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

Abstract Ulcerative colitis (UC), a chronic inflammatory bowel disease, significantly increases the risk of colon adenocarcinoma (COAD). Disulfidptosis, a novel form of programmed cell death, has been implicated in various diseases, including UC. This study investigates the expression of disulfidptosis-related genes, particularly CD2AP and MYH10, in UC and COAD. Through analysis of public datasets, we found MYH10 significantly upregulated and CD2AP downregulated in UC compared to healthy controls, with consistent patterns in COAD. Immune infiltration analysis revealed correlations between these genes and specific immune cell types, suggesting their roles in immune modulation. Molecular docking showed strong binding affinities of UC drugs such as budesonide and sulfasalazine with CD2AP and MYH10. Connectivity Map analysis identified additional drug candidates, including simvastatin and mephenytoin, which may be repurposed for UC and COAD therapy. These findings suggest disulfidptosis-related genes as potential biomarkers and therapeutic targets, linking chronic inflammation to cancer progression.

Abstract Drug development is known to be a costly and time-consuming process, which is prone to high failure rates. Drug repurposing allows drug discovery by reusing already approved compounds. The outcomes of past clinical trials can be used to predict novel drug-disease associations by leveraging drug- and disease-related similarities. To tackle this classification problem, collaborative filtering with implicit feedback (and potentially additional data on drugs and diseases) has become popular. It can handle large imbalances between negative and positive known associations and known and unknown associations. However, properly evaluating the improvement over the state of the art is challenging, as there is no consensus approach to compare models. We propose a reproducible methodology for comparing collaborative filtering-based drug repurposing. We illustrate this method by comparing 11 models from the literature on eight diverse drug repurposing datasets. Based on this benchmark, we derive guidelines to ensure a fair and comprehensive evaluation of the performance of those models. In particular, an uncontrolled bias on unknown associations might lead to severe data leakage and a misestimation of the model’s true performance. Moreover, in drug repurposing, the ability of a model to extrapolate beyond its training distribution is crucial and should also be assessed. Finally, we identified a subcategory of collaborative filtering that seems efficient and robust to distribution shifts. Benchmarks constitute an essential step towards increased reproducibility and more accessible development of competitive drug repurposing methods.

Objective: The prevalence of breast cancer and gynaecological cancers is high, and these cancer types can occur consecutively as secondary cancers. The aim of our study is to determine the genes commonly expressed in these cancers and to identify the common hub genes and drug components. Materials and Methods: Gene intensity values of breast cancer, gynaecological cancers such as cervical, ovarian and endometrial cancers were used from the Gene Expression Omnibus database Affymetrix Human Genome U133 Plus 2.0 Array project. Using the linear modelling method included in the R LIMMA package, genes that differ between healthy individuals and cancer patients were identified. Hub genes were determined using cytoHubba in Cytoscape program. “ShinyGo 0.80” tool was used to determine the disease-specific biological KEGG pathways. Drug.MATADOR from the ShinyGo 0.80 tool was used to predict drug-target relationships. Results: The RecQ Like Helicase 4 and Family with Sequence Similarity 13 Member C genes were found to be similarly expressed in breast cancer and gynaecological cancers. Upon KEGG pathway analyses with hub genes, Drug.MATADOR analysis with hub genes related to cancer related pathways was performed. We have determined these gene/drug interactions: NBN (targeted by Hydroxyurea), EP300 (targeted by Acetylcarnitine) and MAPK14 (targeted by Salicylate and Dibutyryl cyclic AMP). Conclusion: The drugs associated with hub genes determined in our study are not routinely used in cancer treatment. Our study offers the opportunity to identify the target genes of drugs used in breast and gynaecological cancers with the drug repurposing approach.

Abstract Background Glioblastoma (GBM) is a rare brain cancer with an exceptionally high mortality rate, which illustrates the pressing demand for more effective therapeutic options. Despite considerable research efforts on GBM, its underlying biological mechanisms remain unclear. Furthermore, none of the United States Food and Drug Administration (FDA) approved drugs used for GBM deliver satisfactory survival improvement. Methods This study presents a novel computational pipeline by utilizing gene expression data analysis for GBM for drug repurposing to address the challenges in rare disease drug development, particularly focusing on GBM. The GBM Gene Expression Profile (GGEP) was constructed with multi-omics data to identify drugs with reversal gene expression to GGEP from the Integrated Network-Based Cellular Signatures (iLINCS) database. Results We prioritized the candidates via hierarchical clustering of their expression signatures and quantification of their reversal strength by calculating two self-defined indices based on the GGEP genes’ log2 foldchange (LFC) that the drug candidates could induce. Among five prioritized candidates, in-vitro experiments validated Clofarabine and Ciclopirox as highly efficacious in selectively targeting GBM cancer cells. Conclusions The success of this study illustrated a promising avenue for accelerating drug development by uncovering underlying gene expression effect between drugs and diseases, which can be extended to other rare diseases and non-rare diseases.

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

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

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

Breast cancer has become one of the most prevalent cancers among women worldwide, posing a significant burden on their health. Current standard therapies are often expensive and associated with the risk of drug resistance. Drug repurposing has gained increasing attention as a cost-effective and time-saving strategy in pharmaceutical research. Many drugs already in clinical use or undergoing clinical trials can be repurposed for the treatment of new clinical indications. Based on a comprehensive understanding of the mechanisms of action of these drugs and the pathophysiological processes of breast cancer, researchers can better identify drugs with potential anti-breast cancer properties and translate them into clinical practice. This paper provides a review of the current research on repurposing existing drugs for breast cancer treatment, summarizes the mechanisms of action of these drugs, and discusses the challenges associated with the strategy of drug repurposing.

Abstract Monkeypox (Mpox) is a growing public health concern, with complex interactions within host systems contributing to its impact. This study employs multi-omics approaches to uncover therapeutic targets and potential drug repurposing opportunities to better understand Mpox’s molecular pathogenesis. We developed an in silico host-pathogen interaction (HPI) network and applied weighted gene co-expression network analysis (WGCNA) to explore interactions between Mpox and host proteins. Subtype-specific host-pathogen protein-protein interaction networks were constructed, and key modules from the HPI and WGCNA were integrated to identify significant host proteins. To predict upstream signaling pathways and transcription factors, we used eXpression2Kinases and ChIP-X Enrichment Analysis. The multi-Steiner trees method was applied to compare our findings with those from FDA-approved antiviral drugs. Analysis of 55 differentially expressed genes in Mpox infection revealed 11 kinases and 15 transcription factors as key regulators. We identified 16 potential drug targets, categorized into 8 proviral genes (ESR2, ERK1, ERK2, P38, JNK1, CDK4, GSK3B, STAT3) designated for inhibition, and 8 antiviral genes (IKKA, HDAC1, HIPK2, TF65, CSK21, HIPK2, ESR2, GSK3B) designated for activation. Proviral genes are involved in the AKT, Wnt, and STAT3 pathways, while antiviral genes impact the AP-1, NF-κB, apoptosis, and IFN pathways. Promising FDA-approved candidates were identified, including kinase inhibitors, steroid hormone receptor agonists, STAT3 inhibitors, and notably Niclosamide. This study enhances our understanding of Mpox by identifying key therapeutic targets and potential repurposable drugs, providing a valuable framework for developing new treatments.

Abstract Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This study suggested GBM-causing ten key genes (ASPM, CCNB2, CDK1, AURKA, TOP2A, CHEK1, CDCA8, SMC4, MCM10, and RAD51AP1) from nine transcriptomics datasets by combining supervised and unsupervised learning results. Differential expression patterns of key genes (KGs) between GBM and control samples were verified by different independent databases. Gene regulatory network (GRN) detected some important transcriptional and post-transcriptional regulators for KGs. The KGs-set enrichment analysis unveiled some crucial GBM-causing molecular functions, biological processes, cellular components, and pathways. The DNA methylation analysis detected some hypo-methylated CpG sites that might stimulate the GBM development. From the immune infiltration analysis, we found that almost all KGs are associated with different immune cell infiltration levels. Finally, we recommended KGs-guided four repurposable drug molecules (Fluoxetine, Vatalanib, TGX221 and RO3306) against GBM through molecular docking, drug likeness, ADMET analyses and molecular dynamics simulation studies. Thus, the discoveries of this study could serve as valuable resources for wet-lab experiments in order to take a proper treatment plan against GBM.

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

Abstract Background Current effective breast cancer treatment options have severe side effects, highlighting a need for new therapies. Drug repurposing can accelerate improvements to care, as FDA-approved drugs have known safety and pharmacological profiles. Some drugs for other conditions, such as metformin, an antidiabetic, have been tested in clinical trials for repurposing for breast cancer. Here, we exploit the genetics of breast cancer and linked predisposing diseases to propose novel drug repurposing opportunities. We hypothesize that if a predisposing disease contributes to breast cancer pathology, identifying the pleiotropic genes related to the risk of cancer could prioritize drugs, among all drugs treating a predisposing disease. We aim to develop a method to not only prioritize drugs for repurposing, but also to highlight shared etiology explaining repurposing. Methods We compile breast cancer’s predisposing diseases from literature. For each predisposing disease, we use GWAS summary statistics data to identify genes in loci showing genetic correlation with breast cancer. Then, we use a network approach to link these shared genes to canonical pathways. Similarly, for all drugs treating the predisposing disease, we link their targets to pathways. In this manner, we are able to prioritize a list of drugs based on each predisposing disease, with each drug linked to a set of implicating pathways. Finally, we evaluate our recommendations against drugs currently under investigation for breast cancer. Results We identify 84 loci harboring mutations with positively correlated effects between breast cancer and its predisposing diseases; these contain 194 identified shared genes. Out of the 112 drugs indicated for the predisposing diseases, 74 drugs can be linked to shared genes via pathways (candidate drugs for repurposing). Fifteen out of these candidate drugs are already in advanced clinical trial phases or approved for breast cancer (OR = 9.28, p = 7.99e-03, one-sided Fisher’s exact test), highlighting the ability of our approach to identify likely successful candidate drugs for repurposing. Conclusions Our novel approach accelerates drug repurposing for breast cancer by leveraging shared genetics with its known predisposing diseases. The result provides 59 novel candidate drugs alongside biological insights supporting each recommendation.

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

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

Abstract The bacterium Clostridium botulinum, well-known for producing botulinum neurotoxins, which cause the severe paralytic illness known as botulism, produces C2 toxin, a binary AB-toxin with ADP-ribosyltranferase activity. C2 toxin possesses two separate protein components, an enzymatically active A-component C2I and the binding and translocation B-component C2II. After proteolytic activation of C2II to C2IIa, the heptameric structure binds C2I and is taken up via receptor-mediated endocytosis into the target cells. Due to acidification of endosomes, the C2IIa/C2I complex undergoes conformational changes and consequently C2IIa forms a pore into the endosomal membrane and C2I can translocate into the cytoplasm, where it ADP-ribosylates G-actin, a key component of the cytoskeleton. This modification disrupts the actin cytoskeleton, resulting in the collapse of cytoskeleton and ultimately cell death. Here, we show that the serine-protease inhibitor α1-antitrypsin (α1AT) which we identified previously from a hemofiltrate library screen for PT from Bordetella pertussis is a multitoxin inhibitor. α1AT inhibits intoxication of cells with C2 toxin via inhibition of binding to cells and inhibition of enzyme activity of C2I. Moreover, diphtheria toxin and an anthrax fusion toxin are inhibited by α1AT. Since α1AT is commercially available as a drug for treatment of the α1AT deficiency, it could be repurposed for treatment of toxin-mediated diseases.

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

Summary: Background: Lupus nephritis (LN) is one of the most common and severe complications of systemic lupus erythematosus (SLE). Multitarget therapy (MT) achieves a 20% higher complete remission (CR) rate compared to conventional therapy in LN management. Intrigued by its excellent clinical efficacy, we aimed to develop a single-agent therapy with comparable efficacy to MT, offering a simplified treatment regimen. Methods: AZD1152, an Aurora kinase B (Aurkb) inhibitor, was identified through transcriptomic analyses and the L1000 CMap drug repurposing database. The therapeutic efficacy of AZD1152 was evaluated in MRL/lpr mice. Transcriptome sequencing and functional assays were performed to elucidate its mechanisms of action. Aurkb expression and its clinical relevance were assessed in lupus-prone mice and patients with LN. Findings: AZD1152 significantly attenuated systemic immune activation and renal injury in MRL/lpr mice, demonstrating efficacy comparable to MT regimens in animal studies. AZD1152 treatment modulated immune-inflammatory pathways in the kidney. Aurkb expression was upregulated in T cells infiltrating the renal interstitium in LN. Additionally, Aurkb expression levels positively correlated with the activity index (AI) and serum creatinine (Scr) in patients with LN. Mechanistic studies revealed that AZD1152 exerts therapeutic effects primarily by inhibiting T-cell proliferation. Interpretation: This study presents a drug development strategy that integrates clinically validated LN therapies with drug repurposing approaches. This strategy could accelerate drug development and clinical translation processes for LN. Funding: A full list of funding sources can be found in the acknowledgements section.

There are thousands of Mendelian diseases with more being discovered weekly and the majority have no approved treatments. To address this need, we require scalable approaches that are relatively inexpensive compared to traditional drug development. In the absence of a validated drug target, phenotypic screening in model organisms provides a route for identifying candidate treatments. Success requires a screenable phenotype. However, the right phenotype and assay may not be obvious for pleiotropic neuromuscular disorders. Here, we show that high-throughput imaging and quantitative phenotyping can be conducted systematically on a panel of C. elegans disease model strains. We used CRISPR genome-editing to create 25 worm models of human Mendelian diseases and phenotyped them using a single standardised assay. All but two strains were significantly different from wild-type controls in at least one feature. The observed phenotypes were diverse, but mutations of genes predicted to have related functions led to similar behavioural differences in worms. As a proof-of-concept, we performed a drug repurposing screen of an FDA-approved compound library, and identified two compounds that rescued the behavioural phenotype of a model of UNC80 deficiency. Our results show that a single assay to measure multiple phenotypes can be applied systematically to diverse Mendelian disease models. The relatively short time and low cost associated with creating and phenotyping multiple strains suggest that high-throughput worm tracking could provide a scalable approach to drug repurposing commensurate with the number of Mendelian diseases.

Summary: Background: Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. We aimed to define high-risk COPD subtypes using genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics. Methods: We defined high-risk groups based on PRS and TRS quantiles by maximising differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein–protein interaction networks and drug repurposing analyses between high-risk groups. Findings: We examined two high-risk omics-defined groups in non-overlapping test sets (n = 1133 NHW COPDGene, n = 299 African American (AA) COPDGene, n = 468 ECLIPSE). We defined “high activity” (low PRS, high TRS) and “severe risk” (high PRS, high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signalling processes compared to a low-risk (low PRS, low TRS) subgroup. “High activity” but not “severe risk” participants had greater prospective FEV1 decline (COPDGene: −51 mL/year; ECLIPSE: −40 mL/year) and proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors. Interpretation: Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection. Funding: National Institutes of Health.

Abstract Repurposing of FDA-approved drugs is a quick and cost-effective alternative to de novo drug development. Here, we identify genes involved in bortezomib sensitivity, predict cancer types that may benefit from treatment with bortezomib, and evaluate the mechanism-of-action of bortezomib in breast cancer (BT-474 and ZR-75–30), melanoma (A-375), and glioblastoma (A-172) cells in vitro. Cancer cell lines derived from cancers of the blood, kidney, nervous system, and skin were found to be significantly more sensitive to bortezomib than other organ systems. The in vitro studies confirmed that although bortezomib effectively inhibited the β5 catalytic site in all four cell lines, cell cycle arrest was only induced in G2/M phase and apoptosis in A-375 and A-172 after 24h. The genomic and transcriptomic analyses identified 33 genes (e.g. ALDH18A1, ATAD2) associated with bortezomib resistance. Taken together, we identified biomarkers predictive of bortezomib sensitivity and cancer types that might benefit from treatment with bortezomib.

Abstract Type 2 diabetes (T2D) and Clear-cell renal cell carcinoma (ccRCC) are both complicated diseases which incidence rates gradually increasing. Population based studies show that severity of ccRCC might be associated with T2D. However, so far, no researcher yet investigated about the molecular mechanisms of their association. This study explored T2D and ccRCC causing shared key genes (sKGs) from multiple transcriptomics profiles to investigate their common pathogenetic processes and associated drug molecules. We identified 259 shared differentially expressed genes (sDEGs) that can separate both T2D and ccRCC patients from control samples. Local correlation analysis based on the expressions of sDEGs indicated significant association between T2D and ccRCC. Then ten sDEGs (CDC42, SCARB1, GOT2, CXCL8, FN1, IL1B, JUN, TLR2, TLR4, and VIM) were selected as the sKGs through the protein–protein interaction (PPI) network analysis. These sKGs were found significantly associated with different CpG sites of DNA methylation that might be the cause of ccRCC. The sKGs-set enrichment analysis with Gene Ontology (GO) terms and KEGG pathways revealed some crucial shared molecular functions, biological process, cellular components and KEGG pathways that might be associated with development of both T2D and ccRCC. The regulatory network analysis of sKGs identified six post-transcriptional regulators (hsa-mir-93-5p, hsa-mir-203a-3p, hsa-mir-204-5p, hsa-mir-335-5p, hsa-mir-26b-5p, and hsa-mir-1-3p) and five transcriptional regulators (YY1, FOXL1, FOXC1, NR2F1 and GATA2) of sKGs. Finally, sKGs-guided top-ranked three repurposable drug molecules (Digoxin, Imatinib, and Dovitinib) were recommended as the common treatment for both T2D and ccRCC by molecular docking and ADME/T analysis. Therefore, the results of this study may be useful for diagnosis and therapies of ccRCC patients who are also suffering from T2D.

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

Abstract Due to considerable global prevalence and high recurrence rate, the pursuit of effective new medication for epilepsy treatment remains an urgent and significant challenge. Drug repurposing emerges as a cost-effective and efficient strategy to combat this disorder. This study leverages the transformer-based deep learning methods coupled with molecular binding affinity calculation to develop a novel in-silico drug repurposing pipeline for epilepsy. The number of candidate inhibitors against 24 target proteins encoded by gain-of-function genes implicated in epileptogenesis ranged from zero to several hundreds. Our pipeline has repurposed the medications with most anti-epileptic drugs and nearly half psychiatric medications, highlighting the effectiveness of our pipeline. Furthermore, Lomitapide, a cholesterol-lowering drug, first emerged as particularly noteworthy, exhibiting high binding affinity for 10 targets and verified by molecular dynamics simulation and mechanism analysis. These findings provided a novel perspective on therapeutic strategies for other central nervous system disease.

Abstract Drug repurposing aims to find new therapeutic applications for existing drugs in the pharmaceutical market, leading to significant savings in time and cost. The use of artificial intelligence and knowledge graphs to propose repurposing candidates facilitates the process, as large amounts of data can be processed. However, it is important to pay attention to the explainability needed to validate the predictions. We propose a general architecture to understand several explainable methods for graph completion based on knowledge graphs and design our own architecture for drug repurposing. We present XG4Repo (eXplainable Graphs for Repurposing), a framework that takes advantage of the connectivity of any biomedical knowledge graph to link compounds to the diseases they can treat. Our method allows methapaths of different types and lengths, which are automatically generated and optimised based on data. XG4Repo focuses on providing meaningful explanations to the predictions, which are based on paths from compounds to diseases. These paths include nodes such as genes, pathways, side effects, or anatomies, so they provide information about the targets and other characteristics of the biomedical mechanism that link compounds and diseases. Paths make predictions interpretable for experts who can validate them and use them in further research on drug repurposing. We also describe three use cases where we analyse new uses for Epirubicin, Paclitaxel, and Predinisone and present the paths that support the predictions.

Prostate and bladder cancer treatments have several challenges, including intense side effects and mechanisms of resistance. Thus, it is urgent to find drugs that can fill these gaps. For this purpose, Entecavir (ETV) was tested alone and in combination with 5-Fluorouracil (5-FU). Prior to this, a preliminary computational analysis was conducted to evaluate the combination of these two drugs. After exposing PC-3 and UM-UC-5 cells to the drugs, cell morphology was assessed using a microscope, while cell viability, proliferation, and cytotoxicity were evaluated using the MTT assay, and finally, the statistical analysis was performed. It was concluded that ETV showed significant cytotoxic effects in the PC-3 cells, and 5-FU, although not as effective as in other tumor types, it managed to inhibit the viability of the PC-3 cells. The combination of 5-FU with ETV after 72 h of exposure is an advantageous association, surpassing the results of each drug alone. In the UM-UC-5 cells, ETV alone did not produce the expected effect, neither did the combination. Nevertheless, repurposing ETV has proven to be an effective strategy in PC, especially through its combination with 5-FU.

Abstract There have been 774,075,242 cases of COVID-19 and 7,012,986 deaths worldwide as of January 2024. In the early stages of the pandemic, there was an urgent need to reduce the severity of the disease and prevent the need for hospitalization to avoid stress on healthcare systems worldwide. The repurposing of drugs to prevent clinical deterioration of COVID-19 patients was trialed in many studies using many different drugs. Fluvoxamine (an SSRI and sigma-1 receptor agonist) was initially identified to potentially provide beneficial effects in COVID-19-infected patients, preventing clinical deterioration and the need for hospitalization. Fourteen clinical studies have been carried out to date, with seven of those being randomized placebo-controlled studies. This systematic review and meta-analysis covers the literature from the outbreak of SARS-CoV-2 in late 2019 until January 2024. Search terms related to fluvoxamine, such as its trade names and chemical names, along with words related to COVID-19, such as SARS-CoV-2 and coronavirus, were used in literature databases including PubMed, Google Scholar, Scopus, and the ClinicalTrials.gov database from NIH, to identify the trials used in the subsequent analysis. Clinical deterioration and death data were extracted from these studies where available and used in the meta-analysis. A total of 7153 patients were studied across 14 studies (both open-label and double-blind placebo-controlled). 681 out of 3553 (19.17%) in the standard care group and 255 out of 3600 (7.08%) in the fluvoxamine-treated group experienced clinical deterioration. The estimated average log odds ratio was 1.087 (95% CI 0.200 to 1.973), which differed significantly from zero (z = 2.402, p = 0.016). The seven placebo-controlled studies resulted in a log odds ratio of 0.359 (95% CI 0.1111 to 0.5294), which differed significantly from zero (z = 3.103, p = 0.002). The results of this study identified fluvoxamine as effective in preventing clinical deterioration, and subgrouping analysis suggests that earlier treatment with a dose of 200 mg or above provides the best outcomes. We hope the outcomes of this study can help design future studies into respiratory viral infections and potentially improve clinical outcomes.

High-grade glioma (HGG) is an aggressive brain cancer with an overall 5-year survival rate of less than 10% in adults and less than 2% in children. Despite significant research efforts, surgery combined with chemo- and radiotherapy is the only treatment option available for these patients. New targeted therapies such as kinase inhibitors, and combined modalities fail in clinical trials due to the inability of drugs to cross the blood-brain barrier, and HGG pathway rewiring. In vitro studies suggest that ion channels contribute to HGG pathway rewiring and tumor survival. There are several United States Food and Drug Administration-approved neurological drugs that readily cross the blood-brain barrier and target ion channels. These drugs are readily available on the shelf and can be easily repurposed to treat HGG. A systematic understanding of the oncogenic roles of ion channels in patients with HGG will help us to repurpose ion channel drugs to treat HGG. The study of the oncogenic potential and therapeutic targeting of ion channels in HGG is still in the early stage. This review summarises the findings that elucidate the expression and oncogenic potential of ion channels in HGG patients. We have identified the research gaps to translate ion channels as therapeutic targets for HGG. Finally, we highlight the potential to use ion channel drugs as a single agent or as part of combination therapy for the treatment of patients with HGG.

Summary: Background: Global cyclical outbreaks of human enterovirus infections has positioned human enterovirus A71 (EV-A71) as a neurotropic virus of clinical importance. However, there remains a scarcity of internationally approved antivirals and vaccines. Methods: In pursuit of repurposing drugs for combating human enteroviruses, we employed a comprehensive pharmacophore- and molecular docking-based virtual screen targeting EV-A71 capsid protein VP1-4, 3C protease, and 3D polymerase proteins. Among 15 shortlisted ligand candidates, we dissected the inhibitory mechanism of Tanomastat in cell-based studies and evaluated its in vivo efficacy in an EV-A71-infected murine model. Findings: We demonstrated that Tanomastat exerts dose-dependent inhibition on EV-A71 replication, with comparable efficacy profiles in enterovirus species A, B, C, and D in vitro. Time-course studies suggested that Tanomastat predominantly disrupts early process(es) of the EV-A71 replication cycle. Mechanistically, live virus particle tracking and docking predictions revealed that Tanomastat specifically impedes viral capsid dissociation, potentially via VP1 hydrophobic pocket binding. Bypassing its inhibition on entry stages, we utilized EV-A71 replication-competent, 3Dpol replication-defective, and bicistronic IRES reporter replicons to show that Tanomastat also inhibits viral RNA replication, but not viral IRES translation. We further showed that orally administered Tanomastat achieved 85% protective therapeutic effect and alleviated clinical symptoms in EV-A71-infected neonatal mice. Interpretation: Our study establishes Tanomastat as a broad-spectrum anti-enterovirus candidate with promising pre-clinical efficacy, warranting further testing for potential therapeutic application. Funding: MOE Tier 2 grants (MOE-T2EP30221-0005, R571-000-068-592, R571-000-076-515, R571-000-074-733) and A∗STAR Biomedical Research Council (BMRC).

Drugs that induce reversible slowing of metabolic and physiological processes would have great value for organ preservation, especially for organs with high susceptibility to hypoxia-reperfusion injury, such as the heart. Using whole-organism screening of metabolism, mobility, and development in Xenopus, we identified an existing drug, SNC80, that rapidly and reversibly slows biochemical and metabolic activities while preserving cell and tissue viability. Although SNC80 was developed as a delta opioid receptor activator, we discovered that its ability to slow metabolism is independent of its opioid modulating activity as a novel SNC80 analog (WB3) with almost 1000 times less delta opioid receptor binding activity is equally active. Metabolic suppression was also achieved using SNC80 in microfluidic human organs-on-chips, as well as in explanted whole porcine hearts and limbs, demonstrating the cross-species relevance of this approach and potential clinical relevance for surgical transplantation. Pharmacological induction of physiological slowing in combination with organ perfusion transport systems may offer a new therapeutic approach for tissue and organ preservation for transplantation, trauma management, and enhancing patient survival in remote and low-resource locations.

Background The growing concern of antibiotic-resistant microbial strains worldwide has prompted the need for alternative methods to combat microbial resistance. Biofilm formation poses a significant challenge to antibiotic efficiency due to the difficulty of penetrating antibiotics through the sticky microbial aggregates. Drug repurposing is an innovative technique that aims to expand the use of non-antibiotic medications to address this issue. The primary objective of this study was to evaluate the antimicrobial properties of Diltiazem HCl, a 1,5-benzothiazepine Ca2+ channel blocker commonly used as an antihypertensive agent, against four pathogenic bacteria and three pathogenic yeasts, as well as its antiviral activity against the Coxsackie B4 virus (CoxB4). Methods To assess the antifungal and antibacterial activities of Diltiazem HCl, the well diffusion method was employed, while crystal violet staining was used to determine the anti-biofilm activity. The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) colorimetric assay was utilized to evaluate the antiviral activity of Diltiazem HCl against the CoxB4 virus. Results This study revealed that Diltiazem HCl exhibited noticeable antimicrobial properties against Gram-positive bacteria, demonstrating the highest inhibition of Staphylococcus epidermidis, followed by Staphylococcus aureus. It effectively reduced the formation of biofilms by 95.1% and 90.7% for S. epidermidis, and S. aureus, respectively. Additionally, the antiviral activity of Diltiazem HCl was found to be potent against the CoxB4 virus, with an IC50 of 35.8 ± 0.54 μg mL−1 compared to the reference antiviral Acyclovir (IC50 42.71 ± 0.43 μg mL−1). Conclusion This study suggests that Diltiazem HCl, in addition to its antihypertensive effect, may also be a potential treatment option for infections caused by Gram-positive bacteria and the CoxB4 viruses, providing an additional off-target effect for Diltiazem HCl.

Abstract Discovering effective anti-cancer agents poses a formidable challenge given the limited efficacy of current therapeutic modalities against various cancer types due to intrinsic resistance mechanisms. Cancer immunochemotherapy is an alternative strategy for breast cancer treatment and overcoming cancer resistance. Human Indoleamine 2,3-dioxygenase (hIDO1) and human Tryptophan 2,3-dioxygenase 2 (hTDO2) play pivotal roles in tryptophan metabolism, leading to the generation of kynurenine and other bioactive metabolites. This process facilitates the de novo synthesis of Nicotinamide Dinucleotide (NAD), promoting cancer resistance. This study identified a new dual hIDO1/hTDO2 inhibitor using a drug repurposing strategy of FDA-approved drugs. Herein, we delineate the development of a ligand-based pharmacophore model based on a training set of 12 compounds with reported hIDO1/hTDO2 inhibitory activity. We conducted a pharmacophore search followed by high-throughput virtual screening of 2568 FDA-approved drugs against both enzymes, resulting in ten hits, four of them with high potential of dual inhibitory activity. For further in silico and in vitro biological investigation, the anti-hypercholesterolemic drug Pitavastatin deemed the drug of choice in this study. Molecular dynamics (MD) simulations demonstrated that Pitavastatin forms stable complexes with both hIDO1 and hTDO2 receptors, providing a structural basis for its potential therapeutic efficacy. At nanomolar (nM) concentration, it exhibited remarkable in vitro enzyme inhibitory activity against both examined enzymes. Additionally, Pitavastatin demonstrated potent cytotoxic activity against BT-549, MCF-7, and HepG2 cell lines (IC50 = 16.82, 9.52, and 1.84 µM, respectively). Its anticancer activity was primarily due to the induction of G1/S phase arrest as discovered through cell cycle analysis of HepG2 cancer cells. Ultimately, treating HepG2 cancer cells with Pitavastatin affected significant activation of caspase-3 accompanied by down-regulation of cellular apoptotic biomarkers such as IDO, TDO, STAT3, P21, P27, IL-6, and AhR.

Abstract Background There is a lack of effective therapeutic strategies for amyotrophic lateral sclerosis (ALS); therefore, drug repurposing might provide a rapid approach to meet the urgent need for treatment. Methods To identify therapeutic targets associated with ALS, we conducted Mendelian randomization (MR) analysis and colocalization analysis using cis-eQTL of druggable gene and ALS GWAS data collections to determine annotated druggable gene targets that exhibited significant associations with ALS. By subsequent repurposing drug discovery coupled with inclusion criteria selection, we identified several drug candidates corresponding to their druggable gene targets that have been genetically validated. The pharmacological assays were then conducted to further assess the efficacy of genetics-supported repurposed drugs for potential ALS therapy in various cellular models. Results Through MR analysis, we identified potential ALS druggable genes in the blood, including TBK1 [OR 1.30, 95%CI (1.19, 1.42)], TNFSF12 [OR 1.36, 95%CI (1.19, 1.56)], GPX3 [OR 1.28, 95%CI (1.15, 1.43)], TNFSF13 [OR 0.45, 95%CI (0.32, 0.64)], and CD68 [OR 0.38, 95%CI (0.24, 0.58)]. Additionally, we identified potential ALS druggable genes in the brain, including RESP18 [OR 1.11, 95%CI (1.07, 1.16)], GPX3 [OR 0.57, 95%CI (0.48, 0.68)], GDF9 [OR 0.77, 95%CI (0.67, 0.88)], and PTPRN [OR 0.17, 95%CI (0.08, 0.34)]. Among them, TBK1, TNFSF12, RESP18, and GPX3 were confirmed in further colocalization analysis. We identified five drugs with repurposing opportunities targeting TBK1, TNFSF12, and GPX3, namely fostamatinib (R788), amlexanox (AMX), BIIB-023, RG-7212, and glutathione as potential repurposing drugs. R788 and AMX were prioritized due to their genetic supports, safety profiles, and cost-effectiveness evaluation. Further pharmacological analysis revealed that R788 and AMX mitigated neuroinflammation in ALS cell models characterized by overly active cGAS/STING signaling that was induced by MSA-2 or ALS-related toxic proteins (TDP-43 and SOD1), through the inhibition of TBK1 phosphorylation. Conclusions Our MR analyses provided genetic evidence supporting TBK1, TNFSF12, RESP18, and GPX3 as druggable genes for ALS treatment. Among the drug candidates targeting the above genes with repurposing opportunities, FDA-approved drug-R788 and AMX served as effective TBK1 inhibitors. The subsequent pharmacological studies validated the potential of R788 and AMX for treating specific ALS subtypes through the inhibition of TBK1 phosphorylation.

Abstract Effective drugs for the treatment of gastric cancer (GC) are still lacking. Nortriptyline Hydrochloride (NTP), a commonly used antidepressant medication, has been demonstrated by numerous studies to have antitumor effects. This study first validated the ability of NTP to inhibit GC and preliminarily explored its underlying mechanism. To begin with, NTP inhibits the activity of AGS and HGC27 cells (Human-derived GC cells) in a dose-dependent manner, as well as proliferation, cell cycle, and migration. Moreover, NTP induces cell apoptosis by upregulating BAX, BAD, and c-PARP and downregulating PARP and Bcl-2 expression. Furthermore, the mechanism of cell death caused by NTP is closely related to oxidative stress. NTP increases intracellular reactive oxygen species (ROS) and malondialdehyde (MDA) levels, decreasing the mitochondrial membrane potential (MMP) and inducing glucose (GSH) consumption. While the death of GC cells can be partially rescued by ROS inhibitor N-acetylcysteine (NAC). Mechanistically, NTP activates the Kelch-like ECH-associated protein (Keap1)—NF-E2-related factor 2 (Nrf2) pathway, which is an important pathway involved in oxidative stress. RNA sequencing and proteomics analysis further revealed molecular changes at the mRNA and protein levels and provided potential targets and pathways through differential gene expression analysis. In addition, NTP can inhibited tumor growth in nude mouse subcutaneous tumor models constructed respectively using AGS and MFC (mouse-derived GC cells), providing preliminary evidence of its effectiveness in vivo. In conclusion, our study demonstrated that NTP exhibits significant anti-GC activity and is anticipated to be a candidate for drug repurposing.

Abstract Background Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn’s disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn’s disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. Conclusions We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio’s potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

The development of antivirals for respiratory viruses has advanced markedly in response to the growing threat of pathogens such as Influenzavirus (IAV), respiratory syncytial virus (RSV), and SARS-CoV-2. This article reviews the advances and challenges in this field, highlighting therapeutic strategies that target critical stages of the viral replication cycle, including inhibitors of viral entry, replication, and assembly. In addition, innovative approaches such as inhibiting host cellular proteins to reduce viral resistance and repurposing existing drugs are explored, using advanced bioinformatics tools that optimize the identification of antiviral candidates. The analysis also covers emerging technologies such as nanomedicine and CRISPR gene editing, which promise to improve the stability and efficacy of treatments. While current antivirals offer valuable options, they face challenges such as viral evolution and the need for accessible treatments for vulnerable populations. This article underscores the importance of continued innovation in biotechnology to overcome these limitations and provide safe and effective treatments. Combining traditional and advanced approaches in developing antivirals is essential in order to address respiratory viral diseases that affect global health.

Background: Chemoresistance is a major obstacle in high-grade serous carcinoma (HGSC) treatment. Although many patients initially respond to chemotherapy, the majority of them relapse due to Carboplatin and Paclitaxel resistance. Drug repurposing has surfaced as a potentially effective strategy that works synergically with standard chemotherapy to bypass chemoresistance. In a prior study, using 2D cultures and two HGSC chemoresistant cell lines, it was demonstrated that combining Carboplatin or Paclitaxel with Pitavastatin or Ivermectin resulted in the most notable synergy. Acknowledging that 2D culture systems are limited in reflecting the tumor architecture, 3D cultures were generated to provide insights on treatment efficacy tests in more complex models. Objectives: We aimed to investigate whether combining Carboplatin or Paclitaxel with Pitavastatin or Ivermectin offers therapeutic benefits in a Cultrex-based 3D model. Methods: Here, the cytotoxicity of Carboplatin and Paclitaxel, both alone and in combination with Pitavastatin or Ivermectin, were analyzed on two chemoresistant tumor cell lines, OVCAR8 and OVCAR8 PTX R C, in 3D cultures. Cellular viability was assessed using CellTiter-Glo® Luminescent assays. Also, it explored synergistic interactions using zero interaction potency, Loewe, Bliss independence, and High-single agent reference models. Results: Our research indicates combining chemotherapeutic drugs with Pitavastatin or Ivermectin yields significantly more cytotoxic effects than chemotherapy alone. For all the combinations tested, at least one model indicated an additive effect; however, only the combination of Paclitaxel and Ivermectin consistently demonstrated an additive effect across all chemoresistant cell lines cultured in 3D models, as well as in all four synergy reference models used to assess drug interactions. Conclusions: Combining Paclitaxel with Ivermectin has the highest cytotoxic and the strongest additive effect for both chemoresistant cell lines compared to Paclitaxel alone.

Infection with the protozoan parasite Trypanosoma cruzi causes human Chagas disease. Benznidazole (BNZ) and nifurtimox are the current drugs for the treatment; however, they induce severe adverse side effects in patients; therefore, there is a need to improve the treatment effectiveness and efficiency of these drugs for its safer use. Background/Objective: Glyburide, glipizide, and gliquidone, hypoglycemic drugs for diabetes treatment, were previously predicted to bind to dihydrofolate reductase-thymidylate synthase from T. cruzi by in silico docking analysis; they also showed antiproliferative effects against T. cruzi epimastigotes, the stage of the insect vector. In the present study, the potential parasiticidal effect of these antidiabetic drugs was tested in monotherapy and bi-therapy with BNZ in human cells in vitro and in animals. Methods: Evaluation was performed in (a) a model of in vitro infection of T. cruzi trypomastigotes using human fibroblasts as host cells and (b) in mice infected with T. cruzi. Results: The antidiabetic drugs in monotherapy showed antiparasitic effects in preventing infection progression (trypomastigotes release), with an IC50 of 8.4–14.3 µM in comparison to that of BNZ (0.26 µM) in vitro. However, in bi-therapy, the presence of just 0.5 or 1 µM of the antidiabetics decreased the BNZ IC50 by 5–10 times to 0.03–0.05 µM. Remarkably, the antidiabetic drugs in monotherapy decreased the infection in mice by 40–60% in a similar extent to BNZ (80%). In addition, the combination of BNZ plus antidiabetics perturbed the antioxidant metabolites in epimastigotes. Conclusions: These results identified antidiabetics as potential drugs in combination therapy with BNZ to treat T. cruzi infection.

Currently, vaccines have shown efficacy against new SARS-CoV-2 variants. This study aimed to develop a systems medicine framework that can predict and validate drug combinations that can be repurposed for treating COVID-19 and its comorbidities, specifically type 2 diabetes and hypertension. This study found that gut microbes could potentially influence the action of drugs, innate immune response, intestinal dysfunction, and susceptibility to the virus in individuals with these comorbidities. It was also discovered that the spike protein of the virus interacts with 57 human genes, many of which are linked to food-borne bacteria. An analysis of disease enrichment showed that arthritis and hypertension were frequently observed as comorbidities in patients infected with SARS-CoV-2. Several drugs, including Fluvoxamine, Donepezil, and Ifenprodil, have been identified as potentially repurposable drugs for treating COVID-19 in individuals with hypertension. Moreover, nitazoxanide and tocilizumab (antivirals), bacitracin (antibacterial), and gliclazide (antidiabetics) were also identified as potential repurposable drugs. Tocilizumab and gliclazide are effective drug combinations for treating COVID-19 in individuals with type 2 diabetes. A combination of tocilizumab and lidocaine has also been suggested for treating COVID-19 in individuals infected with food-borne bacteria.

Abstract Alzheimer’s disease (AD) is the major form of dementia prevalent in older adults and with a high incidence in females. Identification of early biomarkers is essential for preventive intervention to delay its progression. Furthermore, due to its multifactorial nature, a multi-target approach could be therapeutically beneficial. Our studies included 4- (pre-pathology) and 11-month (mild-pathology) TgF344-AD rats, a transgenic Alzheimer’s model that exhibits age-dependent AD progression. We identified two potential early biomarker genes for AD, early growth response 2 (EGR2) and histone 1H2AA (HIST1H2AA), in the hippocampus of 4-month females. Out of 17,168 genes analyzed by RNA sequencing, expression of these two genes was significantly altered in 4-month TgF344-AD rats compared to wild-type littermates. We also evaluated co-treatment with diazoxide (DZ), a potassium channel activator, and dibenzoylmethane (DIB), which inhibits eIF2α-P activity, on TgF344-AD and wild-type rats. DZ/DIB-treatment mitigated spatial memory deficits and buildup of hippocampal Aβ plaques and tau PHF in 11-month TgF344-AD rats but had no effect on wild-type littermates. To our knowledge, this preclinical study is the first to report EGR2 and HIST1H2AA as potential AD biomarkers in females, and the benefits of DZ/DIB-treatment in AD. Evaluations across multiple AD-related models is warranted to corroborate our findings.

Saeed Shakibfar,1 Kristine H Allin,2 Tine Jess,2 Maria Antonietta Barbieri,1,3 Vera Battini,1,4 Eva Simoncic,1 Julien Kirchgesner,5 Trond Ulven,1,* Maurizio Sessa1,* 1Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark; 2Center for Molecular Prediction of Inflammatory Bowel Disease (PREDICT), Department of Clinical Medicine, Aalborg University, Copenhagen, Denmark; 3Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy; 4Pharmacovigilance & Clinical Research, International Centre for Pesticides and Health Risk Prevention, Department of Biomedical and Clinical Sciences (DIBIC), ASST Fatebenefratelli-Sacco University Hospital, Università Degli Studi Di Milano, Milan, Italy; 5Department of Gastroenterology, INSERM, Institut Pierre Louis d’Epidémiologie Et de Santé Publique, AP-HP, Hôpital Saint-Antoine, Sorbonne Université, Paris, France*These authors contributed equally to this workCorrespondence: Saeed Shakibfar, Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark, Email saeed.shakibfar@sund.ku.dkAim: Drug repurposing, utilizing electronic healthcare records (EHRs), offers a promising alternative by repurposing existing drugs for new therapeutic indications, especially for patients lacking effective therapies. Intestinal fibrosis, a severe complication of Crohn’s disease (CD), poses significant challenges, increasing morbidity and mortality without available pharmacological treatments. This article focuses on identifying medications associated with an elevated or reduced risk of fibrosis in CD patients through a population-wide real-world data and artificial intelligence (AI) approach.Methods: Patients aged 65 or older with a diagnosis of CD from 1996 to 2019 in the Danish EHRs were followed for up to 24 years. The primary outcome was the need of specific surgical procedures, namely proctocolectomy with ileostomy and ileocecal resection as proxies of intestinal fibrosis. The study explored drugs linked to an increased or reduced risk of the study outcome through machine-learning driven survival analysis.Results: Among the 9179 CD patients, 1029 (11.2%) underwent surgery, primarily men (58.5%), with a mean age of 76 years, 10 drugs were linked to an elevated risk of surgery for proctocolectomy with ileostomy and ileocecal resection. In contrast, 10 drugs were associated with a reduced risk of undergoing surgery for these conditions.Conclusion: This study focuses on repurposing existing drugs to prevent surgery related to intestinal fibrosis in CD patients, using Danish EHRs and advanced statistical methods. The findings offer valuable insights into potential treatments for this condition, addressing a critical unmet medical need. Further research and clinical trials are warranted to validate the effectiveness of these repurposed drugs in preventing surgery related to intestinal fibrosis in CD patients.Keywords: Crohn’s disease, drug repurposing, inflammatory bowel disease, intestinal fibrosis, machine-learning, real-world data

Abstract Background Despite recent advances in locoregional, systemic, and novel checkpoint inhibitor treatment, hepatocellular carcinoma (HCC) is still associated with poor prognosis. The feasibility of potentially curative liver resection (LR) and transplantation (LT) is limited by the underlying liver disease and a shortage of organ donors. Especially after LR, high recurrence rates present a problem and circulating tumor cells are a major cause of extrahepatic recurrence. Tigecycline, a commonly used glycylcycline antibiotic, has been shown to have antitumorigenic effects and could be used as a perioperative and adjuvant therapeutic strategy to target circulating tumor cells. We aimed to investigate the effect of tigecycline on HCC cell lines and its mechanisms of action. Methods Huh7, HepG2, Hep3B, and immortalized hepatocytes underwent incubation with clinically relevant tigecycline concentrations, and the influence on proliferation, migration, and invasion was assessed in two- and three-dimensional in vitro assays, respectively. Bioinformatic analysis was used to identify specific targets of tigecycline. The expression of RAC1 was detected using western blot, RT-PCR and RNA sequencing. ELISA and flow cytometry were utilized to measure reactive oxygen species (ROS) generation upon tigecycline treatment and flow cytometry to detect alterations in cell cycle. Changes in mitochondrial function were detected via seahorse analysis. RNA sequencing was performed to examine involved pathways. Results Tigecycline treatment resulted in a significant reduction of mitochondrial function with concomitantly preserved mitochondrial size, which preceded the observed decrease in HCC cell viability. The sensitivity of HCC cells to tigecycline treatment was higher than that of immortalized non-cancerous THLE-2 hepatocytes. Tigecycline inhibited both migratory and invasive properties. Tigecycline application led to an increase of detected ROS and an S-phase cell cycle arrest. Bioinformatic analysis identified RAC1 as a likely target for tigecycline and the expression of this molecule was increased in HCC cells as a result of tigecycline treatment. Conclusion Our study provides evidence for the antiproliferative effect of tigecycline in HCC. We show for the first time that this effect, likely to be mediated by reduced mitochondrial function, is associated with increased expression of RAC1. The reported effects of tigecycline with clinically relevant and achievable doses on HCC cells lay the groundwork for a conceivable use of this agent in cancer treatment.

Metformin is a commonly used drug for treating type 2 diabetes. Metformin is an inexpensive drug with low/no side effects and is well tolerated in human patients of different ages. Recent therapeutic strategies for human disease have considered the benefits of drug repurposing. This includes the use of the anti-diabetic drug metformin. Accordingly, the anti-inflammatory, anti-cancer, anti-viral, neuroprotective, and cardioprotective potentials of metformin have deemed it a suitable candidate for treating a plethora of human diseases. As results from preclinical studies using cellular and animal model systems appear promising, clinical trials with metformin in the context of non-diabetes-related illnesses have been started. Here, we aim to provide a comprehensive overview of the therapeutic potential of metformin in different animal models of human disease and its suggested relationship to epigenetics and ailments with epigenetic components.

Background: Histone deacetylase 6 (HDAC6) plays a crucial role in neurological, inflammatory, and other diseases; thus, it has emerged as an important target for therapeutic intervention. To date, there are no FDA-approved HDAC6-targeting drugs, and most pipeline candidates suffer from poor target engagement, inadequate brain penetration, and low tolerability. There are a few HDAC6 clinical candidates for the treatment of mostly non-CNS cancers as their pharmacokinetic liabilities exclude them from targeting HDAC6-implicated neurological diseases, urging development to address these challenges. They also demonstrate off-target toxicity due to limited selectivity, leading to adverse effects in patients. Selective inhibitors have thus been the focus of development over the past decade, though no selective and potent HDAC6 inhibitor has yet been approved. Methods: This study involved an integrated virtual screening against HDAC6 using the DrugBank database to identify repurposed drugs capable of inhibiting HDAC6 activity. The primary assessment involved the determination of the ability of molecules to bind with HDAC6. Subsequently, interaction analyses and 500 ns molecular dynamics (MD) simulations followed by essential dynamics were carried out to study the conformational flexibility and stability of HDAC6 in the presence of the screened molecules, i.e., penfluridol and pimozide. Results: The virtual screening results pinpointed penfluridol and pimozide as potential repurposed drugs against HDAC6 based on their binding efficiency and appropriate drug profiles. The docking results indicate that penfluridol and pimozide share the same binding site as the reference inhibitor with HDAC6. The MD simulation results showed that stable protein–ligand complexes of penfluridol and pimozide with HDAC6 were formed. Additionally, MMPBSA analysis revealed favorable binding free energies for all HDAC6–ligand complexes, confirming the stability of their interactions. Conclusions: The study implies that both penfluridol and pimozide have strong and favorable binding with HDAC6, which supports the idea of repositioning these drugs for the management of neurodegenerative disorders. However, further in-depth studies are needed to explore their efficacy and safety in biological systems.

Background: Dysregulation of receptor tyrosine kinase c-MET is known to promote tumor development by stimulating oncogenic signaling pathways in different cancers, including pediatric neuroblastoma (NB). NB is an extracranial solid pediatric cancer that accounts for almost 15% of all pediatric cancer-related deaths, with less than a 50% long-term survival rate. Results: In this study, we analyzed a large cohort of primary NB patient data and revealed that high MET expression strongly correlates with poor overall survival, disease progression, relapse, and high MYCN levels in NB patients. To determine the effects of c-MET in NB, we repurposed a small molecule inhibitor, tivantinib, and found that c-MET inhibition significantly inhibits NB cellular growth. Tivantinib significantly blocks NB cell proliferation and 3D spheroid tumor formation and growth in different MYCN-amplified and MYCN-non-amplified NB cell lines. Furthermore, tivantinib blocks the cell cycle at the G2/M phase transition and induces apoptosis in different NB cell lines. As expected, c-MET inhibition by tivantinib inhibits the expression of multiple genes in PI3K, STAT, and Ras cell signaling pathways. Conclusions: Overall, our data indicate that c-MET directly regulates NB growth and 3D spheroid growth, and c-MET inhibition by tivantinib may be an effective therapeutic approach for high-risk NB. Further developing c-MET targeted therapeutic approaches and combining them with current therapies may pave the way for effectively translating novel therapies for NB and other c-MET-driven cancers.

Background: Cu/Zn Superoxide Dismutase 1 (SOD1) is a 32 kDa cytosolic dimeric metalloenzyme that neutralizes superoxide anions into oxygen and hydrogen peroxide. Mutations in SOD1 are associated with ALS, a disease causing motor neuron atrophy and subsequent mortality. These mutations exert their harmful effects through a gain of function mechanism, rather than a loss of function. Despite extensive research, the mechanism causing selective motor neuron death still remains unclear. A defining feature of ALS pathogenesis is protein misfolding and aggregation, evidenced by ubiquitinated protein inclusions containing SOD1 in affected motor neurons. This work aims to identify compounds countering SOD1(A4V) misfolding and aggregation, which could potentially aid in ALS treatment. Methods: The approach employed was in vitro screening of a library comprising 1280 pharmacologically active compounds (LOPAC®) in the context of drug repurposing. Using differential scanning fluorimetry (DSF), these compounds were tested for their impact on SOD1(A4V) thermal stability. Results and Conclusions: Dimer stability was the parameter chosen as the criterion for screening, since the dissociation of the native SOD1 dimer is the step prior to its in vitro aggregation. The screening revealed one compound raising protein-ligand Tm by 6 °C, eleven inducing a higher second Tm, suggesting a stabilization effect, and fourteen reducing Tm from 10 up to 26 °C, suggesting possible interactions or non-specific binding.

Abstract Background We consider two key challenges that early-stage biotechnology firms face in developing a sustainable financing strategy and a sustainable business model: developing a valuation model for drug compounds, and choosing an appropriate operating model and corporate structure. We use the specific example of Unravel Biosciences—a therapeutics platform company that identifies novel drug targets through off-target mechanisms of existing drugs and then develops optimized new molecules—throughout the paper and explore a specific scenario of drug repurposing for rare genetic diseases. Results The first challenge consists of producing a realistic financial valuation of a potential rare disease repurposed drug compound, in this case targeting Rett syndrome. More generally, we develop a framework to value a portfolio of pairwise correlated rare disease compounds in early-stage development and quantify its risk profile. We estimate the probability of a negative return to be $$80.8\%$$ 80.8 % for a single compound and $$56.1\%$$ 56.1 % for a portfolio of 8 drugs. The probability of selling the project at a loss decreases from $$79.2\%$$ 79.2 % (phase 3) for a single compound to $$55.4\%$$ 55.4 % (phase 3) for the 8-drug portfolio. For the second challenge, we find that the choice of operating model and corporate structure is crucial for early-stage biotech startups and illustrate this point with three concrete examples. Conclusions Repurposing existing compounds offers important advantages that could help early-stage biotech startups better align their business and financing issues with their scientific and medical objectives, enter a space that is not occupied by large pharmaceutical companies, and accelerate the validation of their drug development platform.

Abstract Background Currently, the main pharmaceutical intervention for COVID-19 is vaccination. While antidepressant (AD) drugs have shown some efficacy in treatment of symptomatic COVID-19, their preventative potential remains largely unexplored. Analysis of association between prescription of ADs and COVID-19 incidence in the population would be beneficial for assessing the utility of ADs in COVID-19 prevention. Methods Retrospective study of association between AD prescription and COVID-19 diagnosis was performed in a cohort of community-dwelling adult mental health outpatients during the 1st wave of COVID-19 pandemic in the UK. Clinical record interactive search (CRIS) was performed for mentions of ADs within 3 months preceding admission to inpatient care of the South London and Maudsley (SLaM) NHS Foundation Trust. Incidence of positive COVID-19 tests upon admission and during inpatient treatment was the primary outcome measure. Results AD mention was associated with approximately 40% lower incidence of positive COVID-19 test results when adjusted for socioeconomic parameters and physical health. This association was also observed for prescription of ADs of the selective serotonin reuptake inhibitor (SSRI) class. Conclusions This preliminary study suggests that ADs, and SSRIs in particular, may be of benefit for preventing COVID-19 infection spread in the community. The key limitations of the study are its retrospective nature and the focus on a mental health patient cohort. A more definitive assessment of AD and SSRI preventative potential warrants prospective studies in the wider demographic.