijms25126314

Biomedicines. 2024 May 23;12(6):1156. doi: 10.3390/biomedicines12061156.

ABSTRACT

The role of the immune system in myocarditis onset and progression involves a range of complex cellular and molecular pathways. Both innate and adaptive immunity contribute to myocarditis pathogenesis, regardless of its infectious or non-infectious nature and across different histological and clinical subtypes. The heterogeneity of myocarditis etiologies and molecular effectors is one of the determinants of its clinical variability, manifesting as a spectrum of disease phenotype and progression. This spectrum ranges from a fulminant presentation with spontaneous recovery to a slowly progressing, refractory heart failure with ventricular dysfunction, to arrhythmic storm and sudden cardiac death. In this review, we first examine the updated definition and classification of myocarditis at clinical, biomolecular and histopathological levels. We then discuss recent insights on the role of specific immune cell populations in myocarditis pathogenesis, with particular emphasis on established or potential therapeutic applications. Besides the well-known immunosuppressive agents, whose efficacy has been already demonstrated in human clinical trials, we discuss the immunomodulatory effects of other drugs commonly used in clinical practice for myocarditis management. The immunological complexity of myocarditis, while presenting a challenge to simplistic understanding, also represents an opportunity for the development of different therapeutic approaches with promising results.

PMID:38927363 | DOI:10.3390/biomedicines12061156

Biology (Basel). 2024 May 30;13(6):397. doi: 10.3390/biology13060397.

ABSTRACT

Gynecological diseases are triggered by aberrant molecular pathways that alter gene expression, hormonal balance, and cellular signaling pathways, which may lead to long-term physiological consequences. This study was able to identify highly preserved modules and key hub genes that are mainly associated with gynecological diseases, represented by endometriosis (EM), ovarian cancer (OC), cervical cancer (CC), and endometrial cancer (EC), through the weighted gene co-expression network analysis (WGCNA) of microarray datasets sourced from the Gene Expression Omnibus (GEO) database. Five highly preserved modules were observed across the EM (GSE51981), OC (GSE63885), CC (GSE63514), and EC (GSE17025) datasets. The functional annotation and pathway enrichment analysis revealed that the highly preserved modules were heavily involved in several inflammatory pathways that are associated with transcription dysregulation, such as NF-kB signaling, JAK-STAT signaling, MAPK-ERK signaling, and mTOR signaling pathways. Furthermore, the results also include pathways that are relevant in gynecological disease prognosis through viral infections. Mutations in the ESR1 gene that encodes for ERα, which were shown to also affect signaling pathways involved in inflammation, further indicate its importance in gynecological disease prognosis. Potential drugs were screened through the Drug Repurposing Encyclopedia (DRE) based on the up-and downregulated hub genes, wherein a bacterial ribosomal subunit inhibitor and a benzodiazepine receptor agonist were the top candidates. Other drug candidates include a dihydrofolate reductase inhibitor, glucocorticoid receptor agonists, cholinergic receptor agonists, selective serotonin reuptake inhibitors, sterol demethylase inhibitors, a bacterial antifolate, and serotonin receptor antagonist drugs which have known anti-inflammatory effects, demonstrating that the gene network highlights specific inflammatory pathways as a therapeutic avenue in designing drug candidates for gynecological diseases.

PMID:38927277 | DOI:10.3390/biology13060397

Life Sci. 2024 Jun 24:122859. doi: 10.1016/j.lfs.2024.122859. Online ahead of print.

ABSTRACT

Lung cancer is among leading causes of death worldwide. The five-year survival rate of this disease is extremely low (17.8 %), mainly due to difficult early diagnosis and to the limited efficacy of currently available chemotherapeutics. This underlines the necessity to develop innovative therapies for lung cancer. In this context, drug repurposing represents a viable approach, as it reduces the turnaround time of drug development removing costs associated to safety testing of new molecular entities. Ribavirin, an antiviral molecule used to treat hepatitis C virus infections, is particularly promising as repurposed drug for cancer treatment, having shown therapeutic activity against glioblastoma, acute myeloid leukemia, and nasopharyngeal carcinoma. In the present study, we thoroughly investigated the in vitro anticancer activity of ribavirin against A549 human lung adenocarcinoma cells. From a functional standpoint, ribavirin significantly inhibits cancer hallmarks such as cell proliferation, migration, and colony formation. Mechanistically, ribavirin downregulates the expression of numerous proteins and genes regulating cell migration, proliferation, apoptosis, and cancer angiogenesis. The anticancer potential of ribavirin was further investigated in silico through gene ontology pathway enrichment and protein-protein interaction networks, identifying five putative molecular interactors of ribavirin (Erb-B2 Receptor Tyrosine Kinase 4 (Erb-B4); KRAS; Intercellular Adhesion Molecule 1 (ICAM-1); amphiregulin (AREG); and neuregulin-1 (NRG1)). These interactions were characterized via molecular docking and molecular dynamic simulations. The results of this study highlight the potential of ribavirin as a repurposed chemotherapy against lung cancer, warranting further studies to ascertain the in vivo anticancer activity of this molecule.

PMID:38925223 | DOI:10.1016/j.lfs.2024.122859

Clin Transl Med. 2024 Jul;14(7):e1745. doi: 10.1002/ctm2.1745.

NO ABSTRACT

PMID:38924682 | DOI:10.1002/ctm2.1745

Sci Transl Med. 2024 Jun 26;16(753):eadl0998. doi: 10.1126/scitranslmed.adl0998. Epub 2024 Jun 26.

ABSTRACT

Drug repurposing can be cheaper and faster than developing new compounds. Yet, it remains underused, partially because of regulatory and intellectual property challenges. Policy-makers in the United States and Europe have created seven drug development programs that aim to overcome these challenges using a variety of different strategies.

PMID:38924430 | DOI:10.1126/scitranslmed.adl0998

Pharmacol Res Perspect. 2024 Aug;12(4):e1225. doi: 10.1002/prp2.1225.

ABSTRACT

Drug repurposing has gained significant interest in recent years due to the high costs associated with de novo drug development; however, comprehensive pharmacological information is needed for the translation of pre-existing drugs across clinical applications. In the present study, we explore the current pharmacological understanding of the orphan drug, hemin, and identify remaining knowledge gaps with regard to hemin repurposing for the treatment of cardiovascular disease. Originally approved by the United States Food and Drug Administration in 1983 for the treatment of porphyria, hemin has attracted significant interest for therapeutic repurposing across a variety of pathophysiological conditions. Yet, the clinical translation of hemin remains limited to porphyria. Understanding hemin's pharmacological profile in health and disease strengthens our ability to treat patients effectively, identify therapeutic opportunities or limitations, and predict and prevent adverse side effects. However, requirements for the pre-clinical and clinical characterization of biologics approved under the U.S. FDA's Orphan Drug Act in 1983 (such as hemin) differed significantly from current standards, presenting fundamental gaps in our collective understanding of hemin pharmacology as well as knowledge barriers to clinical translation for future applications. Using information extracted from the primary and regulatory literature (including documents submitted to Health Canada in support of hemin's approval for the Canadian market in 2018), we present a comprehensive case study of current knowledge related to hemin's biopharmaceutical properties, pre-clinical/clinical pharmacokinetics, pharmacodynamics, dosing, and safety, focusing specifically on the drug's effects on heme regulation and in the context of acute myocardial infarction.

PMID:38923404 | DOI:10.1002/prp2.1225

Daru. 2024 Jun 26. doi: 10.1007/s40199-024-00523-0. Online ahead of print.

ABSTRACT

BACKGROUND: The focus on repurposing readily available, well-known drugs for new, creative uses has grown recently. One such medication is metformin, a drug commonly used to manage diabetes, which shows a favorable correlation between its use and lower cancer morbidity and death. Numerous investigations and clinical trials have been conducted to evaluate the possible application of metformin as an anticancer medication in light of this conclusion.

OBJECTIVE: This study used 'pathway/gene-set analysis' Gene2drug, a resource for Gene Ontology (GO), and DepMap to determine whether metformin would be potentially advantageous for treating cancer.

METHODS: A total of 1826 tumor cell lines were analyzed using the Drug Sensitivity (Primary Purposing Primary Screening) 19Q4 Tool.

RESULTS: 9 genes from 402 genes, SGPL1, CXCR6, ATXN2L, LAMP3, RTN3, BTN2A1, FOXM1, NQO1, and L1TD1 in 1826 cancer cell line showed statistical sensitivity to metformin.

CONCLUSION: This in-silico study showed the sensitivity of specific cancer cell lines to metformin. Therefore, holding promises for metformin and tumor-targeted treatment strategies. It is recommended, however, to conduct further research into its potential effectiveness and mechanism of action.

PMID:38922530 | DOI:10.1007/s40199-024-00523-0

Mar Drugs. 2024 Jun 12;22(6):272. doi: 10.3390/md22060272.

ABSTRACT

The marine environment provides a rich source of distinct creatures containing potentially revolutionary bioactive chemicals. One of these organisms is Caulerpa racemosa, a type of green algae known as green seaweed, seagrapes, or green caviar. This organism stands out because it has great promise for use in medicine, especially in the study of cancer. Through the utilization of computational modeling (in silico) and cellular laboratory experiments (in vitro), the chemical components included in the green seaweed C. racemosa were effectively analyzed, uncovering its capability to treat non-small cell lung cancer (NSCLC). The study specifically emphasized blocking SRC, STAT3, PIK3CA, MAPK1, EGFR, and JAK1 using molecular docking and in vitro. These proteins play a crucial role in the EGFR Tyrosine Kinase Inhibitor Resistance pathway in NSCLC. The chemical Caulersin (C2) included in C. racemosa extract (CRE) has been identified as a potent and effective agent in fighting against non-small cell lung cancer (NSCLC), both in silico and in vitro. CRE and C2 showed a level of inhibition similar to that of osimertinib (positive control/NSCLC drug).

PMID:38921583 | DOI:10.3390/md22060272

J Fungi (Basel). 2024 Jun 6;10(6):408. doi: 10.3390/jof10060408.

ABSTRACT

Candida auris is an emerging Candida sp. that has rapidly spread all over the world. The evidence regarding its origin and emerging resistance is still unclear. The severe infection caused by this species results in significant mortality and morbidity among the elderly and immunocompromised individuals. The development of drug resistance is the major factor associated with the therapeutic failure of existing antifungal agents. Previous studies have addressed the antifungal resistance profile and drug discovery for C. auris. However, complete coverage of this information in a single investigation is not yet available. In this review, we have mainly focused on recent developments in therapeutic strategies against C. auris. Based on the available information, several different approaches were discussed, including existing antifungal drugs, chemical compounds, essential oils, natural products, antifungal peptides, immunotherapy, antimicrobial photodynamic therapy, drug repurposing, and drug delivery systems. Among them, synthetic chemicals, natural products, and antifungal peptides are the prime contributors. However, a limited number of resources are available to prove the efficiency of these potential therapies in clinical usage. Therefore, we anticipate that the findings gathered in this review will encourage further in vivo studies and clinical trials.

PMID:38921394 | DOI:10.3390/jof10060408

Vasc Health Risk Manag. 2024 Jun 21;20:255-288. doi: 10.2147/VHRM.S391808. eCollection 2024.

ABSTRACT

Metformin is an orally effective anti-hyperglycemic drug that despite being introduced over 60 years ago is still utilized by an estimated 120 to 150 million people worldwide for the treatment of type 2 diabetes (T2D). Metformin is used off-label for the treatment of polycystic ovary syndrome (PCOS) and for pre-diabetes and weight loss. Metformin is a safe, inexpensive drug with side effects mostly limited to gastrointestinal issues. Prospective clinical data from the United Kingdom Prospective Diabetes Study (UKPDS), completed in 1998, demonstrated that metformin not only has excellent therapeutic efficacy as an anti-diabetes drug but also that good glycemic control reduced the risk of micro- and macro-vascular complications, especially in obese patients and thereby reduced the risk of diabetes-associated cardiovascular disease (CVD). Based on a long history of clinical use and an excellent safety record metformin has been investigated to be repurposed for numerous other diseases including as an anti-aging agent, Alzheimer's disease and other dementias, cancer, COVID-19 and also atrial fibrillation (AF). AF is the most frequently diagnosed cardiac arrythmia and its prevalence is increasing globally as the population ages. The argument for repurposing metformin for AF is based on a combination of retrospective clinical data and in vivo and in vitro pre-clinical laboratory studies. In this review, we critically evaluate the evidence that metformin has cardioprotective actions and assess whether the clinical and pre-clinical evidence support the use of metformin to reduce the risk and treat AF.

PMID:38919471 | PMC:PMC11198029 | DOI:10.2147/VHRM.S391808

Front Pharmacol. 2024 Jun 11;15:1400029. doi: 10.3389/fphar.2024.1400029. eCollection 2024.

ABSTRACT

Introduction: Cancer refers to a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. Due to its complexity, it has been hard to find an ideal medicine to treat all cancer types, although there is an urgent need for it. However, the cost of developing a new drug is high and time-consuming. In this sense, drug repurposing (DR) can hasten drug discovery by giving existing drugs new disease indications. Many computational methods have been applied to achieve DR, but just a few have succeeded. Therefore, this review aims to show in silico DR approaches and the gap between these strategies and their ultimate application in oncology. Methods: The scoping review was conducted according to the Arksey and O'Malley framework and the Joanna Briggs Institute recommendations. Relevant studies were identified through electronic searching of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We included peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between 1 January 2003, and 31 December 2021. Results: We identified 238 studies for inclusion in the review. Most studies revealed that the United States, India, China, South Korea, and Italy are top publishers. Regarding cancer types, breast cancer, lymphomas and leukemias, lung, colorectal, and prostate cancer are the top investigated. Additionally, most studies solely used computational methods, and just a few assessed more complex scientific models. Lastly, molecular modeling, which includes molecular docking and molecular dynamics simulations, was the most frequently used method, followed by signature-, Machine Learning-, and network-based strategies. Discussion: DR is a trending opportunity but still demands extensive testing to ensure its safety and efficacy for the new indications. Finally, implementing DR can be challenging due to various factors, including lack of quality data, patient populations, cost, intellectual property issues, market considerations, and regulatory requirements. Despite all the hurdles, DR remains an exciting strategy for identifying new treatments for numerous diseases, including cancer types, and giving patients faster access to new medications.

PMID:38919258 | PMC:PMC11196849 | DOI:10.3389/fphar.2024.1400029

Nat Commun. 2024 Jun 25;15(1):5378. doi: 10.1038/s41467-024-49620-3.

ABSTRACT

Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations like lack of well-defined targets. While chemical-induced transcriptional profiles offer a comprehensive view of drug mechanisms, inherent noise often obscures the true signal, hindering their potential for meaningful insights. Here, we highlight the development of TranSiGen, a deep generative model employing self-supervised representation learning. TranSiGen analyzes basal cell gene expression and molecular structures to reconstruct chemical-induced transcriptional profiles with high accuracy. By capturing both cellular and compound information, TranSiGen-derived representations demonstrate efficacy in diverse downstream tasks like ligand-based virtual screening, drug response prediction, and phenotype-based drug repurposing. Notably, in vitro validation of TranSiGen's application in pancreatic cancer drug discovery highlights its potential for identifying effective compounds. We envisage that integrating TranSiGen into the drug discovery and mechanism research holds significant promise for advancing biomedicine.

PMID:38918369 | DOI:10.1038/s41467-024-49620-3

Med Oncol. 2024 Jun 25;41(8):188. doi: 10.1007/s12032-024-02427-0.

ABSTRACT

FOXM1, a proto-oncogenic transcription factor, plays a critical role in cancer development and treatment resistance in cancers, particularly in breast cancer. Thus, this study aimed to identify potential FOXM1 inhibitors through computational screening of drug databases, followed by in vitro validation of their inhibitory activity against breast cancer cells. In silico studies involved pharmacophore modeling using the FOXM1 inhibitor, FDI-6, followed by virtual screening of DrugBank and Selleckchem databases. The selected drugs were prepared for molecular docking, and the crystal structure of FOXM1 was pre-processed for docking simulations. In vitro studies included MTT assays to assess cytotoxicity, and Western blot analysis to evaluate protein expression levels. Our study identified Pantoprazole and Rabeprazole as potential FOXM1 inhibitors through in silico screening and molecular docking. Molecular dynamics simulations confirmed stable interactions of these drugs with FOXM1. In vitro experiments showed both Pantoprazole and Rabeprazole exhibited strong FOXM1 inhibition at effective concentrations and that showed inhibition of cell proliferation. Rabeprazole showed the inhibitor activity at 10 µM in BT-20 and MCF-7 cell lines. Pantoprazole exhibited FOXM1 inhibition at 30 µM and in BT-20 cells and at 70 µM in MCF-7 cells, respectively. Our current study provides the first evidence that Rabeprazole and Pantoprazole can bind to FOXM1 and inhibit its activity and downstream signaling, including eEF2K and pEF2, in breast cancer cells. These findings indicate that rabeprazole and pantoprazole inhibit FOXM1 and breast cancer cell proliferation, and they can be used for FOXM1-targeted therapy in breast or other cancers driven by FOXM1.

PMID:38918225 | DOI:10.1007/s12032-024-02427-0

Cell. 2024 Jun 17:S0092-8674(24)00583-X. doi: 10.1016/j.cell.2024.05.039. Online ahead of print.

ABSTRACT

Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomics data from 1,043 patients across 10 cancer types with additional public datasets to identify potential therapeutic targets. Pan-cancer analysis of 2,863 druggable proteins reveals a wide abundance range and identifies biological factors that affect mRNA-protein correlation. Integration of proteomic data from tumors and genetic screen data from cell lines identifies protein overexpression- or hyperactivation-driven druggable dependencies, enabling accurate predictions of effective drug targets. Proteogenomic identification of synthetic lethality provides a strategy to target tumor suppressor gene loss. Combining proteogenomic analysis and MHC binding prediction prioritizes mutant KRAS peptides as promising public neoantigens. Computational identification of shared tumor-associated antigens followed by experimental confirmation nominates peptides as immunotherapy targets. These analyses, summarized at https://targets.linkedomics.org, form a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development.

PMID:38917788 | DOI:10.1016/j.cell.2024.05.039

Front Med (Lausanne). 2024 Jun 10;11:1407912. doi: 10.3389/fmed.2024.1407912. eCollection 2024.

ABSTRACT

Drug repurposing is considered a valid approach to accelerate therapeutic solutions for rare diseases. However, it is not as widely applied as it could be, due to several barriers that discourage both industry and academic institutions from pursuing this path. Herein we present the case of an academic multicentre study that considered the repurposing of the old drug guanabenz as a therapeutic strategy in amyotrophic lateral sclerosis. The difficulties encountered are discussed as an example of the barriers that academics involved in this type of study may face. Although further development of the drug for this target population was hampered for several reasons, the study was successful in many ways. Firstly, because the hypothesis tested was confirmed in a sub-population, leading to alternative innovative solutions that are now under clinical investigation. In addition, the study was informative and provided new insights into the disease, which are now giving new impetus to laboratory research. The message from this example is that even a repurposing study with an old product has the potential to generate innovation and interest from industry partners, provided it is based on a sound rationale, the study design is adequate to ensure meaningful results, and the investigators keep the full clinical development picture in mind.

PMID:38915767 | PMC:PMC11194437 | DOI:10.3389/fmed.2024.1407912

BMC Musculoskelet Disord. 2024 Jun 24;25(1):490. doi: 10.1186/s12891-024-07589-6.

ABSTRACT

BACKGROUND: Ankylosing spondylitis (AS) with radiographic damage is more prevalent in men than in women. IL-17, which is mainly secreted from peripheral blood mononuclear cells (PBMCs), plays an important role in the development of AS. Its expression is different between male and female. However, it is still unclear whether sex dimorphism of IL-17 contribute to sex differences in AS.

METHODS: GSE221786, GSE73754, GSE25101, GSE181364 and GSE205812 datasets were collected from the Gene Expression Omnibus (GEO) database. Differential expressed genes (DEGs) were analyzed with the Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods. CIBERSORTx and EcoTyper algorithms were used for immune infiltration analyses. Machine learning based on the XGBoost algorithm model was used to identify the impact of DEGs. The Connectivity Map (CMAP) database was used as a drug discovery tool for exploring potential drugs based on the DEGs.

RESULTS: According to immune infiltration analyses, T cells accounted for the largest proportion of IL-17-secreting PBMCs, and KEGG analyses suggested an enhanced activation of mast cells among male AS patients, whereas the expression of TNF was higher in female AS patients. Other signaling pathways, including those involving metastasis-associated 1 family member 3 (MAT3) or proteasome, were found to be more activated in male AS patients. Regarding metabolic patterns, oxidative phosphorylation pathways and lipid oxidation were significantly upregulated in male AS patients. In XGBoost algorithm model, DEGs including METRN and TMC4 played important roles in the disease process. we integrated the CMAP database for systematic analyses of polypharmacology and drug repurposing, which indicated that atorvastatin, famciclocir, ATN-161 and taselisib may be applicable to the treatment of AS.

CONCLUSIONS: We analyzed the sex dimorphism of IL-17-secreting PBMCs in AS. The results showed that mast cell activation was stronger in males, while the expression of TNF was higher in females. In addition, through machine learning and the CMAP database, we found that genes such as METRN and TMC4 may promote the development of AS, and drugs such as atorvastatin potentially could be used for AS treatment.

PMID:38914997 | DOI:10.1186/s12891-024-07589-6

Expert Rev Anticancer Ther. 2024 Jun 24. doi: 10.1080/14737140.2024.2372336. Online ahead of print.

ABSTRACT

INTRODUCTION: . The pharmacological treatment of cancer has evolved from cytotoxic to molecular targeted therapy. The median survival gains of 124 drugs approved by the FDA from 2003 to 2021 is 2.8 months. Targeted therapy is based on the somatic mutation theory, which has some paradoxes and limitations. While efforts of targeted therapy must continue, we must study newer approaches that could advance therapy and affordability for patients.

AREAS COVERED: This work briefly overviews how cancer therapy has evolved from cytotoxic chemotherapy to current molecular-targeted therapy. The limitations of the one-target, one-drug approach considering cancer as a robust system and the basis for multitargeting approach with polypharmacotherapy using repurposing drugs.

EXPERT OPINION: Multitargeted polypharmacotherapy for cancer with repurposed drugs should be systematically investigated in preclinical and clinical studies. Remarkably, most of these proposed drugs already have a long history in the clinical setting, and their safety is known. In principle, the risk of their simultaneous administration should not be greater than that of a first-in-human phase I study as long as the protocol is developed with strict vigilance to detect early possible side effects from their potential interactions. Research on cancer therapy should go beyond the prevailing paradigm targeted therapy.

PMID:38913911 | DOI:10.1080/14737140.2024.2372336

Bioinformatics. 2024 Jun 24:btae349. doi: 10.1093/bioinformatics/btae349. Online ahead of print.

ABSTRACT

MOTIVATION: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a systematic approach for drug repurposing to achieve cost savings and enhance human lives. In recent years, using biological network-based methods for drug repurposing has generated promising results. Nevertheless, these methods have limitations. Primarily, the scope of these methods is generally limited concerning the size and variety of data they can effectively handle. Another issue arises from the treatment of heterogeneous data, which needs to be addressed or converted into homogeneous data, leading to a loss of information. A significant drawback is that most of these approaches lack end-to-end functionality, necessitating manual implementation and expert knowledge in certain stages.

RESULTS: We propose a new solution, HGTDR (Heterogeneous Graph Transformer for Drug Repurposing), to address the challenges associated with drug repurposing. HGTDR is a three-step approach for knowledge graph-based drug repurposing: 1) constructing a heterogeneous knowledge graph, 2) utilizing a heterogeneous graph transformer network, and 3) computing relationship scores using a fully connected network. By leveraging HGTDR, users gain the ability to manipulate input graphs, extract information from diverse entities, and obtain their desired output. In the evaluation step, we demonstrate that HGTDR performs comparably to previous methods. Furthermore, we review medical studies to validate our method's top ten drug repurposing suggestions, which have exhibited promising results. We also demonstrated HGTDR's capability to predict other types of relations through numerical and experimental validation, such as drug-protein and disease-protein inter-relations.

AVAILABILITY: The source code and data are available at https://github.com/bcb-sut/HGTDR and http://git.dml.ir/BCB/HGTDR.

PMID:38913860 | DOI:10.1093/bioinformatics/btae349

J Mol Model. 2024 Jun 24;30(7):227. doi: 10.1007/s00894-024-05990-5.

ABSTRACT

CONTEXT: Breast cancer stem cells (BCSCs) are a small subset of cells within breast tumors with characteristics similar to normal stem cells. Despite advancements in chemotherapy and targeted therapy for breast cancer, the prognosis for breast cancer patients has remained poor due to drug resistance, reoccurrence, and metastasis. Growing evidence suggests that deregulation of the self-renewal pathways, like the Wnt signaling pathway mediated by β-catenin, plays a crucial role in the survival of breast cancer stem cells. Targeting the Wnt signaling pathway in breast cancer stem cells offers a promising avenue for developing effective therapeutic strategies targeting these cells, potentially leading to improved patient outcomes and reduced tumor recurrence.

METHODS: For this purpose, we have screened a 1615 FDA-approved drug library against our target protein, β-catenin, which is involved in the Wnt signaling pathway using molecular docking analysis, molecular dynamics (MD) simulations, and molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations.

RESULTS: Molecular docking studies showed that the Lumacaftor- β-catenin complex had the lowest docking score of - 8.7 kcal/mol towards β-catenin protein than the reference inhibitor. Molecular dynamic simulations and MM/PBSA calculations were also performed for the Lumacaftor-β-catenin complex to establish the stability of the interactions involved. Considering its promising attributes and encouraging results, Lumacaftor holds significant potential as a novel therapeutic option to target BCSCs. This study opens avenues for further investigation and may pave the way for developing therapeutic potential in breast cancer treatment. Further confirmation is warranted through in vitro and clinical studies to validate the findings of this study.

PMID:38913211 | DOI:10.1007/s00894-024-05990-5