Azelastine for COVID-19

ABSTRACTBackgroundThe COVID-19 pandemic is an enormous threat for healthcare systems and economies worldwide that urgently demands effective preventive and therapeutic strategies. Unlike the development of vaccines and new drugs specifically targeting SARS-CoV-2, repurposing of approved or clinically tested drugs can provide an immediate solution.MethodsWe applied a novel computational approach to search among approved and clinically tested drugs from the DrugBank database. Candidates were selected based on Shannon entropy homology and predefined activity profiles of three small molecules with proven anti-SARS-CoV activity and a published data set. Antiviral activity of a predicted drug, azelastine, was tested in vitro in SARS-CoV-2 infection assays with Vero E6 monkey kidney epithelial cells and reconstituted human nasal tissue. The effect on viral replication was assessed by quantification of viral genomes by droplet digital PCR.FindingsThe computational approach with four independent queries identified major drug families, most often and in overlapping fashion anti-infective, anti-inflammatory, anti-hypertensive, anti-histamine and neuroactive drugs. Azelastine, an histamine 1 receptor-blocker, was predicted in multiple screens, and based on its attractive safety profile and availability in nasal formulation, was selected for experimental testing. Azelastine significantly reduced cytopathic effect and SARS-CoV-2 infection of Vero E6 cells with an EC50 of ∼6 μM both in a preventive and treatment setting. Furthermore, azelastine in a commercially available nasal spray tested at 5-fold dilution was highly potent in inhibiting viral propagation in SARS-CoV-2 infected reconstituted human nasal tissue.InterpretationsAzelastine, an anti-histamine, available in nasal sprays developed against allergic rhinitis may be considered as a topical prevention or treatment of nasal colonization with SARS-CoV-2. As such, it could be useful in reducing viral spread and prophylaxis of COVID-19. Ultimately, its potential benefit should be proven in clinical studies.Fundingprovided by the Hungarian government to the National Laboratory of Virology and by CEBINA GmbH.

Abstract Background:The current COVID-19 pandemic has had a major influence on our daily lives. The most frequent early symptoms associated with SARS-CoV-2 infection are coughing, fever, rhinitis, and loss of smell and taste. If the infection progresses to the lower respiratory tract, it can cause massive inflammation of the pulmonary system, which can be life threatening. There is urgent need for a broadly available and effective therapy for the treatment of early infections with SARS-CoV-2 in order to prevent progression to severe disease. Methodology:CARVIN is a phase II proof of concept, randomized, parallel, double-blind, placebo-controlled, interventional clinical trial. 90 SARS-CoV-2 positive volunteers were randomized into three groups to receive either placebo, azelastine 0.02% or azelastine 0.1% nasal spray for a period of 11 days. Seven nasopharyngeal swabs were taken during this period for quantitative PCR measurements assessing the viral load via the ORF 1a/b and E genes. Investigators also assessed patients’ status continuously throughout the trial, and the intensity of individual symptoms were reported by the patients using an electronic diary. Two safety follow-ups were performed at days 16 and 60 of study participation. Results:Since the data of the primary outcome did not show a normal distribution, all statistical tests presented here were done non-parametrically and all p-values are descriptive and without adjustment for multiple testing. A broader descriptive analysis will be performed at a later date on all variables and it will be published in a peer-reviewed publication. A wide range of initial viral loads in the nasopharyngeal swabs of the study population was observed with an overall median/mean + SD Ct value of approximately 21.9 / 23.6 + 5.8, corresponding to log10 6.6 + 1.8 copies per /ml. Out of the 90 enrolled subjects, at least 54 carried the Alpha (B.1.1.7, UK) variant.Treatment with azelastine nasal sprays resulted in a greater but non-significant decrease in mean viral load compared to that measured in the placebo group at all 6 timepoints after initiation of treatment. This tendency was stable and most pronounced on day 8 (after 7 days treatment), when in the 0.1% and 0.02% azelastine nasal spray groups, an approximately 8- and 29-fold greater clinically meaningful reduction of the baseline viral load, respectively, compared to placebo was observed (based on the ORF1a/b gene). On days 4 and 11, approximately 4-fold greater mean viral load reduction was seen in the 0.1% azelastine group.Differences in mean viral load compared to baseline values were seen starting on the second day (after one day of treatment) in the azelastine 0.1% and azelastine 0.02% group for ORF 1a/b gene, and with azelastine 0.1% for the E gene, while this reduction was less pronounced in the placebo group.The effects of 0.1% azelastine nasal spray treatment to accelerate viral load reduction were even more pronounced in patients..

The Coronavirus Disease 2019 (COVID-19) pandemic and the subsequent increase in respiratory viral infections highlight the need for broad-spectrum antivirals to enable a quick and efficient reaction to current and emerging viral outbreaks. We previously demonstrated that the antihistamine azelastine hydrochloride (azelastine-HCl) exhibited in vitro antiviral activity against SARS-CoV-2. Furthermore, in a phase 2 clinical study, a commercial azelastine-containing nasal spray significantly reduced the viral load in SARS-CoV-2-infected individuals. Here, we evaluate the efficacy of azelastine-HCl against additional human coronaviruses, including the SARS-CoV-2 omicron variant and a seasonal human coronavirus, 229E, through in vitro infection assays, with azelastine showing a comparable potency against both. Furthermore, we determined that azelastine-HCl also inhibits the replication of Respiratory syncytial virus A (RSV A) in both prophylactic and therapeutic settings. In a human 3D nasal tissue model (MucilAirTM-Pool, Epithelix), azelastine-HCl protected tissue integrity and function from the effects of infection with influenza A H1N1 and resulted in a reduced viral load soon after infection. Our results suggest that azelastine-HCl has a broad antiviral effect and can be considered a safe option against the most common respiratory viruses to prevent or treat such infections locally in the form of a nasal spray that is commonly available globally.

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.

AbstractA consensus virtual screening protocol has been applied to ca. 2000 approved drugs to seek inhibitors of the main protease (Mpro) of SARS-CoV-2, the virus responsible for COVID-19. 42 drugs emerged as top candidates, and after visual analyses of the predicted structures of their complexes with Mpro, 17 were chosen for evaluation in a kinetic assay for Mpro inhibition. Remarkably 14 of the compounds at 100-μM concentration were found to reduce the enzymatic activity and 5 provided IC50 values below 40 μM: manidipine (4.8 μM), boceprevir (5.4 μM), lercanidipine (16.2 μM), bedaquiline (18.7 μM), and efonidipine (38.5 μM). Structural analyses reveal a common cloverleaf pattern for the binding of the active compounds to the P1, P1’, and P2 pockets of Mpro. Further study of the most active compounds in the context of COVID-19 therapy is warranted, while all of the active compounds may provide a foundation for lead optimization to deliver valuable chemotherapeutics to combat the pandemic.

AbstractThe pandemic of novel coronavirus disease 2019 (COVID-19) has rampaged the world, with more than 58.4 million confirmed cases and over 1.38 million deaths across the world by 23 November 2020. There is an urgent need to identify effective drugs and vaccines to fight against the virus. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) belongs to the family of coronaviruses consisting of four structural and 16 non-structural proteins (NSP). Three non-structural proteins, main protease (Mpro), papain-like protease (PLpro), and RNA-dependent RNA polymerase (RdRp), are believed to have a crucial role in replication of the virus. We applied computational ligand-receptor binding modeling and performed comprehensive virtual screening on FDA-approved drugs against these three SARS-CoV-2 proteins using AutoDock Vina, Glide, and rDock. Our computational studies identified six novel ligands as potential inhibitors against SARS-CoV-2, including antiemetics rolapitant and ondansetron for Mpro; labetalol and levomefolic acid for PLpro; and leucal and antifungal natamycin for RdRp. Molecular dynamics simulation confirmed the stability of the ligand-protein complexes. The results of our analysis with some other suggested drugs indicated that chloroquine and hydroxychloroquine had high binding energy (low inhibitory effect) with all three proteins—Mpro, PLpro, and RdRp. In summary, our computational molecular docking approach and virtual screening identified some promising candidate SARS-CoV-2 inhibitors that may be considered for further clinical studies.