Drug Repurposing Research Articles

The Potential of Drug Repurposing as a Rapid Response Strategy in COVID-19 Therapeutics

Drug repurposing has emerged as a promising strategy in the rapid development of effective therapeutics for COVID-19. This approach leverages existing medications, previously approved for other indications, to target the pathophysiological mechanisms of SARS-CoV-2 infection. Several drugs were tested during the COVID-19 pandemic, developed originally for other purposes and under less-than-ideal conditions. Some of the most well-known include remdesivir, an Ebola drug approved by the FDA for emergency use to treat COVID-19, and dexamethasone, a corticosteroid that reduces death associated with severe infection through immunomodulation. However, while hydroxychloroquine and ivermectin, among others, showed very meager or no benefit, it is clear that such early promise must be subjected to firm testing. Despite such promises, drug repurposing may face several inconsistent clinical outcomes, questions over safety, and the inability to address all forms of COVID-19 pathology. Key candidates identified through high-throughput screening and computational methods include antiviral agents, anti-inflammatory drugs, and those targeting host cell pathways critical for viral replication. This review discusses the efficacy and mechanisms of these repurposed drugs, highlights ongoing clinical trials, and addresses challenges such as resistance and optimal dosing. Ultimately, drug repurposing represents a crucial component of the multi-faceted response required to combat the COVID-19 pandemic effectively.

Pancreatic ductal adenocarcinoma, β-blockers and antihistamines: A clinical trial is needed.

Survival in pancreatic cancer (pancreatic ductal adenocarcinoma, PDAC) at just 5 months is the worst of all cancers. It is predicted to become the second highest cause of cancer deaths worldwide this decade and unlike most cancers, there has been little progress in improving survival in PDAC. Numerous studies including molecular and mechanistic studies, cancer biology studies and retrospective human epidemiological studies suggest that two well-known, approved drug classes - β-blockers and H1-antihistamines - may be beneficial and thus may potentially prolong life in patients with PDAC. In our opinion, the body of evidence has reached a point where the potential gains outweigh the very low risks involved in a clinical study in PDAC. We thus believe that it is now time for a clinical trial involving these two agents in PDAC patients. As a repurposing of generic drugs, this is not likely to be appealing to pharmaceutical companies and therefore is likely to require governmental, philanthropic and /or charitable organisational input. In this article, we opine and propose that an urgent clinical trial is needed to determine if repurposing these two orally administered, inexpensive, largely safe drug classes, either alone or in combination, could prolong survival in PDAC and thus improve the outcome for the 10,000 people worldwide who die from PDAC each week.

Integrated virtual screening and MD simulation study to discover potential inhibitors of mycobacterial electron transfer flavoprotein oxidoreductase.

Tuberculosis (TB) continues to be a major global health burden, with high incidence and mortality rates, compounded by the emergence and spread of drug-resistant strains. The limitations of current TB medications and the urgent need for new drugs targeting drug-resistant strains, particularly multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB, underscore the pressing demand for innovative anti-TB drugs that can shorten treatment duration. This has led to a focus on targeting energy metabolism of Mycobacterium tuberculosis (Mtb) as a promising approach for drug discovery. This study focused on repurposing drugs against the crucial mycobacterial protein, electron transfer flavoprotein oxidoreductase (EtfD), integral to utilizing fatty acids and cholesterol as a carbon source during infection. The research adopted an integrative approach, starting with virtual screening of approved drugs from the ZINC20 database against EtfD, followed by molecular docking, and concluding with molecular dynamics (MD) simulations. Diacerein, levonadifloxacin, and gatifloxacin were identified as promising candidates for repurposing against TB based on their strong binding affinity, stability, and interactions with EtfD. ADMET analysis and anti-TB sensitivity predictions assessed their pharmacokinetic and therapeutic potential. Diacerein and levonadifloxacin, previously unexplored in anti-tuberculous therapy, along with gatifloxacin, known for its efficacy in drug-resistant TB, have broad-spectrum antimicrobial properties and favorable pharmacokinetic profiles, suggesting potential as alternatives to current TB treatments, especially against resistant strains. This study underscores the efficacy of computational drug repurposing, highlighting bacterial energy metabolism and lipid catabolism as fruitful targets. Further research is necessary to validate the clinical suitability and efficacy of diacerein, levonadifloxacin, and gatifloxacin, potentially enhancing the arsenal against global TB.

Shared genetics between breast cancer and predisposing diseases identifies novel breast cancer treatment candidates.

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. 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. 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. 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.

Mebendazole effectively overcomes imatinib resistance by dual-targeting BCR/ABL oncoprotein and β-tubulin in chronic myeloid leukemia cells.

To target the pivotal BCR/ABL oncoprotein in chronic myeloid leukemia (CML) cells, tyrosine kinase inhibitors (TKIs) are utilized as landmark achievements in CML therapy. However, TKI resistance and intolerance remain principal obstacles in the treatment of CML patients. In recent years, drug repositioning provided alternative and promising perspectives apart from the classical cancer therapies, and promoted anthelmintic mebendazole (MBZ) as an effective anti-cancer drug in various cancers. Here, we investigated the role of MBZ in CML treatment including imatinib-resistant CML cells. Our results proved that MBZ inhibited the proliferation and induced apoptosis in CML cells. We found that MBZ effectively suppressed BCR/ABL kinase activity and MEK/ERK signaling pathway by reducing p-BCR/ABL and p-ERK levels with ABL1 targeting ability. Meanwhile, MBZ directly targeted the colchicine-binding site of β-tubulin protein, hampered microtubule polymerization and induced mitosis arrest and mitotic catastrophe. In addition, MBZ increased DNA damage levels and hampered the accumulation of ataxia-telangiectasia mutated and DNA-dependent protein kinase into the nucleus. This work discovered that anthelmintic MBZ exerts remarkable anticancer effects in both imatinib-sensitive and imatinib-resistant CML cells in vitro and revealed mechanisms underlying. From the perspective of drug repositioning and multi-target therapeutic strategy, this study provides a promising option for CML treatment, especially in TKI-resistant or intolerant individuals.

Decoding Acute Myeloid Leukemia: A Clinician’s Guide to Functional Profiling

Acute myeloid leukemia (AML) is a complex clonal disorder characterized by clinical, genetic, metabolomic, and epigenetic heterogeneity resulting in the uncontrolled proliferation of aberrant blood-forming precursor cells. Despite advancements in the understanding of the genetic, metabolic, and epigenetic landscape of AML, it remains a significant therapeutic challenge. Functional profiling techniques, such as BH3 profiling (BP), gene expression profiling (GEP), proteomics, metabolomics, drug sensitivity/resistance testing (DSRT), CRISPR/Cas9, and RNAi screens offer valuable insights into the functional behavior of leukemia cells. BP evaluates the mitochondrial response to pro-apoptotic BH3 peptides, determining a cell’s apoptotic threshold and its reliance on specific anti-apoptotic proteins. This knowledge can pinpoint vulnerabilities in the mitochondria-mediated apoptotic pathway in leukemia cells, potentially informing treatment strategies and predicting therapeutic responses. GEP, particularly RNA sequencing, evaluates the transcriptomic landscape and identifies gene expression alterations specific to AML subtypes. Proteomics and metabolomics, utilizing mass spectrometry and nuclear magnetic resonance (NMR), provide a detailed view of the active proteins and metabolic pathways in leukemia cells. DSRT involves exposing leukemia cells to a panel of chemotherapeutic and targeted agents to assess their sensitivity or resistance profiles and potentially guide personalized treatment strategies. CRISPR/Cas9 and RNAi screens enable systematic disruption of genes to ascertain their roles in leukemia cell survival and proliferation. These techniques facilitate precise disease subtyping, uncover novel biomarkers and therapeutic targets, and provide a deeper understanding of drug-resistance mechanisms. Recent studies utilizing functional profiling have identified specific mutations and gene signatures associated with aggressive AML subtypes, aberrant signaling pathways, and potential opportunities for drug repurposing. The integration of multi-omics approaches, advances in single-cell sequencing, and artificial intelligence is expected to refine the precision of functional profiling and ultimately improve patient outcomes in AML. This review highlights the diverse landscape of functional profiling methods and emphasizes their respective advantages and limitations. It highlights select successes in how these methods have further advanced our understanding of AML biology, identifies druggable targets that have improved outcomes, delineates challenges associated with these techniques, and provides a prospective view of the future where these techniques are likely to be increasingly incorporated into the routine care of patients with AML.

Enhancing the anticancer effect of metformin through nanoencapsulation: Apoptotic induction, inflammatory reduction, and suppression of cell migration in colorectal cancer cells.

Colorectal cancer (CRC) continues to be a significant health challenge, necessitating the development of efficient therapeutic strategies. Drug repurposing, which involves the use of existing medications for new purposes, presents a promising opportunity. Metformin, a widely used antidiabetic drug, has demonstrated potential anticancer effects. To enhance its efficacy, we formulated nano-metformin, metformin encapsulated within pectin nanoparticles. Our study aimed to evaluate the superiority of nano-metformin over free metformin in treating CRC. The cytotoxicity of both metformin and nano-metformin on Caco-2 CRC cells was assessed using the MTT assay, revealing a significant dose-dependent inhibition of cell growth using nano-metformin. The anti-inflammatory potential was evaluated by measuring the levels of nitric oxide and the pro-inflammatory cytokines IL-2 and IL-6 following lipopolysaccharide (LPS) induction, and the results revealed that treating LPS-induced cells with nano-metformin significantly reduced the production of these inflammatory mediators. To elucidate the mechanism of cell death, we employed an acridine orange/ethidium bromide staining assay, which revealed the enhancement of apoptotic cell death following treatment with nano-metformin. Additionally, we examined the expression of key apoptotic regulators using real-time qPCR. Nano-metformin, in particular, significantly downregulated the expression of the antiapoptotic markers Bcl-2 and Survivin while upregulating the proapoptotic caspases 3, 7, and 9. The comet assay revealed significant DNA damage induced by treatment with the nano-metformin compared with that in the free form. Moreover, nano-metformin significantly reduced the migration ability of cells. In conclusion, our work revealed the superior efficacy of our formulated nanoform over free metformin, highlighting its potential as a promising therapeutic agent for CRC treatment.

Abstract 4118735: Interpretable deep learning translation of GWAS findings for drug repurposing in Atrial Fibrillation

Introduction: Translating human genetic findings, such as genome-wide association studies (GWAS) to pathobiology and the discovery of therapeutic target remains a major challenge for Atrial Fibrillation (AF). We previously published a network topology-based deep learning framework to identify disease-associated genes (NETTAG). Hypothesis: By using a deep learning framework, we can efficiently identify AF risk genes, druggable targets, and candidates of repurposable drugs. Aims: To identify potential AF related genes and repurposable drug candidates using our deep learning framework. Methods: First, we collected the reported quantitative trait loci (QTLs) for AF from human heart tissues. Then, we identified the overlaps between the QTLs and the previously reported 150 AF GWAS loci in the latest meta-analysis. We previously built a comprehensive human protein-protein interactome using 18 publicly available databases, containing 351,444 unique PPIs and 17,706 proteins. Using the human protein-protein interactome and the overlaps between AF GWAS hits and QTLs, we prioritized genes and defined the genes with the top 1 % predicted score as AF risk genes (afRGs) using the NETTAG. Then, we assembled drugs from the Drugbank database relating 2,938 FDA-approved drugs or clinically investigated molecules. Using network proximity approaches to evaluate the closest distance between afRGs and a drug’s targets within the human protein-protein interactome, we computationally predicted drugs for AF using Z scores <-2.0. Results: We first collected the overlaps between AF GWAS hits and QTLs, which constituted 27 expression and 12 splicing QTLs. Via NETTAG, we identified 176 afRGs. Among the 176 predicted afRGs, 12 proteins (gene products of afRGs) have been identified as known drug targets with FDA-approved medicines. In total, 1,275 targets have been widely investigated as therapeutic targets for treating AF. Using the closest-based network proximity approach, we computationally identified 49 candidate drugs. These included drugs both reportedly potentially treating AF, such as Pioglitazone (Z=2.29), Telmisartan (Z=-2.52), Sildenafil (Z=-2.86), and those have never been reported before, such as Balsalazide (Z=-2.32). Conclusion: Using a deep learning methodology that utilized GWAS and QTL findings, we identified risk genes and repurposing drug candidates for AF.

Doxifluridine effectively kills antibiotic-resistant Staphylococcus aureus in chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality globally, often exacerbated by infections such as methicillin-resistant Staphylococcus aureus (MRSA). The rise in antibiotic-resistant strains complicates treatment and underscores the need for novel therapeutic drugs. In this paper, we further investigated the antimicrobial potential of a fluoropyrimidine anticancer drug doxifluridine against multidrug-resistant S. aureus. Determination of minimum inhibitory concentration (MIC) or minimum bactericidal concentration (MBC), monitoring of growth curve, time-kill assays, biofilm bactericidal assays, and chequerboard studies were conducted to evaluate the antibacterial efficacy of doxifluridine. Safety was assessed via hemolysis and cytotoxicity assays, and an in vivo Galleria mellonella larvae model was employed to test protective effects. Doxifluridine demonstrated significant antibacterial activity against clinical multidrug resistance (MDR) S. aureus isolates, with MIC and MBC values ranging from 0.5 to 2 µg/mL and 1 to 4 µg/mL, respectively. The results revealed doxifluridine's potent bactericidal effects within 8 hours. Moreover, doxifluridine-treated bacteria showed a substantial reduction in biofilm mass and viability. Furthermore, chequerboard assays indicated synergistic interactions between doxifluridine and other antibiotics, reducing MIC values by two- to eightfold. More importantly, safety evaluations confirmed that doxifluridine did not exhibit hemolytic toxicity or cytotoxicity. Finally, doxifluridine significantly increased the survival rate of MRSA-infected G. mellonella larvae in vivo. In brief, doxifluridine exhibited promising in vitro and in vivo antibacterial activity against MRSA, suggesting its potential as a repurposed drug for treating resistant bacterial infections in COPD patients.IMPORTANCEThe study provides robust evidence for the antibacterial efficacy of doxifluridine against Methicillin-resistant Staphylococcus aureus in chronic obstructive pulmonary disease (COPD) patients. Its rapid action, ability to disrupt biofilms, and synergistic effects with other antibiotics, combined with a favorable safety profile, highlight its potential as a repurposed therapeutic agent. Future clinical trials will be essential to confirm these findings and pave the way for its integration into clinical practice. This work not only provides candidate for tackling the management of bacterial infections in COPD but also exemplifies the potential of drug repurposing in combating antibiotic-resistant infections.

Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches.

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.

Bridging gap in treatment of polycystic ovarian syndrome through drug repurposing: what we achieved and where we are?

Polycystic ovarian syndrome (PCOS) is one of the chief causes of infertility in women of reproductive age. Several drugs belonging to the oral contraceptive class have been approved for the treatment of PCOS. Nonetheless, the capability to target only a few symptoms of PCOS and fatal side effects are key hurdles to their use. Therefore, repurposing existing drugs can be promising in managing PCOS efficiently. Drugs from different pharmacological classes like antidiabetics (metformin, rosiglitazone, pioglitazone, and semaglutide), statins (simvastatin and atorvastatin), antiandrogen drugs (finasteride and flutamide), etc. demonstrated significant potential in managing PCOS. The present review offers a comprehensive overview of all the medications examined as potential repurposed options for the efficient treatment of PCOS. The pathogenesis of PCOS, existing therapies for PCOS and their challenges, drug repurposing and its significance is also explained. The small-molecular drugs from various pharmacological classes and different phytoceuticals repurposed against PCOS are discussed along with their anti-PCOS activity mechanisms. Moreover, novel drug targets responsible for PCOS and opportunities for drug repurposing are briefed. The repurposed drugs in clinical trials for PCOS and drug repurposing challenges are discussed. Thus, drug repurposing can serve as a potential way to effectively treat PCOS, reducing the extent of infertility and improving the quality of life of women.

Crystal structure of N-terminally hexahistidine-tagged Onchocerca volvulus macrophage migration inhibitory factor-1.

Onchocerca volvulus causes blindness, onchocerciasis, skin infections and devastating neurological diseases such as nodding syndrome. New treatments are needed because the currently used drug, ivermectin, is contraindicated in pregnant women and those co-infected with Loa loa. The Seattle Structural Genomics Center for Infectious Disease (SSGCID) produced, crystallized and determined the apo structure of N-terminally hexahistidine-tagged O. volvulus macrophage migration inhibitory factor-1 (His-OvMIF-1). OvMIF-1 is a possible drug target. His-OvMIF-1 has a unique jellyfish-like structure with a prototypical macrophage migration inhibitory factor (MIF) trimer as the `head' and a unique C-terminal `tail'. Deleting the N-terminal tag reveals an OvMIF-1 structure with a larger cavity than that observed in human MIF that can be targeted for drug repurposing and discovery. Removal of the tag will be necessary to determine the actual biological oligomer of OvMIF-1 because size-exclusion chomatographic analysis of His-OvMIF-1 suggests a monomer, while PISA analysis suggests a hexamer stabilized by the unique C-terminal tails.

Structure-guided drug repurposing identifies aristospan as a potential inhibitor of β-lactamase: insights from virtual screening and molecular dynamics simulations

The rise of β-Lactamase mediated antibiotic resistance is a major concern for public health; hence, there is an urgent need to find new treatment approaches. Structure-guided drug repurposing offers a promising approach to swiftly deliver essential therapeutics in the fight against escalating antibiotic resistance. Here, a structure-guided virtual screening approach was used involving drug profiling, molecular docking, and molecular dynamics (MD) simulation to identify existing drugs against β-Lactamase-associated drug resistance. We exploited a large panel of FDA-approved drugs to an extensive in silico analysis to ascertain their ability to inhibit β-Lactamase. First, molecular docking investigations were performed to assess the binding affinities and interactions of screened molecules with the active site of β-Lactamase enzymes. Out of all the screened candidates, Aristospan was identified to possess promising characteristics, which include appropriate drug profiles, high binding specificity, and efficiency towards the binding pocket of β-Lactamase. Further analysis showed that Aristospan possesses several desirable biological characteristics and tends to bind to the β-Lactamase binding site. To explore the interactions further, the best docking pose of Aristospan was selected for MD simulations to assess the thermodynamic stability of the drug-enzyme complex and its conformational changes over 500 ns. The MD simulations in independent replica runs demonstrated that the β-Lactamase-Aristospan complex was stable in the 500 ns trajectory. These enlightening results suggest that Aristospan may harbor the potential for further evolution into a possible β-Lactamase inhibitor, with potential applications in overcoming antibiotic resistance in both Gram-positive and Gram-negative bacteria.

Network Medicine-Based Strategy Identifies Maprotiline as a Repurposable Drug by Inhibiting PD-L1 Expression via Targeting SPOP in Cancer.

Immune checkpoint inhibitors (ICIs) are drugs that inhibit immune checkpoint (ICP) molecules to restore the antitumor activity of immune cells and eliminate tumor cells. Due to the limitations and certain side effects of current ICIs, such as programmed death protein-1, programmed cell death-ligand 1, and cytotoxic T lymphocyte-associated antigen 4 (CTLA4) antibodies, there is an urgent need to find new drugs with ICP inhibitory effects. In this study, a network-based computational framework called multi-network algorithm-driven drug repositioning targeting ICP (Mnet-DRI) is developed to accurately repurpose novel ICIs from ≈3000 Food and Drug Administration-approved or investigational drugs. By applying Mnet-DRI to PD-L1, maprotiline (MAP), an antidepressant drug is repurposed, as a potential PD-L1 modifier for colorectal and lung cancers. Experimental validation revealed that MAP reduced PD-L1 expression by targeting E3 ubiquitin ligase speckle-type zinc finger structural protein (SPOP), and the combination of MAP and anti-CTLA4 in vivo significantly enhanced the antitumor effect, providing a new alternative for the clinical treatment of colorectal and lung cancer.

Network medicine informed multiomics integration identifies drug targets and repurposable medicines for Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a devastating, immensely complex neurodegenerative disease by lack of effective treatments. We developed a network medicine methodology via integrating human brain multi-omics data to prioritize drug targets and repurposable treatments for ALS. We leveraged non-coding ALS loci effects from genome-wide associated studies (GWAS) on human brain expression quantitative trait loci (QTL) (eQTL), protein QTL (pQTL), splicing QTL (sQTL), methylation QTL (meQTL), and histone acetylation QTL (haQTL). Using a network-based deep learning framework, we identified 105 putative ALS-associated genes enriched in known ALS pathobiological pathways. Applying network proximity analysis of predicted ALS-associated genes and drug-target networks under the human protein-protein interactome (PPI) model, we identified potential repurposable drugs (i.e., Diazoxide and Gefitinib) for ALS. Subsequent validation established preclinical evidence for top-prioritized drugs. In summary, we presented a network-based multi-omics framework to identify drug targets and repurposable treatments for ALS and other neurodegenerative disease if broadly applied.

Antifungal Associations with a Polyelectrolyte Promote Significant Reduction of Minimum Inhibitory Concentrations against Opportunistic Candida spp. Strains.

The current global scenario presents us with a growing increase in infections caused by fungi, referred to by specialists in the field as a "silent epidemic", aggravated by the limited pharmacological arsenal and increasing resistance to this therapy. For this reason, drug repositioning and therapeutic compound combinations are promising strategies to mitigate this serious problem. In this context, this study investigates the antifungal activity of the non-toxic, low-cost and widely available cationic polyelectrolyte Poly(diallyldimethylammonium chloride) (PDDA), in combination with different antifungal drugs: systemic (amphotericin B, AMB), topical (clioquinol, CLIO) and oral (nitroxoline, NTX). For each combination, different drug:PDDA ratios were tested and, through the broth microdilution technique, the minimum inhibitory concentration (MIC) of these drugs in the different ratios against clinically important Candida species strains was determined. Overall, PDDA combinations with the studied drugs demonstrated a significant increase in drug activity against most strains, reaching MIC reductions of up to 512 fold for the fluconazole resistant Candida krusei (Pichia kudriavzevii). In particular, the AMB-PDDA combination 1:99 was highly effective against AMB-resistant strains, demonstrating the excellent profile of PDDA as an adjuvant/association in novel antifungal formulations with outdated conventional drugs.

Deciphering the genetic underpinnings of neuroticism: A Mendelian randomization study of druggable gene targets

BackgroundNeuroticism, known for its association with a greater risk of psychiatric conditions such as depression and anxiety, is a critical focus of research. MethodsCis-expression quantitative trait loci (eQTLs) from 31,684 whole blood samples provided by the eQTLGen Consortium, alongside data from a large neuroticism cohort, were analyzed to identify genes causally linked to neuroticism. To further explore the influence of gene expression changes on neuroticism, colocalization analysis was conducted. Identified drug targets were assessed for potential side effects using a phenome-wide association study (PheWAS). Additionally, we utilized multiple databases to explore the interactions between drugs and genes for drug prediction and assess the current medications for drug repurposing. ResultsThe analysis involved a total of 4473 druggable genes, with two-sample Mendelian randomization (MR) identifying 186 genes that are causally linked to neuroticism. Colocalization analysis highlighted 11 genes (TLR4, MMRN1, EP300, BRAF, ORM1, ACVR1B, LRRC17, NOS2, ADAMTS6, GPX1, and VCL) with a posterior probability of colocalization (PPH4) >0.8. PheWAS revealed that drugs targeting BRAF, LRRC17, ADAMTS6, and GPX1 were also associated with other traits. Notably, six of these genes (TLR4, MMRN1, BRAF, ACVR1B, NOS2, and GPX1) are already being explored for drug development in psychiatric and other diseases. ConclusionThis study pinpointed six genes as promising therapeutic targets for neuroticism. The repurposing and development of drugs targeting these genes hold potential for managing neuroticism and associated psychiatric disorders.

Drug Repurposing against Novel Therapeutic Targets in Plasmodium falciparum for Malaria: The Computational Perspective.

Malaria remains one of the most challenging tropical diseases. Since malaria cases are reportedly alarming in terms of infections and mortality, urgent attention is needed for addressing the issues of drug resistance in falciparum malaria. High throughput screening methods have paved way for rapid identification of anti-malarial. Furthermore, drug repurposing helps in shortening the time required for drug safety approvals. Hence, discovery of new antimalarials by drug repurposing is a promising approach for combating the disease. This article summarizes the recent computational approaches used for identifying novel antimalarials by using drug target interaction tools followed by pharmacokinetic studies.

Precision Meets Repurposing: Innovative Approaches in Human Papillomavirus and Epstein-Barr Virus-Driven Cancer Therapy

Viral malignancies represent a distinct entity among cancers. Oncoviruses like the Human Papilloma Virus (HPV) and the Epstein Barr Virus (EBV) are highly potent inducers of oncogenic transformation leading to tumor development. HPV and EBV are known to be increasingly involved in the pathogenesis of various classes of cancers like cervical, head and neck, colorectal, breast, oral and anogenitial. Therapeutic vaccines directed at such oncoviruses, often fail to unleash the desired immune response against the tumor. This is largely due to the immunosuppressive microenvironment of the virus-induced tumors. Consequently, metronomic chemotherapies administered in conjunction with therapeutic viral vaccines have considerably enhanced the antitumor activity of these vaccines. Moreover, given the unique attributes of HPV and EBV-associated cancers, therapeutic agents directly targeting the oncoproteins of these viruses are still obscure. In this light, an increasing number of reports have evidenced the repurposing of drugs for therapeutic benefits in such cancers. This work delineates the significance and implications of metronomic chemotherapy and drug repurposing in HPV and EBV-associated cancers.

Transcriptomic imputation identifies tissue-specific genes associated with cervical myelopathy

Degenerative cervical myelopathy (DCM) is a progressive spinal condition that can lead to severe neurological dysfunction. Despite its degenerative pathophysiology, family history has shown to be a largely important factor in incidence and progression, suggesting that inherent genetic predisposition may play a role in pathophysiology. To determine the tissue-specific, functional genetic basis of hereditary predisposition to cervical myelopathy. Retrospective case-control study using patient genetics and matched EHR from the Mount Sinai BioMe Biobank. In a large, diverse, urban biobank of 32,031 individuals, with 558 individuals with cervical myopathy, we applied transcriptomic imputation to identify genetically regulated gene expression signatures associated with DCM. We performed drug-repurposing analysis using the CMAP database to identify candidate therapeutic interventions to reverse the cervical myelopathy-associated gene signature. We identified 16 genes significantly associated with DCM across five different tissues, suggesting tissue-specific manifestations of inherited genetic risk (upregulated: HES6, PI16, TMEM183A, BDH2, LINC00937, CLEC4D, USP43, SPATA1; downregulated: TTC12, CDK5, PAFAH1B2, RCSD1, KLHL29, PTPRG, RP11-620J15.3, C1RL). Drug repurposing identified 22 compounds with the potential to reverse the DCM-associated signature, suggesting points of therapeutic intervention. The inherited genetic risk for cervical myelopathy is functionally associated with genes involved in tissue-specific nociceptive and proliferative processes. These signatures may be reversed by candidate therapeutics with nociceptive, calcium channel modulating, and antiproliferative effects. Understanding the genetic basis of DCM provides critical insights into the hereditary factors contributing to the disease, allowing for more personalized and targeted therapeutic approaches. The identification of candidate drugs through transcriptomic imputation and drug repurposing analysis offers potential new treatments that could significantly improve patient outcomes and quality of life by addressing the underlying genetic mechanisms of DCM.