Pharmaceutics. 2021 Sep 24;13(10):1548. doi: 10.3390/pharmaceutics13101548.

ABSTRACT

The wet type of age-related macular degeneration (AMD) accompanies the subfoveal choroidal neovascularization (CNV) caused by the abnormal extension or remodeling of blood vessels to the macula and retinal pigment epithelium (RPE). Vascular endothelial growth factor (VEGF) is known to play a crucial role in the pathogenesis of the disease. In this study, we tried to repurpose an investigational anticancer drug, rivoceranib, which is a selective inhibitor of VEGF receptor-2 (VEGFR2), and evaluate the therapeutic potential of the drug for the treatment of wet-type AMD in a laser-induced CNV mouse model using microsphere-based sustained drug release formulations. The PLGA-based rivoceranib microsphere can carry out a sustained delivery of rivoceranib for 50 days. When administered intravitreally, the sustained microsphere formulation of rivoceranib effectively inhibited the formation of subfoveal neovascular lesions in mice.

PMID:34683841 | PMC:PMC8538988 | DOI:10.3390/pharmaceutics13101548

J Fungi (Basel). 2021 Sep 25;7(10):803. doi: 10.3390/jof7100803.

ABSTRACT

Fungal infections have been increasing during the last decades. Scedosporium and Lomentospora species are filamentous fungi most associated to those infections, especially in immunocompromised patients. Considering the limited options of treatment and the emergence of resistant isolates, an increasing concern motivates the development of new therapeutic alternatives. In this context, the present study screened the Pathogen Box library to identify compounds with antifungal activity against Scedosporium and Lomentospora. Using antifungal susceptibility tests, biofilm analysis, scanning electron microscopy (SEM), and synergism assay, auranofin and iodoquinol were found to present promising repurposing applications. Both compounds were active against different Scedosporium and Lomentospora, including planktonic cells and biofilm. SEM revealed morphological alterations and synergism analysis showed that both drugs present positive interactions with voriconazole, fluconazole, and caspofungin. These data suggest that auranofin and iodoquinol are promising compounds to be studied as repurposing approaches against scedosporiosis and lomentosporiosis.

PMID:34682224 | PMC:PMC8539698 | DOI:10.3390/jof7100803

Int J Mol Sci. 2021 Oct 13;22(20):11029. doi: 10.3390/ijms222011029.

ABSTRACT

Mycobacterium abscessus (M. abscessus) causes chronic pulmonary infections and is the most difficult non-tuberculous mycobacteria (NTM) to treat due to its resistance to current antimicrobial drugs, with a treatment success rate of 45.6%. Thus, novel treatment drugs are needed, of which we identified the drug clomiphene citrate (CC), known to treat infertility in women, to exhibit inhibitory activity against M. abscessus. To assess the potential of CC as a treatment for M. abscessus pulmonary diseases, we measured its efficacy in vitro and established the intracellular activity of CC against M. abscessus in human macrophages. CC significantly inhibited the growth of not only wild-type M. abscessus strains but also clinical isolate strains and clarithromycin (CLR)-resistant strains of M. abscessus. CC's drug efficacy did not have cytotoxicity in the infected macrophages. Furthermore, CC worked in anaerobic non-replicating conditions as well as in the presence of biofilm. The results of this in vitro study on M. abscessus activity suggest the possibility of using CC to develop new drug hypotheses for the treatment of M. abscessus infections.

PMID:34681686 | PMC:PMC8537717 | DOI:10.3390/ijms222011029

Pharmaceuticals (Basel). 2021 Oct 16;14(10):1051. doi: 10.3390/ph14101051.

ABSTRACT

Differentially expressed genes have been previously identified by us in multidrug-resistant tumor cells mainly resistant to doxorubicin. In the present study, we exemplarily focused on some of these genes to investigate their causative relationship with drug resistance. HMOX1, NEIL2, and PRKCA were overexpressed by lentiviral-plasmid-based transfection of HEK293 cells. An in silico drug repurposing approach was applied using virtual screening and molecular docking of FDA-approved drugs to identify inhibitors of these new drug-resistant genes. Overexpression of the selected genes conferred resistance to doxorubicin and daunorubicin but not to vincristine, docetaxel, and cisplatin, indicating the involvement of these genes in resistance to anthracyclines but not to a broader MDR phenotype. Using virtual drug screening and molecular docking analyses, we identified FDA-approved compounds (conivaptan, bexarotene, and desloratadine) that were interacting with HMOX1 and PRKCA at even stronger binding affinities than 1-(adamantan-1-yl)-2-(1H-imidazol-1-yl)ethenone and ellagic acid as known inhibitors of HMOX1 and PRKCA, respectively. Conivaptan treatment increased doxorubicin sensitivity of both HMOX1- and PRKCA-transfected cell lines. Bexarotene treatment had a comparable doxorubicin-sensitizing effect in HMOX1-transfected cells and desloratadine in PRKCA-transfected cells. Novel drug resistance mechanisms independent of ABC transporters have been identified that contribute to anthracycline resistance in MDR cells.

PMID:34681275 | PMC:PMC8540045 | DOI:10.3390/ph14101051

J Cell Biochem. 2021 Oct 21. doi: 10.1002/jcb.30163. Online ahead of print.

ABSTRACT

The emergence of multidrug-resistant strains of Candida albicans has become a global threat mostly due to co-infection with immune-compromised patients leading to invasive candidiasis. The life-threatening form of the disease can be managed quickly and effectively by drug repurposing. Thus, the study used in silico approaches to evaluate Food and Drug Administration (FDA) approved drugs against three drug targets-TRR1, TOM40, and YHB1. The tertiary structures of three drug targets were modeled, refined, and evaluated for their structural integrity based on PROCHECK, ERRAT, and PROSA. High-throughput virtual screening of FDA-approved drugs (8815), interaction analysis, and energy profiles had revealed that DB01102 (Arbutamine), DB01611 (Hydroxychloroquine), and DB09319 (Carindacillin) exhibited better binding affinity with TRR1, TOM40, and YHB1, respectively. Notably, the molecular dynamic simulation explored that Gln45, Thr119, and Asp288 of TRR1; Thr107 and Ser121 of TOM40; Arg193, Glu213, and Ser228 of YHB1 are crucial residues for stable drug-target interaction. Additionally, it also prioritized Arbutamine-TRR1 as the best drug-target complex based on MM-PBSA (-52.72 kcal/mol), RMSD (2.43 Å), and radius of gyration (-21.49 Å) analysis. In-depth, PCA results supported the findings of molecular dynamic simulations. Interestingly, the conserved region (>70%) among the TRR1 sequences from pathogenic Candida species indicated the effectiveness of Arbutamine against multiple species of Candida as well. Thus, the study dispenses new insight and enriches the understanding of developing an advanced technique to consider potential antifungals against C. albicans. Nonetheless, a detailed experimental validation is needed to investigate the efficacy of Arbutamin against life-threatening candidiasis.

PMID:34672012 | DOI:10.1002/jcb.30163

Microbiol Spectr. 2021 Oct 20:e0101821. doi: 10.1128/Spectrum.01018-21. Online ahead of print.

ABSTRACT

Leishmania parasites are the causal agent of leishmaniasis, an endemic disease in more than 90 countries worldwide. Over the years, traditional approaches focused on the parasite when developing treatments against leishmaniasis. Despite numerous attempts, there is not yet a universal treatment, and those available have allowed for the appearance of resistance. Here, we propose and follow a host-directed approach that aims to overcome the current lack of treatment. Our approach identifies potential therapeutic targets in the host cell and proposes known drug interactions aiming to improve the immune response and to block the host machinery necessary for the survival of the parasite. We started analyzing transcription factor regulatory networks of macrophages infected with Leishmania major. Next, based on the regulatory dynamics of the infection and available gene expression profiles, we selected potential therapeutic target proteins. The function of these proteins was then analyzed following a multilayered network scheme in which we combined information on metabolic pathways with known drugs that have a direct connection with the activity carried out by these proteins. Using our approach, we were able to identify five host protein-coding gene products that are potential therapeutic targets for treating leishmaniasis. Moreover, from the 11 drugs known to interact with the function performed by these proteins, 3 have already been tested against this parasite, verifying in this way our novel methodology. More importantly, the remaining eight drugs previously employed to treat other diseases, remain as promising yet-untested antileishmanial therapies. IMPORTANCE This work opens a new path to fight parasites by targeting host molecular functions by repurposing available and approved drugs. We created a novel approach to identify key proteins involved in any biological process by combining gene regulatory networks and expression profiles. Once proteins have been selected, our approach employs a multilayered network methodology that relates proteins to functions to drugs that alter these functions. By applying our novel approach to macrophages during the Leishmania infection process, we both validated our work and found eight drugs already approved for use in humans that to the best of our knowledge were never employed to treat leishmaniasis, rendering our work as a new tool in the box available to the scientific community fighting parasites.

PMID:34668739 | DOI:10.1128/Spectrum.01018-21

J Cell Biochem. 2021 Oct 20. doi: 10.1002/jcb.30166. Online ahead of print.

ABSTRACT

Drug repurposing is an attractive option for identifying new treatment strategies, in particular in extraordinary situations of urgent need such as the current coronavirus disease 2019 (Covid-19) pandemic. Recently, the World Health Organization announced testing of three drugs as potential Covid-19 therapeutics that are known for their dampening effect on the immune system. Thus, the underlying concept of selecting these drugs is to temper the potentially life-threatening overshooting of the immune system reacting to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. This viewpoint discusses the possibility that the impact of these and other drugs on autophagy contributes to their therapeutic effect by hampering the SARS-CoV-2 life cycle.

PMID:34668225 | DOI:10.1002/jcb.30166

Sci Rep. 2021 Oct 19;11(1):20687. doi: 10.1038/s41598-021-99721-y.

ABSTRACT

This analysis presents a systematic evaluation of the extent of therapeutic opportunities that can be obtained from drug repurposing by connecting drug targets with disease genes. When using FDA-approved indications as a reference level we found that drug repurposing can offer an average of an 11-fold increase in disease coverage, with the maximum number of diseases covered per drug being increased from 134 to 167 after extending the drug targets with their high confidence first neighbors. Additionally, by network analysis to connect drugs to disease modules we found that drugs on average target 4 disease modules, yet the similarity between disease modules targeted by the same drug is generally low and the maximum number of disease modules targeted per drug increases from 158 to 229 when drug targets are neighbor-extended. Moreover, our results highlight that drug repurposing is more dependent on target proteins being shared between diseases than on polypharmacological properties of drugs. We apply our drug repurposing and network module analysis to COVID-19 and show that Fostamatinib is the drug with the highest module coverage.

PMID:34667255 | DOI:10.1038/s41598-021-99721-y

J Neuroinflammation. 2021 Oct 19;18(1):240. doi: 10.1186/s12974-021-02278-w.

ABSTRACT

BACKGROUND: Lysophosphatidic acid receptors (LPARs) are G-protein-coupled receptors involved in many physiological functions in the central nervous system. However, the role of the LPARs in multiple sclerosis (MS) has not been clearly defined yet.

METHODS: Here, we investigated the roles of LPARs in myelin oligodendrocyte glycoprotein peptides-induced experimental autoimmune encephalomyelitis (EAE), an animal model of MS.

RESULTS: Pre-inhibition with LPAR1-3 antagonist Ki16425 deteriorated motor disability of EAElow. Specifically, LPAR1-3 antagonist (intraperitoneal) deteriorated symptoms of EAElow associated with increased demyelination, chemokine expression, cellular infiltration, and immune cell activation (microglia and macrophage) in spinal cords of mice compared to the sham group. This LPAR1-3 antagonist also increased the infiltration of CD4+/IFN-γ+ (Th1) and CD4+/IL-17+ (Th17) cells into spinal cords of EAElow mice along with upregulated mRNA expression of IFN-γ and IL-17 and impaired blood-brain barrier (BBB) in the spinal cord. The underlying mechanism for negative effects of LPAR1-3 antagonist was associated with the overproduction of reactive oxygen species (ROS)-generating nicotinamide adenine dinucleotide phosphate (NADPH) oxidases (NOX) 2 and NOX3. Interestingly, LPAR1/2 agonist 1-oleoyl-LPA (LPA 18:1) (intraperitoneal) ameliorated symptoms of EAEhigh and improved representative pathological features of spinal cords of EAEhigh mice.

CONCLUSIONS: Our findings strongly suggest that some agents that can stimulate LPARs might have potential therapeutic implications for autoimmune demyelinating diseases such as MS.

PMID:34666785 | DOI:10.1186/s12974-021-02278-w

J Chem Inf Model. 2021 Oct 20. doi: 10.1021/acs.jcim.1c00524. Online ahead of print.

ABSTRACT

COVID-19, an acute viral pneumonia, has emerged as a devastating pandemic. Drug repurposing allows researchers to find different indications of FDA-approved or investigational drugs. In this current study, a sequence of pharmacophore and molecular modeling-based screening against COVID-19 Mpro (PDB: 6LU7) suggested a subset of drugs, from the Drug Bank database, which may have antiviral activity. A total of 44 out of 8823 of the most promising virtual hits from the Drug Bank were subjected to molecular dynamics simulation experiments to explore the strength of their interactions with the SARS-CoV-2 Mpro active site. MD findings point toward three drugs (DB04020, DB12411, and DB11779) with very low relative free energies for SARS-CoV-2 Mpro with interactions at His41 and Met49. MD simulations identified an additional interaction with Glu166, which enhanced the binding affinity significantly. Therefore, Glu166 could be an interesting target for structure-based drug design. Quantitative structural-activity relationship analysis was performed on the 44 most promising hits from molecular docking-based virtual screening. Partial least square regression accurately predicted the values of independent drug candidates' binding energy with impressively high accuracy. Finally, the EC50 and CC50 of 10 drug candidates were measured against SARS-CoV-2 in cell culture. Nilotinib and bemcentinib had EC50 values of 2.6 and 1.1 μM, respectively. In summary, the results of our computer-aided drug design provide a roadmap for rational drug design of Mpro inhibitors and the discovery of certified medications as COVID-19 antiviral therapeutics.

PMID:34666487 | DOI:10.1021/acs.jcim.1c00524

Drug Discov Today. 2021 Oct 16:S1359-6446(21)00438-4. doi: 10.1016/j.drudis.2021.10.002. Online ahead of print.

ABSTRACT

In the COVID-19 pandemic, drug repositioning has presented itself as an alternative to the time-consuming process of generating new drugs. This review describes a drug repurposing process that is based on a new data-driven approach: we put forward five information paths that associate COVID-19-related genes and COVID-19 symptoms with drugs that directly target these gene products, that target the symptoms or that treat diseases that are symptomatically or genetically similar to COVID-19. The intersection of the five information paths results in a list of 13 drugs that we suggest as potential candidates against COVID-19. In addition, we have found information in published studies and in clinical trials that support the therapeutic potential of the drugs in our final list.

PMID:34666181 | DOI:10.1016/j.drudis.2021.10.002

Free Radic Biol Med. 2021 Oct 16:S0891-5849(21)00762-0. doi: 10.1016/j.freeradbiomed.2021.08.245. Online ahead of print.

ABSTRACT

As hypoxia is a major driver for the pathophysiology of COVID-19, it is crucial to characterize the hypoxic response at the cellular and molecular levels. In order to augment drug repurposing with the identification of appropriate molecular targets, investigations on therapeutics preventing hypoxic cell damage is required. In this work, we propose a hypoxia model based on alveolar lung epithelial cells line using chemical inducer, CoCl2 that can be used for testing calcium channel blockers (CCBs). Since recent studies suggested that CCBs may reduce the infectivity of SARS-Cov-2, we specifically select FDA approved calcium channel blocker, nifedipine for the study. First, we examined hypoxia-induced cell morphology and found a significant increase in cytosolic calcium levels, mitochondrial calcium overload as well as ROS production in hypoxic A549 cells. Secondly, we demonstrate the protective behaviour of nifedipine for cells that are already subjected to hypoxia through measurement of cell viability as well as 4D imaging of cellular morphology and nuclear condensation. Thirdly, we show that the protective effect of nifedipine is achieved through the reduction of cytosolic calcium, mitochondrial calcium, and ROS generation. Overall, we outline a framework for quantitative analysis of mitochondrial calcium and ROS using 3D imaging in laser scanning confocal microscopy and the open-source image analysis platform ImageJ. The proposed pipeline was used to visualize mitochondrial calcium and ROS level in individual cells that provide an understanding of molecular targets. Our findings suggest that the therapeutic value of nifedipine may potentially be evaluated in the context of COVID-19 therapeutic trials.

PMID:34666149 | DOI:10.1016/j.freeradbiomed.2021.08.245

IEEE J Biomed Health Inform. 2021 Oct 19;PP. doi: 10.1109/JBHI.2021.3120933. Online ahead of print.

ABSTRACT

Disease signature-based drug repositioning approaches typically first identify a disease signature from gene expression profiles of disease samples to represent a particular disease. Then such a disease signature is connected with the drug-induced gene expression profiles to find potential drugs for the particular disease. In order to obtain reliable disease signatures, the size of disease samples should be large enough, which is not always a single case in practice, especially for personalized medicine. On the other hand, the sample sizes of drug-induced gene expression profiles are generally large. In this study, we propose a new drug repositioning approach (HDgS), in which the drug signature is first identified from drug-induced gene expression profiles, and then connected to the gene expression profiles of disease samples to find the potential drugs for patients. In order to take the dependencies among genes into account, the human protein complexes (HPC) are used to define the drug signature. The proposed HDgS is applied to the drug-induced gene expression profiles in LINCS and several types of cancer samples. The results indicate that the HPC-based drug signature can effectively find drug candidates for patients and that the proposed HDgS can be applied for personalized medicine with even one patient sample.

PMID:34665747 | DOI:10.1109/JBHI.2021.3120933

Bioinformatics. 2021 Oct 19:btab715. doi: 10.1093/bioinformatics/btab715. Online ahead of print.

ABSTRACT

MOTIVATION: Identifying drug-target interactions (DTIs) is a crucial step in drug repurposing and drug discovery. Accurately identifying DTIs in silico can significantly shorten development time and reduce costs. Recently, many sequence-based methods are proposed for DTI prediction and improve performance by introducing the attention mechanism. However, these methods only model single non-covalent inter-molecular interactions among drugs and proteins and ignore the complex interaction between atoms and amino acids.

RESULTS: In this paper, we propose an end-to-end bio-inspired model based on the convolutional neural network (CNN) and attention mechanism, named HyperAttentionDTI, for predicting DTIs. We use deep CNNs to learn the feature matrices of drugs and proteins. To model complex non-covalent inter-molecular interactions among atoms and amino acids, we utilize the attention mechanism on the feature matrices and assign an attention vector to each atom or amino acid. We evaluate HpyerAttentionDTI on three benchmark datasets and the results show that our model achieves significantly improved performance compared to the state-of-the-art baselines. Moreover, a case study on the human Gamma-aminobutyric acid receptors confirm that our model can be used as a powerful tool to predict DTIs.

AVAILABILITY: The codes of our model are available at https://github.com/zhaoqichang/HpyerAttentionDTI and https://zenodo.org/record/5039589.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34664614 | DOI:10.1093/bioinformatics/btab715

J Biomol Struct Dyn. 2021 Oct 18:1-17. doi: 10.1080/07391102.2021.1990131. Online ahead of print.

ABSTRACT

Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to Flavivirus (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, in silico drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to de novo developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using in silico molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, in silico molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV. Communicated by Ramaswamy H. Sarma.

PMID:34662258 | DOI:10.1080/07391102.2021.1990131

Front Med (Lausanne). 2021 Sep 30;8:704256. doi: 10.3389/fmed.2021.704256. eCollection 2021.

ABSTRACT

Background: Recently, Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead to enormous losses. This study systematically reviews the application of Artificial Intelligence (AI) techniques in COVID-19, especially for diagnosis, estimation of epidemic trends, prognosis, and exploration of effective and safe drugs and vaccines; and discusses the potential limitations. Methods: We report this systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched PubMed, Embase and the Cochrane Library from inception to 19 September 2020 for published studies of AI applications in COVID-19. We used PROBAST (prediction model risk of bias assessment tool) to assess the quality of literature related to the diagnosis and prognosis of COVID-19. We registered the protocol (PROSPERO CRD42020211555). Results: We included 78 studies: 46 articles discussed AI-assisted diagnosis for COVID-19 with total accuracy of 70.00 to 99.92%, sensitivity of 73.00 to 100.00%, specificity of 25 to 100.00%, and area under the curve of 0.732 to 1.000. Fourteen articles evaluated prognosis based on clinical characteristics at hospital admission, such as clinical, laboratory and radiological characteristics, reaching accuracy of 74.4 to 95.20%, sensitivity of 72.8 to 98.00%, specificity of 55 to 96.87% and AUC of 0.66 to 0.997 in predicting critical COVID-19. Nine articles used AI models to predict the epidemic of the COVID-19, such as epidemic peak, infection rate, number of infected cases, transmission laws, and development trend. Eight articles used AI to explore potential effective drugs, primarily through drug repurposing and drug development. Finally, 1 article predicted vaccine targets that have the potential to develop COVID-19 vaccines. Conclusions: In this review, we have shown that AI achieved high performance in diagnosis, prognosis evaluation, epidemic prediction and drug discovery for COVID-19. AI has the potential to enhance significantly existing medical and healthcare system efficiency during the COVID-19 pandemic.

PMID:34660623 | PMC:PMC8514781 | DOI:10.3389/fmed.2021.704256

Front Pharmacol. 2021 Sep 30;12:720694. doi: 10.3389/fphar.2021.720694. eCollection 2021.

ABSTRACT

In the past decade, the emergence of machine learning (ML) applications has led to significant advances towards implementation of personalised medicine approaches for improved health care, due to the exceptional performance of ML models when utilising complex big data. The immune-mediated chronic inflammatory diseases are a group of complex disorders associated with dysregulated immune responses resulting in inflammation affecting various organs and systems. The heterogeneous nature of these diseases poses great challenges for tailored disease management and addressing unmet patient needs. Applying novel ML techniques to the clinical study of chronic inflammatory diseases shows promising results and great potential for precision medicine applications in clinical research and practice. In this review, we highlight the clinical applications of various ML techniques for prediction, diagnosis and prognosis of autoimmune rheumatic diseases, inflammatory bowel disease, autoimmune chronic kidney disease, and multiple sclerosis, as well as ML applications for patient stratification and treatment selection. We highlight the use of ML in drug development, including target identification, validation and drug repurposing, as well as challenges related to data interpretation and validation, and ethical concerns related to the use of artificial intelligence in clinical research.

PMID:34658859 | PMC:PMC8514674 | DOI:10.3389/fphar.2021.720694

Front Neurosci. 2021 Sep 29;15:736786. doi: 10.3389/fnins.2021.736786. eCollection 2021.

ABSTRACT

Ceftriaxone (CEF) is a safe and multipotent antimicrobial agent that possesses neuroprotective properties. Earlier, we revealed the restoration of cognitive function in OXYS rats with signs of Alzheimer's disease (AD)-like pathology by CEF along with its modulating the expression of genes related to the system of amyloid beta (Aβ) metabolism in the brain. The aim of this study was to determine the effects of CEF on behavior, Aβ deposition, and associated neuroinflammation using another model of an early AD-like pathology induced by Aβ. Mice were injected bilaterally i.c.v. with Aβ fragment 25-35 to produce the AD model, while the CEF treatment (100 mg/kg/day, i.p., 36 days) started the next day after the surgery. The open field test, T-maze, Barnes test, IntelliCage, and passive avoidance test were used for behavioral phenotyping. Neuronal density, amyloid accumulation, and the expression of neuroinflammatory markers were measured in the frontal cortex and hippocampus. CEF exhibited beneficial effects on some cognitive features impaired by Aβ neurotoxicity including complete restoration of the fear-induced memory and learning in the passive avoidance test and improved place learning in the IntelliCage. CEF significantly attenuated amyloid deposition and neuroinflammatory response. Thus, CEF could be positioned as a potent multipurpose drug as it simultaneously targets proteostasis network and neuroinflammation, as well as glutamate excitotoxicity, oxidative pathways, and neurotrophic function as reported earlier. Together with previous reports on the positive effects of CEF in AD models, the results confirm the potential of CEF as a promising treatment against cognitive decline from the early stages of AD progression.

PMID:34658774 | PMC:PMC8511453 | DOI:10.3389/fnins.2021.736786

ACS Infect Dis. 2021 Oct 18. doi: 10.1021/acsinfecdis.1c00278. Online ahead of print.

ABSTRACT

The antimicrobial medication malarone (atovaquone/proguanil) is used as a fixed-dose combination for treating children and adults with uncomplicated malaria or as chemoprophylaxis for preventing malaria in travelers. It is an inexpensive, efficacious, and safe drug frequently prescribed around the world. Following anecdotal evidence from 17 patients in the provinces of Quebec and Ontario, Canada, suggesting that malarone/atovaquone may present some benefits in protecting against COVID-19, we sought to examine its antiviral potential in limiting the replication of SARS-CoV-2 in cellular models of infection. In VeroE6 expressing human TMPRSS2 and human lung Calu-3 epithelial cells, we show that the active compound atovaquone at micromolar concentrations potently inhibits the replication of SARS-CoV-2 and other variants of concern including the alpha, beta, and delta variants. Importantly, atovaquone retained its full antiviral activity in a primary human airway epithelium cell culture model. Mechanistically, we demonstrate that the atovaquone antiviral activity against SARS-CoV-2 is partially dependent on the expression of TMPRSS2 and that the drug can disrupt the interaction of the spike protein with the viral receptor, ACE2. Additionally, spike-mediated membrane fusion was also reduced in the presence of atovaquone. In the United States, two clinical trials of atovaquone administered alone or in combination with azithromycin were initiated in 2020. While we await the results of these trials, our findings in cellular infection models demonstrate that atovaquone is a potent antiviral FDA-approved drug against SARS-CoV-2 and other variants of concern in vitro.

PMID:34658235 | DOI:10.1021/acsinfecdis.1c00278

Expert Rev Hematol. 2021 Oct 16. doi: 10.1080/17474086.2021.1995348. Online ahead of print.

ABSTRACT

INTRODUCTION: Drug repositioning (DR) is defined as determining new therapeutic applications for existing drugs. This approach is advantageous over de novo drug discovery in accelerating clinical development, in terms of lower costs, a shortened development period, a well-known action mechanism, a feasible dosage, and an acceptable safety profile.

AREAS COVERED: This work was aimed at reviewing agents with successful DR in hematology.

EXPERT OPINION: Thalidomide and plerixafor have been successfully repositioned for treating multiple myeloma and harvesting peripheral blood stem cells, respectively. The former was originally developed as a sedative and the latter as an anti-HIV drug. Currently, the feasibility of repositioning various agents is being explored (e.g., an anti-influenza virus drug oseltamivir for primary immune thrombocytopenia, an anti-HIV drug abacavir for adult T-cell leukemia, and a macrolide antibiotic clarithromycin for multiple myeloma). Furthermore, bosutinib for chronic myeloid leukemia or the antiplatelet drug cilostazol have been suggested to have clinical benefits for the management of amyotrophic lateral sclerosis and ischemic stroke, respectively. To promote DR, effective application of artificial intelligence or stem cell models, comprehensive database construction shared between academia and pharmaceutical companies, suitable handling of drug patents, and wide cooperation in the area of specialty are warranted.

PMID:34657533 | DOI:10.1080/17474086.2021.1995348