Levamisole for COVID-19

Abstract Background Levamisole has shown clinical benefits in the management of COVID-19 via its immunomodulatory effect. However, the exact role of Levamisole effect in clinical status of COVID-19 patients is unknown. We aimed to evaluate the efficacy of Levamisole on clinical status of patients with COVID-19 during their course of the disease. Methods This prospective, double-blind, randomized controlled clinical trial was performed in adult patients with mild to moderate COVID-19 (room-air oxygen saturation > 94%) from late April 2020 to mid-August 2020. Patients were randomly assigned to receive a 3-day course of Levamisole or placebo in combination with routine standard of care. Results With 25 patients in each arm, 50 patients with COVID-19 were enrolled in the study. Most of the study participants were men (60%). On days 3 and 14, patients in Levamisole group had significantly better cough status distribution when compared to the placebo group (P-value = 0.034 and 0.005, respectively). Moreover, there was significant differences between the two groups in dyspnea at follow-up intervals of 7 (P-value = 0.015) and 14 (P-value = 0.010) days after receiving the interventions. However, no significant difference in fever status was observed on days 1, 3, 7, and 14 in both groups (P-value > 0.05). Conclusion The results of the current study suggest that Levamisole may improve most of clinical status of patients with COVID-19. The patients receiving Levamisole had significantly better chance of clinical status including cough and dyspnea on day 14 when compared to the placebo. However, the effect-size of this finding has uncertain clinical importance. Trial registration The trial was registered as IRCT20190810044500N7 (19/09/2020).

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.

According to the World Health Organization (WHO), in the second half of 2022, there are about 606 million confirmed cases of COVID-19 and almost 6,500,000 deaths around the world. A pandemic was declared by the WHO in March 2020 when the new coronavirus spread around the world. The short time between the first cases in Wuhan and the declaration of a pandemic initiated the search for ways to stop the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or to attempt to cure the disease COVID-19. More than ever, research groups are developing vaccines, drugs, and immunobiological compounds, and they are even trying to repurpose drugs in an increasing number of clinical trials. There are great expectations regarding the vaccine’s effectiveness for the prevention of COVID-19. However, producing sufficient doses of vaccines for the entire population and SARS-CoV-2 variants are challenges for pharmaceutical industries. On the contrary, efforts have been made to create different vaccines with different approaches so that they can be used by the entire population. Here, we summarize about 8162 clinical trials, showing a greater number of drug clinical trials in Europe and the United States and less clinical trials in low-income countries. Promising results about the use of new drugs and drug repositioning, monoclonal antibodies, convalescent plasma, and mesenchymal stem cells to control viral infection/replication or the hyper-inflammatory response to the new coronavirus bring hope to treat the disease.

An outbreak of pneumonia occurred on December 2019 in Wuhan, China, which caused a serious public health emergency by spreading around the globe. Globally, natural products are being focused on more than synthetic ones. So, keeping that in view, the current study was conducted to discover potential antiviral compounds from Allium sativum. Twenty-five phytocompounds of this plant were selected from the literature and databases including 3-(Allylsulphinyl)-L-alanine, Allicin, Diallyl sulfide, Diallyl disulfide, Diallyl trisulfide, Glutathione, L-Cysteine, S-allyl-mercapto-glutathione, Quercetin, Myricetin, Thiocysteine, Gamma-glutamyl-Lcysteine, Gamma-glutamylallyl-cysteine, Fructan, Lauricacid, Linoleicacid, Allixin, Ajoene, Diazinon Kaempferol, Levamisole, Caffeicacid, Ethyl linoleate, Scutellarein, and S-allylcysteine methyl-ester. Virtual screening of these selected ligands was carried out against drug target 3CL protease by CB-dock. Pharmacokinetic and pharmacodynamic properties defined the final destiny of compounds as drug or non-drug molecules. The best five compounds screened were Allicin, Diallyl Sulfide, Diallyl Disulfide, Diallyl Trisulfide, Ajoene, and Levamisole, which showed themselves as hit compounds. Further refining by screening filters represented Levamisole as a lead compound. All the interaction visualization analysis studies were performed using the PyMol molecular visualization tool and LigPlot+. Conclusively, Levamisole was screened as a likely antiviral compound which might be a drug candidate to treat SARS-CoV-2 in the future. Nevertheless, further research needs to be carried out to study their potential medicinal use.

Acute respiratory distress syndrome (ARDS) is intricately linked with SARS-CoV-2-associated disease severity and mortality, especially in patients with co-morbidities. Lung tissue injury caused as a consequence of ARDS leads to fluid build-up in the alveolar sacs, which in turn affects oxygen supply from the capillaries. ARDS is a result of a hyperinflammatory, non-specific local immune response (cytokine storm), which is aggravated as the virus evades and meddles with protective anti-viral innate immune responses. Treatment and management of ARDS remain a major challenge, first, because the condition develops as the virus keeps replicating and, therefore, immunomodulatory drugs are required to be used with caution. Second, the hyperinflammatory responses observed during ARDS are quite heterogeneous and dependent on the stage of the disease and the clinical history of the patients. In this review, we present different anti-rheumatic drugs, natural compounds, monoclonal antibodies, and RNA therapeutics and discuss their application in the management of ARDS. We also discuss on the suitability of each of these drug classes at different stages of the disease. In the last section, we discuss the potential applications of advanced computational approaches in identifying reliable drug targets and in screening out credible lead compounds against ARDS.