Remdesivir-ivermectin combination displays synergistic interaction with improved in vitro activity against SARS-CoV-2.
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ABSTRACT:
SUBMITTER: Jeffreys LN
PROVIDER: S-EPMC8801767 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The recent COVID-19 pandemic has highlighted the urgency to develop effective antiviral therapies against the disease. Murine hepatitis virus (MHV) is a coronavirus that infects mice and shares some sequence identity to SARS-CoV-2. Both viruses belong to the Betacoronavirus genus, and MHV thus serves as a useful and safe surrogate model for SARS-CoV-2 infections. Clinical trials have indicated that remdesivir is a potentially promising antiviral drug against COVID-19. Using an in vitro model of MHV infection of RAW264.7 macrophages, the safety and efficacy of monotherapy of remdesivir, chloroquine, ivermectin, and doxycycline were investigated. Of the four drugs tested, remdesivir monotherapy exerted the strongest inhibition of live virus and viral RNA replication of about 2-log10 and 1-log10, respectively (at 6 µM). Ivermectin treatment showed the highest selectivity index. Combination drug therapy was also evaluated using remdesivir (6 µM) together with chloroquine (15 µM), ivermectin (2 µM) or doxycycline (15 µM) - above their IC50 values and at high macrophage cell viability of over 95%. The combination of remdesivir and ivermectin exhibited highly potent synergism by achieving significant reductions of about 7-log10 of live virus and 2.5-log10 of viral RNA in infected macrophages. This combination also resulted in the lowest cytokine levels of IL-6, TNF-α, and leukemia inhibitory factor. The next best synergistic combination was remdesivir with doxycycline, which decreased levels of live virus by ~3-log10 and viral RNA by ~1.5-log10. These results warrant further studies to explore the mechanisms of action of the combination therapy, as well as future in vivo experiments and clinical trials for the treatment of SARS-CoV-2 infection.
| S-EPMC8362885 | biostudies-literature
Project description:The SARS-CoV-2 replication and transcription complex (RTC) comprising nonstructural protein (nsp) 2-16 plays crucial roles in viral replication, reducing the efficacy of broad-spectrum nucleoside analog drugs such as remdesivir and evading innate immune responses. Most studies target a specific viral component of the RTC such as the main protease or the RNA-dependent RNA polymerase. In contrast, our strategy is to target multiple conserved domains of the RTC to prevent SARS-CoV-2 genome replication and to create a high barrier to viral resistance and/or evasion of antiviral drugs. We show that the clinically safe Zn-ejector drugs disulfiram and ebselen can target conserved Zn2+ sites in SARS-CoV-2 nsp13 and nsp14 and inhibit nsp13 ATPase and nsp14 exoribonuclease activities. As the SARS-CoV-2 nsp14 domain targeted by disulfiram/ebselen is involved in RNA fidelity control, our strategy allows coupling of the Zn-ejector drug with a broad-spectrum nucleoside analog that would otherwise be excised by the nsp14 proofreading domain. As proof-of-concept, we show that disulfiram/ebselen, when combined with remdesivir, can synergistically inhibit SARS-CoV-2 replication in Vero E6 cells. We present a mechanism of action and the advantages of our multitargeting strategy, which can be applied to any type of coronavirus with conserved Zn2+ sites.
| S-EPMC8009100 | biostudies-literature
Project description:An escalating pandemic by the novel SARS-CoV-2 virus is impacting global health and effective therapeutic options are urgently needed. We evaluated the in vitro antiviral effect of compounds that were previously reported to inhibit coronavirus replication and compounds that are currently under evaluation in clinical trials for SARS-CoV-2 patients. We report the antiviral effect of remdesivir, lopinavir, homorringtonine, and emetine against SARS-CoV-2 virus in Vero E6 cells with the estimated 50% effective concentration at 23.15 ?M, 26.63 ?M, 2.55 ?M and 0.46 ?M, respectively. Ribavirin or favipiravir that are currently evaluated under clinical trials showed no inhibition at 100 ?M. Synergy between remdesivir and emetine was observed, and remdesivir at 6.25 ?M in combination with emetine at 0.195 ?M may achieve 64.9% inhibition in viral yield. Combinational therapy may help to reduce the effective concentration of compounds below the therapeutic plasma concentrations and provide better clinical benefits.
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Project description:The devastating pandemic due to SARS-CoV-2 and the emergence of antigenic variants that jeopardize the efficacy of current vaccines create an urgent need for a comprehensive understanding of the pathophysiology of COVID-19, including the contribution of inflammation to disease. It also warrants for the search of immunomodulatory drugs that could improve disease outcome. Here, we show that standard doses of ivermectin (IVM), an anti-parasitic drug with potential immunomodulatory activities through the cholinergic anti-inflammatory pathway, prevents clinical deterioration, reduces olfactory deficit and limits the inflammation of the upper and lower respiratory tracts in SARS-CoV-2-infected hamsters. Whereas it has no effect on viral load in the airways of infected animals, transcriptomic analyses of infected lungs reveal that IVM dampens type-I interferon responses and modulates several other inflammatory pathways. In particular, IVM dramatically reduces the Il-6/Il-10 ratio in lung tissue and promotes macrophage M2 polarization, which might account for the more favorable clinical presentation of IVM-treated animals. Altogether, this study supports the use of immunomodulatory drugs such as IVM, to improve the clinical condition of SARS-CoV-2-infected patients.
| S-SCDT-EMM-2021-14122 | biostudies-other
Project description:Remdesivir (RDV), a broadly acting nucleoside analogue, is the only FDA approved small molecule antiviral for the treatment of COVID-19 patients. To date, there are no reports identifying SARS-CoV-2 RDV resistance in patients, animal models or in vitro. Here, we selected drug-resistant viral populations by serially passaging SARS-CoV-2 in vitro in the presence of RDV. Using high throughput sequencing, we identified a single mutation in RNA-dependent RNA polymerase (NSP12) at a residue conserved among all coronaviruses in two independently evolved populations displaying decreased RDV sensitivity. Introduction of the NSP12 E802D mutation into our SARS-CoV-2 reverse genetics backbone confirmed its role in decreasing RDV sensitivity in vitro. Substitution of E802 did not affect viral replication or activity of an alternate nucleoside analogue (EIDD2801) but did affect virus fitness in a competition assay. Analysis of the globally circulating SARS-CoV-2 variants (>800,000 sequences) showed no evidence of widespread transmission of RDV-resistant mutants. Surprisingly, we observed an excess of substitutions in spike at corresponding sites identified in the emerging SARS-CoV-2 variants of concern (i.e., H69, E484, N501, H655) indicating that they can arise in vitro in the absence of immune selection. The identification and characterisation of a drug resistant signature within the SARS-CoV-2 genome has implications for clinical management and virus surveillance.
| S-EPMC8496873 | biostudies-literature
Project description:Rapid repurposing of existing drugs as new therapeutics for COVID-19 has been an important strategy in the management of disease severity during the ongoing SARS-CoV-2 pandemic. Here, we used high-throughput docking to screen 6000 compounds within the DrugBank library for their potential to bind and inhibit the SARS-CoV-2 3 CL main protease, a chymotrypsin-like enzyme that is essential for viral replication. For 19 candidate hits, parallel in vitro fluorescence-based protease-inhibition assays and Vero-CCL81 cell-based SARS-CoV-2 replication-inhibition assays were performed. One hit, diclazuril (an investigational anti-protozoal compound), was validated as a SARS-CoV-2 3 CL main protease inhibitor in vitro (IC50 value of 29 µM) and modestly inhibited SARS-CoV-2 replication in Vero-CCL81 cells. Another hit, lenvatinib (approved for use in humans as an anti-cancer treatment), could not be validated as a SARS-CoV-2 3 CL main protease inhibitor in vitro, but serendipitously exhibited a striking functional synergy with the approved nucleoside analogue remdesivir to inhibit SARS-CoV-2 replication, albeit this was specific to Vero-CCL81 cells. Lenvatinib is a broadly-acting host receptor tyrosine kinase (RTK) inhibitor, but the synergistic effect with remdesivir was not observed with other approved RTK inhibitors (such as pazopanib or sunitinib), suggesting that the mechanism-of-action is independent of host RTKs. Furthermore, time-of-addition studies revealed that lenvatinib/remdesivir synergy probably targets SARS-CoV-2 replication subsequent to host-cell entry. Our work shows that combining computational and cellular screening is a means to identify existing drugs with repurposing potential as antiviral compounds. Future studies could be aimed at understanding and optimizing the lenvatinib/remdesivir synergistic mechanism as a therapeutic option.
| S-EPMC8491895 | biostudies-literature
Project description:Viral RNA-dependent RNA polymerase (RdRp), a highly conserved molecule in RNA viruses, has recently emerged as a promising drug target for broad-acting inhibitors. Through a Vero E6-based anti-cytopathic effect assay, we found that BPR3P0128, which incorporates a quinoline core similar to hydroxychloroquine, outperformed the adenosine analog remdesivir in inhibiting RdRp activity (EC50 = 0.66 µM and 3 µM, respectively). BPR3P0128 demonstrated broad-spectrum activity against various severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern. When introduced after viral adsorption, BPR3P0128 significantly decreased SARS-CoV-2 replication; however, it did not affect the early entry stage, as evidenced by a time-of-drug-addition assay. This suggests that BPR3P0128's primary action takes place during viral replication. We also found that BPR3P0128 effectively reduced the expression of proinflammatory cytokines in human lung epithelial Calu-3 cells infected with SARS-CoV-2. Molecular docking analysis showed that BPR3P0128 targets the RdRp channel, inhibiting substrate entry, which implies it operates differently-but complementary-with remdesivir. Utilizing an optimized cell-based minigenome RdRp reporter assay, we confirmed that BPR3P0128 exhibited potent inhibitory activity. However, an enzyme-based RdRp assay employing purified recombinant nsp12/nsp7/nsp8 failed to corroborate this inhibitory activity. This suggests that BPR3P0128 may inhibit activity by targeting host-related RdRp-associated factors. Moreover, we discovered that a combination of BPR3P0128 and remdesivir had a synergistic effect-a result likely due to both drugs interacting with separate domains of the RdRp. This novel synergy between the two drugs reinforces the potential clinical value of the BPR3P0128-remdesivir combination in combating various SARS-CoV-2 variants of concern.
| S-EPMC10989008 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) pandemic severely impacts health, economy, and society worldwide. Antiviral drugs against SARS-CoV-2 are urgently needed to cope with this global crisis. It has been found that the biogenesis and release mechanisms of viruses share a common pathway with extracellular vesicles (EVs). We hypothesized that small molecule inhibitors of EV biogenesis/release could exert an anti-SARS-CoV-2 effect. Here, we screened 17 existing EV inhibitors and found that calpeptin, a cysteine proteinase inhibitor, exhibited the most potent anti-SARS-CoV-2 activity with no apparent cytotoxicity. Calpeptin demonstrated the dose-dependent inhibition against SARS-CoV-2 viral nucleoprotein expression in the infected cells with a half-maximal inhibitory concentration (IC50) of 1.44 µM in Vero-E6 and 26.92 µM in Calu-3 cells, respectively. Moreover, calpeptin inhibited the production of infectious virions with the lower IC50 of 0.6 µM in Vero E6 cells and 10.12 µM in Calu-3 cells. Interestingly, a combination of calpeptin and remdesivir, the FDA-approved antiviral drug against SARS-CoV-2 viral replication, significantly enhanced the anti-SARS-CoV-2 effects compared to monotherapy. This study discovered calpeptin as a promising candidate for anti-SARS-CoV-2 drug development. Further preclinical and clinical studies are warranted to elucidate the therapeutic efficacy of calpeptin and remdesivir combination in COVID-19.
| S-EPMC8465755 | biostudies-literature
Project description:Remdesivir (RDV, Veklury®) is a once-daily, nucleoside ribonucleic acid polymerase inhibitor of severe acute respiratory syndrome coronavirus 2 replication. Remdesivir has been granted approvals in several countries for use in adults and children hospitalized with severe coronavirus disease 2019 (COVID-19). Inside the cell, remdesivir undergoes metabolic activation to form the intracellular active triphosphate metabolite, GS-443902 (detected in peripheral blood mononuclear cells), and ultimately, the renally eliminated plasma metabolite GS-441524. This review discusses the pre-clinical pharmacology of RDV, clinical pharmacokinetics, pharmacodynamics/concentration-QT analysis, rationale for dose selection for treatment of patients with COVID-19, and drug-drug interaction potential based on available in vitro and clinical data in healthy volunteers. Following single-dose intravenous administration over 2 h of an RDV solution formulation across the dose range of 3-225 mg in healthy participants, RDV and its metabolites (GS-704277and GS-441524) exhibit linear pharmacokinetics. Following multiple doses of RDV 150 mg once daily for 7 or 14 days, major metabolite GS-441524 accumulates approximately 1.9-fold in plasma. Based on pharmacokinetic bridging from animal data and available human data in healthy volunteers, the RDV clinical dose regimen of a 200-mg loading dose on day 1 followed by 100-mg maintenance doses for 4 or 9 days was selected for further evaluation of pharmacokinetics and safety. Results showed high intracellular concentrations of GS-443902 suggestive of efficient conversion from RDV into the triphosphate form, and further supporting this clinical dosing regimen for the treatment of COVID-19. Mathematical drug-drug interaction liability predictions, based on in vitro and phase I data, suggest RDV has low potential for drug-drug interactions, as the impact of inducers or inhibitors on RDV disposition is minimized by the parenteral route of administration and extensive extraction. Using physiologically based pharmacokinetic modeling, RDV is not predicted to be a clinically significant inhibitor of drug-metabolizing enzymes or transporters in patients infected with COVID-19 at therapeutic RDV doses.
| S-EPMC8007387 | biostudies-literature
Project description:The effect of cancer therapies is often tested pre-clinically via in vitro experiments, where the post-treatment viability of the cancer cell population is measured through assays estimating the number of viable cells. In this way, large libraries of compounds can be tested, comparing the efficacy of each treatment. Drug interaction studies focus on the quantification of the additional effect encountered when two drugs are combined, as opposed to using the treatments separately. In the bayesynergy R package, we implement a probabilistic approach for the description of the drug combination experiment, where the observed dose response curve is modelled as a sum of the expected response under a zero-interaction model and an additional interaction effect (synergistic or antagonistic). Although the model formulation makes use of the Bliss independence assumption, we note that the posterior estimates of the dose-response surface can also be used to extract synergy scores based on other reference models, which we illustrate for the Highest Single Agent model. The interaction is modelled in a flexible manner, using a Gaussian process formulation. Since the proposed approach is based on a statistical model, it allows the natural inclusion of replicates, handles missing data and uneven concentration grids, and provides uncertainty quantification around the results. The model is implemented in the open-source Stan programming language providing a computationally efficient sampler, a fast approximation of the posterior through variational inference, and features parallel processing for working with large drug combination screens.
| S-EPMC8575029 | biostudies-literature