Cell Death Differ. 2023 May 4. doi: 10.1038/s41418-023-01167-4. Online ahead of print.

ABSTRACT

Drug repurposing is a versatile strategy to improve current therapies. Disulfiram has long been used in the treatment of alcohol dependency and multiple clinical trials to evaluate its clinical value in oncology are ongoing. We have recently reported that the disulfiram metabolite diethyldithiocarbamate, when combined with copper (CuET), targets the NPL4 adapter of the p97VCP segregase to suppress the growth of a spectrum of cancer cell lines and xenograft models in vivo. CuET induces proteotoxic stress and genotoxic effects, however important issues concerning the full range of the CuET-evoked tumor cell phenotypes, their temporal order, and mechanistic basis have remained largely unexplored. Here, we have addressed these outstanding questions and show that in diverse human cancer cell models, CuET causes a very early translational arrest through the integrated stress response (ISR), later followed by features of nucleolar stress. Furthermore, we report that CuET entraps p53 in NPL4-rich aggregates leading to elevated p53 protein and its functional inhibition, consistent with the possibility of CuET-triggered cell death being p53-independent. Our transcriptomics profiling revealed activation of pro-survival adaptive pathways of ribosomal biogenesis (RiBi) and autophagy upon prolonged exposure to CuET, indicating potential feedback responses to CuET treatment. The latter concept was validated here by simultaneous pharmacological inhibition of RiBi and/or autophagy that further enhanced CuET's tumor cytotoxicity, using both cell culture and zebrafish in vivo preclinical models. Overall, these findings expand the mechanistic repertoire of CuET's anti-cancer activity, inform about the temporal order of responses and identify an unorthodox new mechanism of targeting p53. Our results are discussed in light of cancer-associated endogenous stresses as exploitable tumor vulnerabilities and may inspire future clinical applications of CuET in oncology, including combinatorial treatments and focus on potential advantages of using certain validated drug metabolites, rather than old, approved drugs with their, often complex, metabolic profiles.

PMID:37142656 | DOI:10.1038/s41418-023-01167-4

Bioorg Med Chem. 2023 Apr 25;86:117294. doi: 10.1016/j.bmc.2023.117294. Online ahead of print.

ABSTRACT

Drug repurposing is a distinguished approach for drug development that saves a great deal of time and money. Based on our previous successful repurposing of a compound BMMP from anti-HIV-1 therapy to anti-cancer metastatic activity, we adopted the same techniques for repurposing benzimidazole derivatives considering MM-1 as a lead compound. An extensive structure-activity relationship (SAR) study afforded three promising compounds, MM-1d, MM-1h, and MM-1j, which inhibited cell migration in a similar fashion to BMMP. These compounds suppressed CD44 mRNA expression, whereas only MM-1h further suppressed mRNA expression of the epithelial-mesenchymal transition (EMT) marker zeb 1. Using benzimidazole instead of methyl pyrimidine as in BMMP resulted in better affinity for heterogeneous nuclear ribonucleoprotein (hnRNP) M protein and higher anti-cell migration activity. In conclusion, our study identified new agents that surpass the affinity of BMMP for hnRNP M and have anti-EMT activity, which makes them worthy of future attention and optimization.

PMID:37141680 | DOI:10.1016/j.bmc.2023.117294

Acta Pharm Sin B. 2023 Apr;13(4):1671-1685. doi: 10.1016/j.apsb.2022.08.023. Epub 2022 Sep 5.

ABSTRACT

Sodium-glucose cotransporter 2 (SGLT2) inhibitors have been reapproved for heart failure (HF) therapy in patients with and without diabetes. However, the initial glucose-lowering indication of SGLT2i has impeded their uses in cardiovascular clinical practice. A challenge of SGLT2i then becomes how to separate their anti-HF activity from glucose-lowering side-effect. To address this issue, we conducted structural repurposing of EMPA, a representative SGLT2 inhibitor, to strengthen anti-HF activity and reduce the SGLT2-inhibitory activity according to structural basis of inhibition of SGLT2. Compared to EMPA, the optimal derivative JX01, which was produced by methylation of C2-OH of the glucose ring, exhibited weaker SGLT2-inhibitory activity (IC50 > 100 nmol/L), and lower glycosuria and glucose-lowering side-effect, better NHE1-inhibitory activity and cardioprotective effect in HF mice. Furthermore, JX01 showed good safety profiles in respect of single-dose/repeat-dose toxicity and hERG activity, and good pharmacokinetic properties in both mouse and rat species. Collectively, the present study provided a paradigm of drug repurposing to discover novel anti-HF drugs, and indirectly demonstrated that SGLT2-independent molecular mechanisms play an important role in cardioprotective effects of SGLT2 inhibitors.

PMID:37139418 | PMC:PMC10149898 | DOI:10.1016/j.apsb.2022.08.023

PeerJ Comput Sci. 2017 Feb 13;3:e106. doi: 10.7717/peerj-cs.106. eCollection 2017.

ABSTRACT

Metastatic cutaneous melanoma is an aggressive skin cancer with some progression-slowing treatments but no known cure. The omics data explosion has created many possible drug candidates; however, filtering criteria remain challenging, and systems biology approaches have become fragmented with many disconnected databases. Using drug, protein and disease interactions, we built an evidence-weighted knowledge graph of integrated interactions. Our knowledge graph-based system, ReDrugS, can be used via an application programming interface or web interface, and has generated 25 high-quality melanoma drug candidates. We show that probabilistic analysis of systems biology graphs increases drug candidate quality compared to non-probabilistic methods. Four of the 25 candidates are novel therapies, three of which have been tested with other cancers. All other candidates have current or completed clinical trials, or have been studied in in vivo or in vitro. This approach can be used to identify candidate therapies for use in research or personalized medicine.

PMID:37133296 | PMC:PMC10151034 | DOI:10.7717/peerj-cs.106

ArXiv. 2023 Apr 18:arXiv:2304.09344v1. Preprint.

ABSTRACT

Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge graphs can easily represent heterogeneous types of information, and many algorithms and tools exist for querying and analyzing graphs. Biomedical knowledge graphs have been used in a variety of applications, including drug repurposing, identification of drug targets, prediction of drug side effects, and clinical decision support. Typically, knowledge graphs are constructed by centralization and integration of data from multiple disparate sources. Here, we describe BioThings Explorer, an application that can query a virtual, federated knowledge graph derived from the aggregated information in a network of biomedical web services. BioThings Explorer leverages semantically precise annotations of the inputs and outputs for each resource, and automates the chaining of web service calls to execute multi-step graph queries. Because there is no large, centralized knowledge graph to maintain, BioThing Explorer is distributed as a lightweight application that dynamically retrieves information at query time. More information can be found at https://explorer.biothings.io, and code is available at https://github.com/biothings/biothings_explorer.

PMID:37131885 | PMC:PMC10153288

bioRxiv. 2023 Apr 19:2023.04.19.537517. doi: 10.1101/2023.04.19.537517. Preprint.

ABSTRACT

Fungal pathogens like Candida albicans can cause devastating human disease. Treatment of candidemia is complicated by the high rate of resistance to common antifungal therapies. Additionally, there is host toxicity associated with many antifungal compounds due to the conservation between essential mammalian and fungal proteins. An attractive new approach for antimicrobial development is to target virulence factors: non-essential processes that are required for the organism to cause disease in human hosts. This approach expands the potential target space while reducing the selective pressure towards resistance, as these targets are not essential for viability. In C. albicans, a key virulence factor is the ability to transition to hyphal morphology. We developed a high-throughput image analysis pipeline to distinguish between yeast and filamentous growth in C. albicans at the single cell level. Based on this phenotypic assay, we screened the FDA drug repurposing library of 2,017 compounds for their ability to inhibit filamentation and identified 33 compounds that block the hyphal transition in C. albicans with IC 50 values ranging from 0.2 to 150 µM. Multiple compounds showed a phenyl vinyl sulfone chemotype, prompting further analysis. Of these phenyl vinyl sulfones, NSC 697923 displayed the most efficacy, and by selecting for resistant mutants, we identified eIF3 as the target of NSC 697923 in C. albicans .

PMID:37131825 | PMC:PMC10153179 | DOI:10.1101/2023.04.19.537517

bioRxiv. 2023 Apr 19:2023.04.19.537449. doi: 10.1101/2023.04.19.537449. Preprint.

ABSTRACT

Yes-associated protein (YAP), the downstream effector of the evolutionarily conserved Hippo pathway, promotes cellular proliferation and coordinates certain regenerative responses in mammals. Small molecule activators of YAP may therefore display therapeutic utility in treating disease states involving insufficient proliferative repair. From a high-throughput chemical screen of the comprehensive drug repurposing library ReFRAME, here we report the identification of SM04690, a clinical stage inhibitor of CLK2, as a potent activator of YAP driven transcriptional activity in cells. CLK2 inhibition promotes alternative splicing of the Hippo pathway protein AMOTL2, producing an exon-skipped gene product that can no longer associate with membrane-bound proteins, resulting in decreased phosphorylation and membrane localization of YAP. This study reveals a novel mechanism by which pharmacological perturbation of alternative splicing inactivates the Hippo pathway and promotes YAP dependent cellular growth.

PMID:37131806 | PMC:PMC10153145 | DOI:10.1101/2023.04.19.537449

Res Sq. 2023 Apr 18:rs.3.rs-2809689. doi: 10.21203/rs.3.rs-2809689/v1. Preprint.

ABSTRACT

Background Glioblastoma (GBM) is the most aggressive and common malignant primary brain tumor; however, treatment remains a significant challenge. This study aims to identify drug repurposing candidates for GBM by developing an integrative rare disease profile network containing heterogeneous types of biomedical data. Methods We developed a Glioblastoma-based Biomedical Profile Network (GBPN) by extracting and integrating biomedical information pertinent to GBM-related diseases from the NCATS GARD Knowledge Graph (NGKG). We further clustered the GBPN based on modularity classes which resulted in multiple focused subgraphs, named mc_GBPN. We then identified high-influence nodes by performing network analysis over the mc_GBPN and validated those nodes that could be potential drug repositioning candidates for GBM. Results We developed the GBPN with 1,466 nodes and 107,423 edges and consequently the mc_GBPN with forty-one modularity classes. A list of the ten most influential nodes were identified from the mc_GBPN. These notably include Riluzole, stem cell therapy, cannabidiol, and VK-0214, with proven evidence for treating GBM. Conclusion Our GBM-targeted network analysis allowed us to effectively identify potential candidates for drug repurposing. This could lead to less invasive treatments for glioblastoma while significantly reducing research costs by shortening the drug development timeline. Furthermore, this workflow can be extended to other disease areas.

PMID:37131675 | PMC:PMC10153381 | DOI:10.21203/rs.3.rs-2809689/v1

AMIA Annu Symp Proc. 2023 Apr 29;2022:1163-1172. eCollection 2022.

ABSTRACT

Adverse event reports (AER) are widely used for post-market drug safety surveillance and drug repurposing, with the assumption that drugs with similar side-effects may have similar therapeutic effects also. In this study, we used distributed representations of drugs derived from the Food and Drug Administration (FDA) AER system using aer2vec, a method of representing AER, with drug embeddings emerging from a neural network trained to predict the probability of adverse drug effects given observed drugs. We combined these representations with molecular features to predict permeability of the blood-brain barrier to drugs, a prerequisite to their application to treat conditions of the central nervous system. Across multiple machine learning classifiers, the addition of distributed representations improved performance over prior methods using drug-drug similarity estimates derived from discrete representations of AER system data. Embedding-based approaches outperformed those using discrete statistics, with improvements in absolute AUC of 5% and 9%, corresponding to improvements of 9% and 13% over performance with molecular features only. Performance was retained when reducing embedding dimensions from 500 to 6, indicating that they are neither attributable to overfitting, nor to a difference in the number of trainable parameters. These results indicate that aer2vec distributed representations carry information that is valuable for drug repurposing.

PMID:37128462 | PMC:PMC10148361

Curr Drug Res Rev. 2023 Apr 29. doi: 10.2174/2589977515666230430004013. Online ahead of print.

ABSTRACT

BACKGROUND: Mucormycosis has been infesting the universe for a while back, often with no prompt treatments. The disease devastation is spreading at an alarming rate. Many researchers are still hoping for a good potential drug that could help the healthcare system in this tussle. Molecular docking is an in silico tool that has gained popularity over the last few decades. Knowing the mechanism of enzymatic action is aided by imitating membrane protein actions in binding ligands.

AIM: The aim of this perspective is to determine whether an existing drug, daclatasvir, has antifungal activity.

OBJECTIVE: The primary objective of this in silico study was to investigate the potential effects of the binding affinity of daclatasvir with the crucial protein (1XFF) of mucormycosis, as well as the binding pattern of the active site amino acids with the drug molecule.

MATERIALS AND METHODS: To calculate the binding affinity of daclatasvir to the fungal protein 1XFF, Auto Dock Vina was used for molecular docking studies. The CDOCKER protocol was used to determine the receptor-ligand interaction by configuring various parameters.

RESULTS: The docking energy of the ligand (daclatasvir) on the protein (1XFF) was found to be -16.7216 kcal/mol, while the interaction energy was found to be - 42.1314 kcal/mol.

CONCLUSION: The binding pattern completely alters the dynamics of the protein, resulting in the breakdown of the fungal wall. The vital protein (1XFF) of Rhizopus oryzae is proposed as a possible protein target for the non-structural protein 5A inhibitor/antiviral drug daclatasvir in this study.

PMID:37125653 | DOI:10.2174/2589977515666230430004013

Cell Oncol (Dordr). 2023 Apr 29. doi: 10.1007/s13402-023-00822-9. Online ahead of print.

ABSTRACT

PURPOSE: Neuroendocrine prostate cancer (NEPC), a highly aggressive subtype of prostate cancer displaying resistance to hormone therapy, presents a poor prognosis and limited therapeutic options. Here, we aimed to find novel medication therapies for NEPC and explore the underlying mechanism.

METHODS: A high-throughput drug screening utilizing an FDA-approved drug library was performed and ketotifen, an antihistamine agent, was identified as a potential therapeutic candidate for NEPC. The whole-transcriptome sequencing analysis was conducted to explore mechanism of ketotifen inhibitory in NEPC. Multiple cell biology and biochemistry experiments were performed to confirm the inhibitory effect of ketotifen in vitro. A spontaneous NEPC mice model (PBCre4:Ptenf/f;Trp53f/f;Rb1f/f) was used to reveal the inhibitory effect of ketotifen in vivo.

RESULTS: Our in vitro experiments demonstrated that ketotifen effectively suppressed neuroendocrine differentiation, reduced cell viability, and reversed the lineage switch via targeting the IL-6/STAT3 pathway. Our in vivo results showed that ketotifen significantly prolonged overall survival and reduced the risk of distant metastases in NEPC mice model.

CONCLUSION: Our findings repurpose ketotifen for antitumor applications and endorse its clinical development for NEPC therapy, offering a novel and promising therapeutic strategy for this formidable cancer subtype.

PMID:37120492 | DOI:10.1007/s13402-023-00822-9

J Biomed Inform. 2023 Apr 27:104373. doi: 10.1016/j.jbi.2023.104373. Online ahead of print.

ABSTRACT

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

PMID:37120047 | DOI:10.1016/j.jbi.2023.104373

Arch Virol. 2023 Apr 28;168(5):147. doi: 10.1007/s00705-023-05770-1.

ABSTRACT

Hepatitis E virus (HEV) is endemic in several developing countries of Africa and Asia. It mainly causes self-limiting waterborne infections, in either sporadic or outbreak form. Recently, HEV was shown to cause chronic infections in immunosuppressed individuals. Ribavirin and interferon, the current off-label treatment options for hepatitis E, have several side effects. Hence, there is a need for new drugs. We evaluated the antimalarial drug artesunate (ART) against genotype 1 HEV (HEV-1) and HEV-3 using a virus-replicon-based cell culture system. ART exhibited 59% and 43% inhibition of HEV-1 and HEV-3, respectively, at the highest nontoxic concentration. Computational molecular docking analysis showed that ART can bind to the helicase active site (affinity score, -7.4 kcal/mol), indicating its potential to affect ATP hydrolysis activity. An in vitro ATPase activity assay of the helicase indeed showed 24% and 55% inhibition at 19.5 µM (EC50) and 78 µM concentrations of ART, respectively. Since ATP is a substrate of RNA-dependent RNA polymerase (RdRp) as well, we evaluated the effect of ART on the enzymatic activity of the viral polymerase. Interestingly, ART showed 26% and 40% inhibition of the RdRp polymerase activity at 19.5 µM and 78 µM concentrations of ART, respectively. It could be concluded from these findings that ART inhibited replication of both HEV-1 and HEV-3 by directly targeting the activities of the viral enzymes helicase and RdRp. Considering that ART is known to be safe in pregnant women, we think this antimalarial drug deserves further evaluation in animal models.

PMID:37115342 | DOI:10.1007/s00705-023-05770-1

Sci Rep. 2023 Apr 28;13(1):6972. doi: 10.1038/s41598-023-33024-2.

ABSTRACT

SARS-CoV-2 infection has led to several million deaths worldwide and ravaged the economies of many countries. Hence, developing therapeutics against SARS-CoV-2 remains a core priority in the fight against COVID-19. Most of the drugs that have received emergency use authorization for treating SARS-CoV-2 infection exhibit a number of limitations, including side effects and questionable efficacy. This challenge is further compounded by reinfection after vaccination and the high likelihood of mutations, as well as the emergence of viral escape mutants that render SARS-CoV-2 spike glycoprotein-targeting vaccines ineffective. Employing de novo drug synthesis or repurposing to discover broad-spectrum antivirals that target highly conserved pathways within the viral machinery is a focus of current research. In a recent drug repurposing study, masitinib, a clinically safe drug against the human coronavirus OC43 (HCoV-OC43), was identified as an antiviral agent with effective inhibitory activity against the SARS-CoV-2 3CLpro. Masitinib is currently under clinical trial in combination with isoquercetin in hospitalized patients (NCT04622865). Nevertheless, masitinib has kinase-related side effects; hence, the development of masitinib analogs with lower anti-tyrosine kinase activity becomes necessary. In this study, in an attempt to address this limitation, we executed a comprehensive virtual workflow in silico to discover drug-like compounds matching selected pharmacophore features in the SARS-CoV-2 3CLpro-bound state of masitinib. We identified a novel lead compound, "masitinibL", a drug-like analog of masitinib that demonstrated strong inhibitory properties against the SARS-CoV-2 3CLpro. In addition, masitinibL further displayed low selectivity for tyrosine kinases, which strongly suggests that masitinibL is a highly promising therapeutic that is preferable to masitinib.

PMID:37117213 | DOI:10.1038/s41598-023-33024-2

Eur J Med Chem. 2023 Apr 23;255:115401. doi: 10.1016/j.ejmech.2023.115401. Online ahead of print.

ABSTRACT

Discovering new anticancer drugs has been widely concerned and remains an open challenge. Target- and phenotypic-based experimental screening represent two mainstream anticancer drug discovery methods, which suffer from time-consuming, labor-intensive, and high experimental costs. In this study, we collected 485,900 compounds involving in 3,919,974 bioactivity records against 426 anticancer targets and 346 cancer cell lines from academic literature, as well as 60 tumor cell lines from NCI-60 panel. A total of 832 classification models (426 target- and 406 cell-based predictive models) were then constructed to predict the inhibitory activity of compounds against targets and tumor cell lines using FP-GNN deep learning method. Compared to the classical machine learning and deep learning methods, the FP-GNN models achieve considerable overall predictive performance, with the highest AUC values of 0.91, 0.88, 0.91 for the test sets of targets, academia-sourced and NCI-60 cancer cell lines, respectively. A user-friendly webserver called DeepCancerMap and its local version were developed based on these high-quality models, enabling users to perform anticancer drug discovery-related tasks including large-scale virtual screening, profiling prediction of anticancer agents, target fishing, and drug repositioning. We anticipate this platform to accelerate the discovery of anticancer drugs in the field. DeepCancerMap is freely available at https://deepcancermap.idruglab.cn.

PMID:37116265 | DOI:10.1016/j.ejmech.2023.115401

J Biomol Struct Dyn. 2023 Apr 28:1-18. doi: 10.1080/07391102.2023.2204973. Online ahead of print.

ABSTRACT

The pandemic outbreak of COVID-19 caused by the new severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a global health burden. To date, there is no highly effective antiviral therapy to eradicate the virus; as a result, researchers are racing to introduce new potential therapeutic agents. Alternatively, traditional immunity boosters and symptomatic treatment based on natural bioactive compounds are also an option. The 3-chymotrypsin-like protease (3CLpro) crystal structure, the main proteolytic enzyme of SARS-CoV-2, has been unraveled, allowing the development of effective protease inhibitors via in silico and biological studies. In COVID-19 infected patients, the loss of lung function, and mortality are reported to be linked to several inflammatory mediators and cytokines. In this context, the approach of introducing immunomodulatory agents may be considered a dual lifesaving strategy in combination with antiviral drugs. This study aims to provide immunomodulatory natural products exhibiting potential protease inhibitory activities. Selected groups of alkaloids of different classes and two prenylated phenylpropanoids from the Brazilian green propolis were in silico screened for their ability to inhibit COVID-19 3CLpro protease. Results showed that compounds exhibited binding energy scores with values ranging from -6.96 to -3.70 compared to the reference synthetic protease inhibitor O6K with a binding energy score of -7.57. O6K binding energy was found comparable with lead phytochemicals in our study, while their toxicity and drug-likeness criteria are better than that of O6K. The activities of these molecules are mainly ascribed to their ability to form hydrogen bonding with 3CLpro crucial amino acid residues of the catalytic site. In addition, the molecular dynamics simulations further showed that some of these compounds formed stable complexes as evidenced by the occupancy fraction measurements. The study suggested that the major immunomodulators 3β, 20α-diacetamido-5α-pregnane, (20S)-(benzamido)-3β-(N,N-dimethyamino)-pregnane, and baccharin are 3CLpro inhibitors. Biological screenings of these phytochemicals will be valuable to experimentally validate and consolidate the results of this study before a rigid conclusion is reached, which may pave the way for the development of efficient modulatory bioactive compounds with dual bioactions in COVID-19 intervention.

PMID:37116054 | DOI:10.1080/07391102.2023.2204973

Front Biosci (Landmark Ed). 2023 Apr 24;28(4):77. doi: 10.31083/j.fbl2804077.

ABSTRACT

Tumors of the Central Nervous System (CNS) represent the leading cause of cancer-related deaths in children. Current treatment options are not curative for most malignant histologies, and intense preclinical and clinical research is needed to develop more effective therapeutic interventions against these tumors, most of which meet the FDA definition for orphan diseases. Increased attention is being paid to the repositioning of already-approved drugs for new anticancer indications as a fast-tracking strategy for identifying new and more effective therapies. Two pediatric CNS tumors, posterior fossa ependymoma (EPN-PF) type A and diffuse midline glioma (DMG) H3K27-altered, share loss of H3K27 trimethylation as a common epigenetic hallmark and display early onset and poor prognosis. These features suggest a potentially common druggable vulnerability. Successful treatment of these CNS tumors raises several challenges due to the location of tumors, chemoresistance, drug blood-brain barrier penetration, and the likelihood of adverse side effects. Recently, increasing evidence demonstrates intense interactions between tumor cell subpopulations and supportive tumor microenvironments (TMEs) including nerve, metabolic, and inflammatory TMEs. These findings suggest the use of drugs, and/or multi-drug combinations, that attack both tumor cells and the TME simultaneously. In this work, we present an overview of the existing evidence concerning the most preclinically validated noncancer drugs with antineoplastic activity. These drugs belong to four pharmacotherapeutic classes: antiparasitic, neuroactive, metabolic, and anti-inflammatory. Preclinical evidence and undergoing clinical trials in patients with brain tumors, with special emphasis on pediatric EPN-PF and DMG, are summarized and critically discussed.

PMID:37114548 | DOI:10.31083/j.fbl2804077

Front Pharmacol. 2023 Apr 11;14:1099425. doi: 10.3389/fphar.2023.1099425. eCollection 2023.

ABSTRACT

Introduction: Niclosamide (Nc) is an FDA-approved anthelmintic drug that was recently identified in a drug repurposing screening to possess antiviral activity against SARS-CoV-2. However, due to the low solubility and permeability of Nc, its in vivo efficacy was limited by its poor oral absorption. Method: The current study evaluated a novel prodrug of Nc (PDN; NCATS-SM4705) in improving in vivo exposure of Nc and predicted pharmacokinetic profiles of PDN and Nc across different species. ADME properties of the prodrug were determined in humans, hamsters, and mice, while the pharmacokinetics (PK) of PDN were obtained in mice and hamsters. Concentrations of PDN and Nc in plasma and tissue homogenates were measured by UPLC-MS/MS. A physiologically based pharmacokinetic (PBPK) model was developed based on physicochemical properties, pharmacokinetic and tissue distribution data in mice, validated by the PK profiles in hamsters and applied to predict pharmacokinetic profiles in humans. Results: Following intravenous and oral administration of PDN in mice, the total plasma clearance (CLp) and volume of distribution at steady-state (Vdss) were 0.061-0.063 L/h and 0.28-0.31 L, respectively. PDN was converted to Nc in both liver and blood, improving the systemic exposure of Nc in mice and hamsters after oral administration. The PBPK model developed for PDN and in vivo formed Nc could adequately simulate plasma and tissue concentration-time profiles in mice and plasma profiles in hamsters. The predicted human CLp/F and Vdss/F after an oral dose were 2.1 L/h/kg and 15 L/kg for the prodrug respectively. The predicted Nc concentrations in human plasma and lung suggest that a TID dose of 300 mg PDN would provide Nc lung concentrations at 8- to 60-fold higher than in vitro IC50 against SARS-CoV-2 reported in cell assays. Conclusion: In conclusion, the novel prodrug PDN can be efficiently converted to Nc in vivo and improves the systemic exposure of Nc in mice after oral administration. The developed PBPK model adequately depicts the mouse and hamster pharmacokinetic and tissue distribution profiles and highlights its potential application in the prediction of human pharmacokinetic profiles.

PMID:37113753 | PMC:PMC10126473 | DOI:10.3389/fphar.2023.1099425

Viruses. 2023 Apr 11;15(4):948. doi: 10.3390/v15040948.

ABSTRACT

The Bunyavirales order is a large group of RNA viruses that includes important pathogens for humans, animals and plants. With high-throughput screening of clinically tested compounds we have looked for potential inhibitors of the endonuclease domain of a bunyavirus RNA polymerase. From a list of fifteen top candidates, five compounds were selected and their antiviral properties studied with Bunyamwera virus (BUNV), a prototypic bunyavirus widely used for studies about the biology of this group of viruses and to test antivirals. Four compounds (silibinin A, myricetin, L-phenylalanine and p-aminohippuric acid) showed no antiviral activity in BUNV-infected Vero cells. On the contrary, acetylsalicylic acid (ASA) efficiently inhibited BUNV infection with a half maximal inhibitory concentration (IC50) of 2.02 mM. In cell culture supernatants, ASA reduced viral titer up to three logarithmic units. A significant dose-dependent reduction of the expression levels of Gc and N viral proteins was also measured. Immunofluorescence and confocal microscopy showed that ASA protects the Golgi complex from the characteristic BUNV-induced fragmentation in Vero cells. Electron microscopy showed that ASA inhibits the assembly of Golgi-associated BUNV spherules that are the replication organelles of bunyaviruses. As a consequence, the assembly of new viral particles is also significantly reduced. Considering its availability and low cost, the potential usability of ASA to treat bunyavirus infections deserves further investigation.

PMID:37112928 | DOI:10.3390/v15040948

Pharmaceutics. 2023 Mar 31;15(4):1117. doi: 10.3390/pharmaceutics15041117.

ABSTRACT

Bladder cancer (BC) is a heterogeneous disease that a tumor develops in the bladder lining and in some cases, the bladder muscle. Chemotherapy and immunotherapy are commonly used to treat bladder cancer. However, chemotherapy can cause burning and irritation in the bladder while BCG immunotherapy, which is the main type of intravesical immunotherapy for bladder cancer, can also cause burning in the bladder and flu-like symptoms. Thus, drugs originating from natural products have attracted much attention due to the reports that they have anti-cancer properties with low adverse effects. In this study, eighty-seven papers that dealt with natural products preventing or treating bladder cancer were reviewed. The studies were classified into the following mechanism: 71 papers on cell death, 5 papers on anti-metastasis, 3 papers on anti-angiogenesis, 1 paper on anti-resistance, and 7 papers on clinical trials. Most of the natural products that induced apoptosis up-regulated proteins such as caspase-3 and caspase-9. Regarding anti-metastasis, MMP-2 and MMP-9 are regulated frequently. Regarding anti-angiogenesis, HIF-1α and VEGF-A are down-regulated frequently. Nevertheless, the number of papers regarding anti-resistance and clinical trial are too few, so more studies are needed. In conclusion, this database will be useful for future in vivo studies of the anti-bladder cancer effect of natural products, in the process of selecting materials used for the experiment.

PMID:37111603 | DOI:10.3390/pharmaceutics15041117