Mebendazole for COVID-19

Background. An in-silico screen identified mebendazole with potential antiviral activity that could be a repurposed drug against SARS-CoV-2. Mebendazole is a well-tolerated and cheap antihelminthic agent that is readily available worldwide and thus could be a therapeutic tool in the fight against COVID-19. Methods. This is an observational retrospective study of PCR-confirmed COVID-19 patients who received mebendazole with the intention-to-treat. The study included an inpatient cohort (157 inpatients) and an outpatient cohort (185 outpatients). Of the 157 inpatients and 185 outpatients, 68 (43.3%) and 94 (50.8%) received mebendazole, respectively. Patients who presented within the same timeframe but did not receive mebendazole were used as controls. Patients received standard-of-care treatment including remdesivir, dexamethasone, and anticoagulants as deemed necessary by the treating physician. The following clinical outcomes were evaluated: for the inpatient cohort, length of stay (LOS) at the hospital, need for ventilation (combined invasive and noninvasive), and mortality; for the outpatient cohort, time to symptom resolution, need for hospitalization, and mortality. Results. For the inpatient cohort, the median age did not differ between the treatment and control groups; 62 (56, 67) vs. 62 (56, 68), <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>P</mi> </math> , and there was a comparable proportion of males in both groups; 43 (63%) vs. 55 (62%), <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mi>P</mi> <mo>=</mo> <mn>0.85</mn> </math> . The hospital LOS was 3.5 days shorter in the treatment group compared to the control group ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mi>P</mi> <mo>&lt;</mo> <mn>0.001</mn> </math> ). There were fewer patients who required invasive or noninvasive ventilation in the treatment group, 2 (2.9%) vs. 7 (7.9%), and the mortality rate is lower in the treatment group, 3 (4.4%) vs. 8 (9.0%), though the differences did not reach statistical significance. For the outpatient cohort, the median age was lower in the treatment group compared with the control group; 40 (34, 48) vs. 48 (41, 54), <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <mi>P</mi> <mo>&lt;</mo> <mn>0.001</mn> </math> . There was a comparable proportion of males between both groups; 50 (53%) vs. 52 (57%), <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5"> <mi>P</mi> ..

The outbreak of the COVID-19 pandemic has spread throughout the world, affecting almost all nations and territories. The current double-blind, randomized, placebo-controlled, phase II clinical trial sought to evaluate the clinical efficacy and safety of mebendazole as an adjuvant therapy for outpatients with COVID-19. The patients were recruited and divided into two groups: a Mebendazole-treated group and placebo group. The mebendazole and placebo groups were matched for age, sex, and complete blood count (CBC) with differential and liver and kidney function tests at baseline. On the third day, the C-reactive protein (CRP) levels were lower (2.03 ± 1.45 vs. 5.45 ± 3.95, p &lt; 0.001) and the cycle threshold (CT) levels were higher (27.21 ± 3.81 vs. 24.40 ± 3.09, p = 0.046) significantly in the mebendazole group than in the placebo group on the third day. Furthermore, CRP decreased and CT dramatically increased on day three compared to the baseline day in the mebendazole group (p &lt; 0.001 and p = 0.008, respectively). There was a significant inverse correlation between lymphocytes and CT levels in the mebendazole group (r = −0.491, p = 0.039) but not in the placebo group (r = 0.051, p = 0.888). Mebendazole therapy increased innate immunity and returned inflammation to normal levels in COVID-19 outpatients faster than it did in the placebo group in this clinical trial. Our findings add to the growing body of research on the clinical and microbiological benefits of repurposing antiparasitic therapy, specifically mebendazole, for SARS-CoV-2 infection and other viral infections.

Background:The development and roll-out of vaccines, and the use of various drugs have contributed to controlling the COVID-19 pandemic. Nevertheless, challenges such as the inequitable distribution of vaccines, the influence of emerging viral lineages and immune evasive variants on vaccine efficacy, and the inadequate immune defense in subgroups of the population continue to motivate the development of new drugs to combat the disease. Aim:In this study, we sought to identify, prioritize, and characterize drug repurposing candidates appropriate for treating mild, moderate, or severe COVID-19 using a network-based integrative approach that systematically integrates drug-related data and multi-omics datasets. Methods: We leveraged drug data, and multi-omics data, and used a random walk restart algorithm to explore an integrated knowledge graph comprised of three sub-graphs: (i) a COVID-19 knowledge graph, (ii) a drug repurposing knowledge graph, and (iii) a COVID-19 disease-state specific omics graph. Results:We prioritized twenty FDA-approved agents as potential candidate drugs for mild, moderate, and severe COVID-19 disease phases. Specifically, drugs that could stimulate immune cell recruitment and activation including histamine, curcumin, and paclitaxel have potential utility in mild disease states to mitigate disease progression. Drugs like omacetaxine, crizotinib, and vorinostat that exhibit antiviral properties and have the potential to inhibit viral replication can be considered for mild to moderate COVID-19 disease states. Also, given the association between antioxidant deficiency and high inflammatory factors that trigger cytokine storms, antioxidants like glutathione can be considered for moderate disease states. Drugs that exhibit potent anti-inflammatory effects like (i) anti-inflammatory drugs (sarilumab and tocilizumab), (ii) corticosteroids (dexamethasone and hydrocortisone), and (iii) immunosuppressives (sirolimus and cyclosporine) are potential candidates for moderate to severe disease states that trigger a hyperinflammatory cascade of COVID-19. Conclusion:Our study demonstrates that the multi-omics data-driven integrative analysis within the drug data enables prioritizing drug candidates for COVID-19 disease phases, offering a comprehensive basis for therapeutic strategies that can be brought to market quickly given their established safety profiles. Importantly, the multi-omics data-driven integrative analysis within the drug data approach implemented here can be used to prioritize drug repurposing candidates appropriate for other diseases.

The current pandemic has highlighted the need for methodologies that can quickly and reliably prioritize clinically approved compounds for their potential effectiveness for SARS-CoV-2 infections. In the past decade, network medicine has developed and validated multiple predictive algorithms for drug repurposing, exploiting the sub-cellular network-based relationship between a drug's targets and disease genes. Here, we deployed algorithms relying on artificial intelligence, network diffusion, and network proximity, tasking each of them to rank 6,340 drugs for their expected efficacy against SARS-CoV-2. To test the predictions, we used as ground truth 918 drugs that had been experimentally screened in VeroE6 cells, and the list of drugs under clinical trial, that capture the medical community's assessment of drugs with potential COVID-19 efficacy. We find that while most algorithms offer predictive power for these ground truth data, no single method offers consistently reliable outcomes across all datasets and metrics. This prompted us to develop a multimodal approach that fuses the predictions of all algorithms, showing that a consensus among the different predictive methods consistently exceeds the performance of the best individual pipelines. We find that 76 of the 77 drugs that successfully reduced viral infection do not bind the proteins targeted by SARS-CoV-2, indicating that these drugs rely on network-based actions that cannot be identified using docking-based strategies. These advances offer a methodological pathway to identify repurposable drugs for future pathogens and neglected diseases underserved by the costs and extended timeline of de novo drug development.

AbstractCoronaviruses (CoVs) circulate in humans and animals, and expand their host range by zoonotic and anthroponotic transmissions. Endemic human CoVs, such as 229E and OC43 cause limited respiratory disease, and elicit short term anti-viral immunity favoring recurrent infections. Yet, severe acute respir-atory syndrome (SARS)-CoV-2 spreads across the globe with unprecedented impact on societies and economics. The world lacks broadly effective and affordable anti-viral agents to fight the pandemic and reduce the death toll. Here, we developed an image-based multicycle replication assay for focus for-mation of α-coronavirus hCoV-229E-eGFP infected cells for screening with a chemical library of 5440 compounds arrayed in 384 well format. The library contained about 39% clinically used compounds, 26% in phase I, II or III clinical trials, and 34% in preclinical development. Hits were counter-selected against toxicity, and challenged with hCoV-OC43 and SARS-CoV-2 in tissue culture and human bronchial and nasal epithelial explant cultures from healthy donors. Fifty three compounds inhibited hCoV-229E-GFP, 39 of which at 50% effective concentrations (EC50) &lt; 2μM, and were at least 2-fold separated from toxicity. Thirty nine of the 53 compounds inhibited the replication of hCoV-OC43, while SARS-CoV-2 was inhibited by 11 compounds in at least two of four tested cell lines. Six of the 11 compounds are FDA-approved, one of which is used in mouth wash formulations, and five are systemic and orally available. Here, we demonstrate that methylene blue (MB) and mycophenolic acid (MPA), two broadly available low cost compounds, strongly inhibited shedding of infectious SARS-CoV-2 at the apical side of the cultures, in either pre- or post-exposure regimens, with somewhat weaker effects on viral RNA release indicated by RT-qPCR measurements. Our study illustrates the power of full cycle screens in repurposing clinical compounds against SARS-CoV-2. Importantly, both MB and MPA reportedly act as immunosuppressants, making them interesting candidates to counteract the cytokine storms affecting COVID-19 patients.

Purpose: This study introduces a sophisticated computational pipeline, eVir, designed for the discovery of antiviral drugs based on their interactions within the human protein network. There is a pressing need for cost-effective therapeutics for infectious diseases (e.g., COVID-19), particularly in resource-limited countries. Therefore, our team devised an Artificial Intelligence (AI) system to explore repurposing opportunities for currently used oral therapies. The eVir system operates by identifying pharmaceutical compounds that mirror the effects of antiviral peptides (AVPs)—fragments of human proteins known to interfere with fundamental phases of the viral life cycle: entry, fusion, and replication. eVir extrapolates the probable antiviral efficacy of a given compound by analyzing its established and predicted impacts on the human protein-protein interaction network. This innovative approach provides a promising platform for drug repurposing against SARS-CoV-2 or any virus for which peptide data is available.Methods: The eVir AI software pipeline processes drug-protein and protein-protein interaction networks generated from open-source datasets. eVir uses Node2Vec, a graph embedding technique, to understand the nuanced connections among drugs and proteins. The embeddings are input a Siamese Network (SNet) and MLPs, each tailored for the specific mechanisms of entry, fusion, and replication, to evaluate the similarity between drugs and AVPs. Scores generated from the SNet and MLPs undergo a Platt probability calibration and are combined into a unified score that gauges the potential antiviral efficacy of a drug. This integrated approach seeks to boost drug identification confidence, offering a potential solution for detecting therapeutic candidates with pronounced antiviral potency. Once identified a number of compounds were tested for efficacy and toxicity in lung carcinoma cells (Calu-3) infected with SARS-CoV-2. A lead compound was further identified to determine its efficacy and toxicity in K18-hACE2 mice infected with SARS-CoV-2.Computational Predictions: The SNet confidently differentiated between similar and dissimilar drug pairs with an accuracy of 97.28% and AUC of 99.47%. Key compounds identified through these networks included Zinc, Mebendazole, Levomenol, Gefitinib, Niclosamide, and Imatinib. Notably, Mebendazole and Zinc showcased the highest similarity scores, while Imatinib, Levemenol, and Gefitinib also ranked within the top 20, suggesting their significant pharmacological potentials. Further examination of protein binding analysis using explainable AI focused on reverse engineering the causality of the networks. Protein interaction scores for Mebendazole and Imatinib revealed their effects on notable proteins such as CDPK1, VEGF2, ABL1, and several tyrosine protein kinases.Laboratory Studies: This study determined that Mebendazole, Gefitinib, Topotecan and to some extent Carfilzomib showed conventional drug-response curves,..