Cell Mol Life Sci. 2023 Apr 25;80(5):132. doi: 10.1007/s00018-023-04760-5.

ABSTRACT

We sought to investigate the utility of ebastine (EBA), a second-generation antihistamine with potent anti-metastatic properties, in the context of breast cancer stem cell (BCSC)-suppression in triple-negative breast cancer (TNBC). EBA binds to the tyrosine kinase domain of focal adhesion kinase (FAK), blocking phosphorylation at the Y397 and Y576/577 residues. FAK-mediated JAK2/STAT3 and MEK/ERK signaling was attenuated after EBA challenge in vitro and in vivo. EBA treatment induced apoptosis and a sharp decline in the expression of the BCSC markers ALDH1, CD44 and CD49f, suggesting that EBA targets BCSC-like cell populations while reducing tumor bulk. EBA administration significantly impeded BCSC-enriched tumor burden, angiogenesis and distant metastasis while reducing MMP-2/-9 levels in circulating blood in vivo. Our findings suggest that EBA may represent an effective therapeutic for the simultaneous targeting of JAK2/STAT3 and MEK/ERK for the treatment of molecularly heterogeneous TNBC with divergent profiles. Further investigation of EBA as an anti-metastatic agent for the treatment of TNBC is warranted.

PMID:37185776 | DOI:10.1007/s00018-023-04760-5

Curr Issues Mol Biol. 2023 Apr 11;45(4):3333-3346. doi: 10.3390/cimb45040218.

ABSTRACT

Cancer is a set of complex diseases, being one of the leading causes of death worldwide. Despite a lot of research on the molecular pathways and effective treatments, there are still huge gaps. Indeed, the development of new anti-cancer drugs is a complex process. To face this problem, drug repurposing is being increasingly applied. This approach aims to identify new indications for already approved drugs. In this regard, statins (clinically used for reducing cholesterol levels) are reported to induce anti-cancer effects, particularly by inducing apoptosis and altering the tumor microenvironment. Atorvastatin is a type of statin with several potentialities as an anti-cancer agent, supported by several studies. Our study aimed to explore the effect of this drug in SH-SY5Y human neuroblastoma cells. Additionally, we also aimed to understand how this drug acts under hypoxia and the inhibition of hypoxia-inducible factor-1 (HIF-1). For that purpose, we assessed cellular viability/morphology after exposure to different concentrations of atorvastatin, with or without chemically induced hypoxia with chloride cobalt (CoCl2) and with or without echinomycin (HIF-1α inhibitor). Our results supported the cytotoxic effects of atorvastatin. Additionally, we also revealed that besides these effects, under hypoxia, this drug induced proliferation of the neuroblastoma cells, supporting the importance of different stimuli and environment on the effect of drugs on cancer cells.

PMID:37185742 | DOI:10.3390/cimb45040218

Drug Deliv Transl Res. 2023 May 15. doi: 10.1007/s13346-023-01353-4. Online ahead of print.

ABSTRACT

Oral candidiasis (OC) is an opportunistic fungal infection, common amongst the elderly and the immunocompromised. Unfortunately, the therapeutic efficacy of common antifungals is imperiled by the rise of antifungal drug resistance. An alternative promising therapeutic option possibly contributing to antifungal therapy is drug repurposing. Herein, we aimed to employ novel pharmaceutical drug delivery for enhancing the emerging antifungal potential of the hypocholesterolemic drug atorvastatin (ATV). ATV-propylene-glycol-liposomes (ATV/PG-Lip) were prepared then integrated in 3D-printed (3DP) mucoadhesive films comprising chitosan, polyvinyl-alcohol and hydroxypropyl methylcellulose, as an innovative blend, for the management of OC. ATV/PG-Lip demonstrated good colloidal properties of particle size (223.3 ± 2.1 nm), PDI (0.12 ± 0.001) and zeta potential (-18.2 ± 0.3 mV) with high entrapment efficiency (81.15 ± 1.88%) and sustained drug release. Also, ATV/PG-Lip showed acceptable three-month colloidal stability and in vitro cytocompatibility on human gingival fibroblasts. The developed 3DP-films exhibited controlled ATV release (79.4 ± 1.4% over 24 h), reasonable swelling and mucoadhesion (2388.4 ± 18.4 dyne/cm2). In vitro antifungal activity of ATV/PG-Lip was confirmed against fluconazole-resistant Candida albicans via minimum inhibitory concentration determination, time-dependent antifungal activity, agar diffusion and scanning electron microscopy. Further, ATV/PG-Lip@3DP-film exceeded ATV@3DP-film in amelioration of infection and associated inflammation in an in vivo oral candidiasis rabbit model. Accordingly, the results confirm the superiority of the fabricated ATV/PG-Lip@3DP-film for the management of oral candidiasis and tackling antifungal resistance.

PMID:37184748 | DOI:10.1007/s13346-023-01353-4

CNS Neurosci Ther. 2023 May 14. doi: 10.1111/cns.14260. Online ahead of print.

ABSTRACT

AIMS: Alzheimer's disease (AD) and type 2 diabetes (T2D) are two of the most common diseases in elderly population and they have a high rate of comorbidity. Study has revealed that T2D is a major risk factor of AD, and thus exploring therapeutic approaches that can target both diseases has drawn much interest in recent years. In this study, we tried to explore drugs that could be potentially used to prevent or treat both AD and T2D via a drug repositioning approach.

METHODS: We first searched the known drugs that may be effective to T2D treatment based on the network distance between the T2D-associated genes and drugs deposited in the DrugBank database. Then, via molecular docking, we further screened these drugs by examining their interaction with islet amyloid polypeptide (IAPP) and Aβ42 peptide, the key components involved in the pathogenesis of T2D or AD. Finally, the binding between the selected drug candidates and the target proteins was verified by molecular dynamics (MD) simulation; and the potential function of the drug candidates and the corresponding targets were analyzed.

RESULTS: From multiple resources, 734 T2D-associated genes were collected, and a list of 1109 drug candidates for T2D was obtained. We found that hypericin had the lowest binding energy and the most stable interaction with either IAPP or Aβ42 peptide. In addition, we also found that the target genes regulated by hypericin were differentially expressed in the tissues related to the two diseases.

CONCLUSION: Our results show that hypericin may be able to bind with IAPP and Aβ42 stably and prevent their accumulation, and thus could be a promising drug candidate for treating the comorbidity of AD and T2D.

PMID:37183545 | DOI:10.1111/cns.14260

Ther Adv Rare Dis. 2021 Aug 16;2:26330040211039518. doi: 10.1177/26330040211039518. eCollection 2021 Jan-Dec.

ABSTRACT

Wolfram Syndrome (WS) is an ultra-rare, progressive neurodegenerative disease characterized by early-onset diabetes mellitus and irreversible loss of vision, secondary to optic nerve degeneration. Visual loss in WS is an important cause of registrable blindness in children and young adults and the pathological hallmark is the preferential loss of retinal ganglion cells within the inner retina. In addition to optic atrophy, affected individuals frequently develop variable combinations of neurological, endocrinological, and psychiatric complications. The majority of patients carry recessive mutations in the WFS1 (4p16.1) gene that encodes for a multimeric transmembrane protein, wolframin, embedded within the endoplasmic reticulum (ER). An increasingly recognised subgroup of patients harbor dominant WFS1 mutations that usually cause a milder phenotype, which can be limited to optic atrophy. Wolframin is a ubiquitous protein with high levels of expression in retinal, neuronal, and muscle tissues. It is a multifunctional protein that regulates a host of cellular functions, in particular the dynamic interaction with mitochondria at mitochondria-associated membranes. Wolframin has been implicated in several crucial cellular signaling pathways, including insulin signaling, calcium homeostasis, and the regulation of apoptosis and the ER stress response. There is currently no cure for WS; management remains largely supportive. This review will cover the clinical, genetic, and pathophysiological features of WS, with a specific focus on disease models and the molecular pathways that could serve as potential therapeutic targets. The current landscape of therapeutic options will also be discussed in the context of the latest evidence, including the pipeline for repurposed drugs and gene therapy.

PLAIN LANGUAGE SUMMARY: Wolfram syndrome - disease mechanisms and treatment options Wolfram syndrome (WS) is an ultra-rare genetic disease that causes diabetes mellitus and progressive loss of vision from early childhood. Vision is affected in WS because of damage to a specialized type of cells in the retina, known as retinal ganglion cells (RGCs), which converge at the back of the eye to form the optic nerve. The optic nerve is the fast-conducting cable that transmits visual information from the eye to the vision processing centers within the brain. As RGCs are lost, the optic nerve degenerates and it becomes pale in appearance (optic atrophy). Although diabetes mellitus and optic atrophy are the main features of WS, some patients can develop more severe problems because the brain and other organs, such as the kidneys and the bladder, are also affected. The majority of patients with WS carry spelling mistakes (mutations) in the WFS1 gene, which is located on the short arm of chromosome 4 (4p16.1). This gene is highly expressed in the eye and in the brain, and it encodes for a protein located within a compartment of the cell known as the endoplasmic reticulum. For reasons that still remain unclear, WFS1 mutations preferentially affect RGCs, accounting for the prominent visual loss in this genetic disorder. There is currently no effective treatment to halt or slow disease progression and management remains supportive, including the provision of visual aids and occupational rehabilitation. Research into WS has been limited by its relative rarity and the inability to get access to eye and brain tissues from affected patients. However, major advances in our understanding of this disease have been made recently by making use of more accessible cells from patients, such as skin cells (fibroblasts), or animal models, such as mice and zebrafish. This review summarizes the mechanisms by which WFS1 mutations affect cells, impairing their function and eventually leading to their premature loss. The possible treatment strategies to block these pathways are also discussed, with a particular focus on drug repurposing (i.e., using drugs that are already approved for other diseases) and gene therapy (i.e., replacing or repairing the defective WFS1 gene).

PMID:37181110 | PMC:PMC10032446 | DOI:10.1177/26330040211039518

Front Pharmacol. 2023 Apr 26;14:1113007. doi: 10.3389/fphar.2023.1113007. eCollection 2023.

ABSTRACT

The two most common reasons for attrition in therapeutic clinical trials are efficacy and safety. We integrated heterogeneous data to create a human interactome network to comprehensively describe drug behavior in biological systems, with the goal of accurate therapeutic candidate generation. The Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multiscale therapeutic discovery, repurposing, and design was enhanced by integrating drug side effects, protein pathways, protein-protein interactions, protein-disease associations, and the Gene Ontology, and complemented with its existing drug/compound, protein, and indication libraries. These integrated networks were reduced to a "multiscale interactomic signature" for each compound that describe its functional behavior as vectors of real values. These signatures are then used for relating compounds to each other with the hypothesis that similar signatures yield similar behavior. Our results indicated that there is significant biological information captured within our networks (particularly via side effects) which enhance the performance of our platform, as evaluated by performing all-against-all leave-one-out drug-indication association benchmarking as well as generating novel drug candidates for colon cancer and migraine disorders corroborated via literature search. Further, drug impacts on pathways derived from computed compound-protein interaction scores served as the features for a random forest machine learning model trained to predict drug-indication associations, with applications to mental disorders and cancer metastasis highlighted. This interactomic pipeline highlights the ability of Computational Analysis of Novel Drug Opportunities to accurately relate drugs in a multitarget and multiscale context, particularly for generating putative drug candidates using the information gleaned from indirect data such as side effect profiles and protein pathway information.

PMID:37180722 | PMC:PMC10169664 | DOI:10.3389/fphar.2023.1113007

Front Cell Infect Microbiol. 2023 Apr 27;13:1132538. doi: 10.3389/fcimb.2023.1132538. eCollection 2023.

ABSTRACT

The chikungunya virus (CHIKV) is an alphavirus transmitted by Aedes mosquitoes. There are no licenced antivirals or vaccines for treatment or prevention. Drug repurposing approach has emerged as a novel concept to find alternative uses of therapeutics to battle pathogens. In the present study, anti CHIKV activity of fourteen FDA-approved drugs was investigated by in vitro and in silico approaches. Focus-forming unit assay, immunofluorescence test, and quantitative RT-PCR assay were used to assess the in vitro inhibitory effect of these drugs against CHIKV in Vero CCL-81 cells. The findings showed that nine compounds, viz., temsirolimus, 2-fluoroadenine, doxorubicin, felbinac, emetine, lomibuvir, enalaprilat, metyrapone and resveratrol exhibit anti chikungunya activity. Furthermore, in silico molecular docking studies performed by targeting CHIKV structural and non-structural proteins revealed that these drugs can bind to structural protein targets such as envelope protein, and capsid, and non-structural proteins NSP2, NSP3 and NSP4 (RdRp). Findings from in vitro and in silico studies reveal that these drugs can suppress the infection and replication of CHIKV and further in vivo studies followed by clinical trials are warranted.

PMID:37180434 | PMC:PMC10174255 | DOI:10.3389/fcimb.2023.1132538

Autophagy. 2023 May 14:1-3. doi: 10.1080/15548627.2023.2210995. Online ahead of print.

ABSTRACT

We have employed artificial intelligence to streamline the small molecule drug screening pipeline and identified the cholesterol-reducing compound probucol in the process. Probucol augmented mitophagy and prevented loss of dopaminergic neurons in flies and zebrafish challenged with mitochondrial toxins. Further dissection of the mechanism of action led to the identification of ABCA1, the target of probucol, as a mitophagy modulator. Probucol treatment regulates lipid droplet dynamics during mitophagy and ABCA1 is required for these effects. Here we will summarize the combination of in silico and cell-based screening that led us to identify and characterize probucol as a compound that enhances mitophagy and include thoughts about future directions for the topics explored in our study.Abbreviations: ABCA1: ATP binding cassette transporter protein 1; ATP: Adenosine tri-phosphate; CCCP: carbonyl cyanide m-chlorophenylhydrazone; DsRed: Discosoma red; FDA: Food and drug administration; GFP: Green fluorescent protein; LAMP: lysosome-associated membrane glycoproteins; LD: Lipid droplet; PD: Parkinson's disease; PINK: PTEN-induced kinase.

PMID:37179524 | DOI:10.1080/15548627.2023.2210995

Comput Biol Med. 2023 May 2;160:106921. doi: 10.1016/j.compbiomed.2023.106921. Online ahead of print.

ABSTRACT

Opioid use disorder (OUD) is a chronic and relapsing condition that involves the continued and compulsive use of opioids despite harmful consequences. The development of medications with improved efficacy and safety profiles for OUD treatment is urgently needed. Drug repurposing is a promising option for drug discovery due to its reduced cost and expedited approval procedures. Computational approaches based on machine learning enable the rapid screening of DrugBank compounds, identifying those with the potential to be repurposed for OUD treatment. We collected inhibitor data for four major opioid receptors and used advanced machine learning predictors of binding affinity that fuse the gradient boosting decision tree algorithm with two natural language processing (NLP)-based molecular fingerprints and one traditional 2D fingerprint. Using these predictors, we systematically analyzed the binding affinities of DrugBank compounds on four opioid receptors. Based on our machine learning predictions, we were able to discriminate DrugBank compounds with various binding affinity thresholds and selectivities for different receptors. The prediction results were further analyzed for ADMET (absorption, distribution, metabolism, excretion, and toxicity), which provided guidance on repurposing DrugBank compounds for the inhibition of selected opioid receptors. The pharmacological effects of these compounds for OUD treatment need to be tested in further experimental studies and clinical trials. Our machine learning studies provide a valuable platform for drug discovery in the context of OUD treatment.

PMID:37178605 | DOI:10.1016/j.compbiomed.2023.106921

Int J Mol Sci. 2023 May 5;24(9):8326. doi: 10.3390/ijms24098326.

ABSTRACT

The accurate prediction of drug-target binding affinity (DTA) is an essential step in drug discovery and drug repositioning. Although deep learning methods have been widely adopted for DTA prediction, the complexity of extracting drug and target protein features hampers the accuracy of these predictions. In this study, we propose a novel model for DTA prediction named MSGNN-DTA, which leverages a fused multi-scale topological feature approach based on graph neural networks (GNNs). To address the challenge of accurately extracting drug and target protein features, we introduce a gated skip-connection mechanism during the feature learning process to fuse multi-scale topological features, resulting in information-rich representations of drugs and proteins. Our approach constructs drug atom graphs, motif graphs, and weighted protein graphs to fully extract topological information and provide a comprehensive understanding of underlying molecular interactions from multiple perspectives. Experimental results on two benchmark datasets demonstrate that MSGNN-DTA outperforms the state-of-the-art models in all evaluation metrics, showcasing the effectiveness of the proposed approach. Moreover, the study conducts a case study based on already FDA-approved drugs in the DrugBank dataset to highlight the potential of the MSGNN-DTA framework in identifying drug candidates for specific targets, which could accelerate the process of virtual screening and drug repositioning.

PMID:37176031 | DOI:10.3390/ijms24098326

Int J Mol Sci. 2023 May 3;24(9):8164. doi: 10.3390/ijms24098164.

ABSTRACT

The β-secretase-1 enzyme (BACE-1) performs a key role in the production of beta-Amyloid protein (Aβ), which is associated with the development of Alzheimer's disease (AD). The inhibition of BACE-1 has been an important pharmacological strategy in the treatment of this neurodegenerative disease. This study aims to identify new potential candidates for the treatment of Alzheimer's with the help of in silico studies, such as molecular docking and ADME prediction, from a broad list of candidates provided by the DrugBank database. From this analysis, 1145 drugs capable of interacting with the enzyme with a higher coupling energy than Verubecestat were obtained, subsequently only 83 presented higher coupling energy than EJ7. Applying the oral route of administration as inclusion criteria, only 41 candidates met this requirement; however, 6 of them are associated with diagnostic tests and not treatment, so 33 candidates were obtained. Finally, five candidates were identified as possible BACE-1 inhibitors drugs: Fluphenazine, Naratriptan, Bazedoxifene, Frovatriptan, and Raloxifene. These candidates exhibit pharmacophore-specific features, including the indole or thioindole group, and interactions with key amino acids in BACE-1. Overall, this study provides insights into the potential use of in silico methods for drug repurposing and identification of new candidates for the treatment of Alzheimer's disease, especially those targeting BACE-1.

PMID:37175873 | DOI:10.3390/ijms24098164

Nat Commun. 2023 May 12;14(1):2743. doi: 10.1038/s41467-023-38389-6.

ABSTRACT

Genome-wide association studies (GWAS) have mapped thousands of susceptibility loci associated with immune-mediated diseases. To assess the extent of the genetic sharing across nine immune-mediated diseases we apply genomic structural equation modelling to GWAS data from European populations. We identify three disease groups: gastrointestinal tract diseases, rheumatic and systemic diseases, and allergic diseases. Although loci associated with the disease groups are highly specific, they converge on perturbing the same pathways. Finally, we test for colocalization between loci and single-cell eQTLs derived from peripheral blood mononuclear cells. We identify the causal route by which 46 loci predispose to three disease groups and find evidence for eight genes being candidates for drug repurposing. Taken together, here we show that different constellations of diseases have distinct patterns of genetic associations, but that associated loci converge on perturbing different nodes in T cell activation and signalling pathways.

PMID:37173304 | DOI:10.1038/s41467-023-38389-6

J Gynecol Oncol. 2023 Apr 24. doi: 10.3802/jgo.2023.34.e58. Online ahead of print.

ABSTRACT

OBJECTIVE: Fenbendazole (FZ) has potential anti-cancer effects, but its poor water solubility limits its use for cancer therapy. In this study, we investigated the anti-cancer effect of FZ with different drug delivery methods on epithelial ovarian cancer (EOC) in both in vitro and in vivo models.

METHODS: EOC cell lines were treated with FZ and cell proliferation was assessed. The effect of FZ on tumor growth in cell line xenograft mouse model of EOC was examined according to the delivery route, including oral and intraperitoneal administration. To improve the systemic delivery of FZ by converting fat-soluble drugs to hydrophilic, we prepared FZ-encapsulated poly(D,L-lactide-co-glycolide) acid (PLGA) nanoparticles (FZ-PLGA-NPs). We investigated the preclinical efficacy of FZ-PLGA-NPs by analyzing cell proliferation, apoptosis, and in vivo models including cell lines and patient-derived xenograft (PDX) of EOC.

RESULTS: FZ significantly decreased cell proliferation of both chemosensitive and chemoresistant EOC cells. However, in cell line xenograft mouse models, there was no effect of oral FZ treatment on tumor reduction. When administered intraperitoneally, FZ was not absorbed but aggregated in the intraperitoneal space. We synthesized FZ-PLGA-NPs to obtain water solubility and enhance drug absorption. FZ-PLGA-NPs significantly decreased cell proliferation in EOC cell lines. Intravenous injection of FZ-PLGA-NP in xenograft mouse models with HeyA8 and HeyA8-MDR significantly reduced tumor weight compared to the control group. FZ-PLGA-NPs showed anti-cancer effects in PDX model as well.

CONCLUSION: FZ-incorporated PLGA nanoparticles exerted significant anti-cancer effects in EOC cells and xenograft models including PDX. These results warrant further investigation in clinical trials.

PMID:37170725 | DOI:10.3802/jgo.2023.34.e58

Antiviral Res. 2023 May 9:105620. doi: 10.1016/j.antiviral.2023.105620. Online ahead of print.

ABSTRACT

Diseases caused by new viruses cost thousands if not millions of human lives and trillions of dollars. We have identified, collected, curated, and integrated all chemogenomics data from ChEMBL for 13 emerging viruses that hold the greatest potential threat to global human health. By identifying and solving several challenges related to data annotation accuracy, we developed a highly curated and thoroughly annotated database of compounds tested in both phenotypic and target-based assays for these viruses that we dubbed SMACC (Small Molecule Antiviral Compound Collection). The pilot version of the SMACC database contains over 32,500 entries for 13 viruses. By analyzing data in SMACC, we have identified ∼50 compounds with polyviral inhibition profile, mostly covering flavi- and coronaviruses. The SMACC database may serve as a reference for virologists and medicinal chemists working on the development of novel BSA agents in preparation for future viral outbreaks. SMACC is publicly available at https://smacc.mml.unc.edu.

PMID:37169224 | DOI:10.1016/j.antiviral.2023.105620

Circ Res. 2023 May 12;132(10):1374-1386. doi: 10.1161/CIRCRESAHA.122.321879. Epub 2023 May 11.

ABSTRACT

COVID-19 is an infectious disease caused by SARS-CoV-2 leading to the ongoing global pandemic. Infected patients developed a range of respiratory symptoms, including respiratory failure, as well as other extrapulmonary complications. Multiple comorbidities, including hypertension, diabetes, cardiovascular diseases, and chronic kidney diseases, are associated with the severity and increased mortality of COVID-19. SARS-CoV-2 infection also causes a range of cardiovascular complications, including myocarditis, myocardial injury, heart failure, arrhythmias, acute coronary syndrome, and venous thromboembolism. Although a variety of methods have been developed and many clinical trials have been launched for drug repositioning for COVID-19, treatments that consider cardiovascular manifestations and cardiovascular disease comorbidities specifically are limited. In this review, we summarize recent advances in drug repositioning for COVID-19, including experimental drug repositioning, high-throughput drug screening, omics data-based, and network medicine-based computational drug repositioning, with particular attention on those drug treatments that consider cardiovascular manifestations of COVID-19. We discuss prospective opportunities and potential methods for repurposing drugs to treat cardiovascular complications of COVID-19.

PMID:37167362 | DOI:10.1161/CIRCRESAHA.122.321879

Drug Dev Res. 2023 May 11. doi: 10.1002/ddr.22075. Online ahead of print.

ABSTRACT

Facing the sudden outbreak of coronavirus disease 2019 (COVID-19), it is extremely urgent to develop effective antiviral drugs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Drug repurposing is a promising strategy for the treatment of COVID-19. To identify the precise target protein of marketed medicines, we initiate a chemical biological program to identify precise target of potential antivirus drugs. In this study, two types of recombinant human coronavirus SARS-CoV-2 RdRp protein capturing probes with various photoaffinity labeling units were designed and synthesized based on the structure of FDA-approved drugs stavudine, remdesivir, acyclovir, and aladenosine. Fortunately, it was found that one novel photoaffinity probe, RD-1, could diaplayed good affinity with SARS-CoV-2 RdRp around the residue ARG_553. In addition, RD-1 probe also exhibited potent inhibitory activity against 3CLpro protease. Taken together, our findings will elucidate the structural basis for the efficacy of marketed drugs, and explore a rapid and efficient strategy of drug repurposing based on the identification of new targets. Moreover, these results could also provide a scientific basis for the clinical application of marketed drugs.

PMID:37165797 | DOI:10.1002/ddr.22075

Mini Rev Med Chem. 2023 May 9. doi: 10.2174/1389557523666230509123036. Online ahead of print.

ABSTRACT

Despite the tremendous progress that has occurred in recent years in cell biology and oncology, in chemical, physical and computer sciences, the disease cancer has continued as the major cause of death globally. Research organizations, academic institutions and pharmaceutical companies invest huge amounts of money in the discovery and development of new anticancer drugs. Though much effort is continuing and whatever available approaches are being attempted, the success of bringing one effective drug into the market has been uncertain. To overcome problems associated with drug discovery, several approaches are being attempted. One such approach has been the use of known, approved and marketed drugs to screen these for new indications, which have gained considerable interest. This approach is known in different terms as "drug repositioning or drug repurposing." Drug repositioning refers to the structure modification of the active molecule by synthesis, in vitro/ in vivo screening and in silico computational applications where macromolecular structure-based drug design (SBDD) is employed. In this perspective, we aimed to focus on the application of repositioning or repurposing of essential drug moieties present in drugs that are already used for the treatment of some diseases such as diabetes, human immunodeficiency virus (HIV) infection and inflammation as anticancer agents. This review thus covers the available literature where molecular modeling of drugs/enzyme inhibitors through SBDD is reported for antidiabetics, anti-HIV and inflammatory diseases, which are structurally modified and screened for anticancer activity using respective cell lines.

PMID:37165589 | DOI:10.2174/1389557523666230509123036

Bioorg Chem. 2023 May 6;137:106585. doi: 10.1016/j.bioorg.2023.106585. Online ahead of print.

ABSTRACT

Multidrug-resistant microorganisms have become a global health problem, prompting research into new antimicrobials. Drug repurposing is a new technique in drug discovery used to improve drug development success. As a well-studied medication with a sulfonamide moiety, furosemide was chosen to study its antimicrobial effect on different microbial strains. In addition, a new family of furosemide analogs was investigated for their antimicrobial efficacy. According to the obtained results, the majority of the examined molecules exhibited potential antimicrobial activity. Compounds 3b and 4a had the best anti-MRSA results, with an MIC = 7.81 µg/mL. They also demonstrated potent anti-gram-negative activity against E. coli (MIC = 1.95 µg/mL and 3.91 µg/mL, respectively). A time-killing kinetics study against E. coli and MRSA showed bactericidal actions of 3b and 4a within 120-150 min. Moreover, an anti-PBP activity and an in vitro cytotoxicity evaluation were performed. Furosemide decreased the PBP2a levels in MRSA by 21.5% compared to the control. However, the furosemide analogs 3b and 4a demonstrated superior anti-PBP activity (55.9 and 57.1 % reduction in the expression of PBP2a, respectively). In addition, compound 4a was nearly nontoxic to normal WI-38 cells (IC50 = 248.60 μg /mL) indicating its high safety profile. Finally, the ability of furosemide and compounds 3b and 4a to bind to the target PBP2a enzyme has also been supported by molecular docking research.

PMID:37163813 | DOI:10.1016/j.bioorg.2023.106585

Adv Healthc Mater. 2023 May 10:e2300591. doi: 10.1002/adhm.202300591. Online ahead of print.

ABSTRACT

To address the challenge of drug resistance and limited treatment options for recurrent gliomas with IDH1 mutations, a highly miniaturized screening of 2208 FDA-approved drugs is conducted using a high-throughput droplet microarray (DMA) platform. Two patient-derived temozolomide-resistant tumorspheres harboring endogenous IDH1 mutations (IDH1mut ) are utilized. Screening identifies over 20 drugs, including verteporfin (VP), that significantly affected tumorsphere formation and viability. Proteomics analysis reveals that nuclear pore complex may be a potential VP target, suggesting a new mechanism of action independent of its known effects on YAP1. Knockdown experiments exclude YAP1 as a drug target in tumorspheres. Pathway analysis shows that NUP107 is a potential upstream regulator associated with VP response. Analysis of publicly available genomics datasets shows a significant correlation between high NUP107 expression and decreased survival in IDH1mut astrocytoma, suggesting NUP107 could be a potential biomarker for VP response. This study demonstrates a miniaturized approach for cost-effective drug repurposing using 3D glioma models and identifies nuclear pore complex as a potential target for drug development. The findings provide preclinical evidence to support in vivo and clinical studies of VP and other identified compounds to treat IDH1mut gliomas, which may ultimately improve clinical outcomes for patients with this challenging disease. This article is protected by copyright. All rights reserved.

PMID:37162029 | DOI:10.1002/adhm.202300591

Int J Biol Macromol. 2023 May 7:124749. doi: 10.1016/j.ijbiomac.2023.124749. Online ahead of print.

ABSTRACT

Cyclophosphamide (CP) is one of the most widely used anticancer drugs for various malignancies. However, its long-term use leads to ALDH1A1-mediated inactivation and subsequent resistance which necessitates the development of potential ALDH1A1 inhibitors. Currently, ALDH1A1 inhibitors from different chemical classes have been reported, but these failed to reach the market due to safety and efficacy problems. Developing a new treatment from the ground requires a huge amount of time, effort, and money, therefore it is worthwhile to improve CP efficacy by proposing better adjuvants as ALDH1A1 inhibitors. Herein, the database constituting the FDA-approved drugs with well-established safety and toxicity profiles was screened through already reported machine learning models by our research group. This model is validated for discriminating the ALDH1A1 inhibitors and non-inhibitors. Virtual screening protocol (VS) from this model identified four FDA-approved drugs, raloxifene, bazedoxifene, avanafil, and betrixaban as selective ALDH1A1 inhibitors. The molecular docking, dynamics, and water swap analysis also suggested these drugs to be promising ALDH1A1 inhibitors which were further validated for their CP resistance reversal potential by in-vitro analysis. The in-vitro enzymatic assay results indicated that raloxifene and bazedoxifene selectively inhibited the ALDH1A1 enzyme with IC50 values of 2.35 and 4.41 μM respectively, whereas IC50 values of both the drugs against ALDH2 and ALDH3A1 was >100 μM. Additional in-vitro stu = dies with well-reported ALDH1A1 overexpressing A549 and MIA paCa-2 cell lines suggested that mafosfamide sensitivity was further ameliorated by the combination of both raloxifene and bazedoxifene. Collectively, in-silico and in-vitro studies indicate raloxifene and bazedoxifene act as promising adjuvants with CP that may improve the quality of treatment for cancer patients with minimal toxicities.

PMID:37160174 | DOI:10.1016/j.ijbiomac.2023.124749