Valdecoxib for COVID-19

Papain-like protease (PLpro) is a crucial enzyme for SARS-CoV-2 replication and immune evasion. Inhibiting PLpro could be a promising strategy to fight against COVID-19. This study aimed to identify potent inhibitors of PLpro among FDA-approved drugs using an in silico approach. The study also aimed to examine and confirm the binding of the selected compounds to the active pocket of PLpro using a multi-phased in silico approach, involving the screening of 3009 FDA-approved drugs to pinpoint the most similar compounds to, TTT, the co-crystallized ligand TTT of PLpro. The selected compounds were subjected to further analysis, including molecular docking, molecular dynamics simulations, MM-GPSA (molecular mechanics generalized Born surface area), and PLIP (Protein-Ligand Interaction Profiler) studies, to examine and confirm their binding to the active pocket of PLpro. Seven candidates (Vismodegib, Celecoxib, Ketoprofen, Indomethacin, Naphazoline, Valdecoxib, and Eslicarbazepine) showed promising in silico activities against the PLpro. The computational analysis confirmed the binding of Celecoxib to the active pocket of PLpro, suggesting its potential in the fight against COVID-19. This study identified seven FDA-approved drugs as potential inhibitors of PLpro, providing a feasible approach for drug repurposing against COVID-19. The results obtained from the in silico approach hold promise, but further in vitro and in vivo studies are warranted to validate the potential of these compounds.

The SARS coronavirus 2 (SARS-CoV-2) has caused an ongoing global pandemic with currently 29 million confirmed cases and close to a million deaths. At this time, there are no FDA-approved vaccines or therapeutics for COVID-19, but Emergency Use Authorization has been granted for remdesivir, a broad-spectrum antiviral nucleoside analog. However, remdesivir is only moderately efficacious against SARS-CoV-2 in the clinic, and improved treatment strategies are urgently needed. To accomplish this goal, we devised a strategy to identify compounds that act synergistically with remdesivir in preventing SARS-CoV-2 replication. We conducted combinatorial high-throughput screening in the presence of submaximal remdesivir concentrations, using a human lung epithelial cell line infected with a clinical isolate of SARS-CoV-2. We identified 20 approved drugs that act synergistically with remdesivir, many with favorable pharmacokinetic and safety profiles. Strongest effects were observed with established antivirals, Hepatitis C virus nonstructural protein 5 A (HCV NS5A) inhibitors velpatasvir and elbasvir. Combination with their partner drugs sofosbuvir and grazoprevir further increased efficacy, increasing remdesivir’s apparent potency 25-fold. We therefore suggest that the FDA-approved Hepatitis C therapeutics Epclusa (velpatasvir/sofosbuvir) and Zepatier (elbasvir/grazoprevir) should be fast-tracked for clinical evaluation in combination with remdesivir to improve treatment of acute SARS-CoV-2 infections.

AbstractSARS coronavirus 2 (SARS-CoV-2) has caused an ongoing global pandemic with significant mortality and morbidity. At this time, the only FDA-approved therapeutic for COVID-19 is remdesivir, a broad-spectrum antiviral nucleoside analog. Efficacy is only moderate, and improved treatment strategies are urgently needed. To accomplish this goal, we devised a strategy to identify compounds that act synergistically with remdesivir in preventing SARS-CoV-2 replication. We conducted combinatorial high-throughput screening in the presence of submaximal remdesivir concentrations, using a human lung epithelial cell line infected with a clinical isolate of SARS-CoV-2. This identified 20 approved drugs that act synergistically with remdesivir, many with favorable pharmacokinetic and safety profiles. Strongest effects were observed with established antivirals, Hepatitis C virus nonstructural protein 5A (HCV NS5A) inhibitors velpatasvir and elbasvir. Combination with their partner drugs sofosbuvir and grazoprevir further increased efficacy, increasing remdesivir’s apparent potency > 25-fold. We report that HCV NS5A inhibitors act on the SARS-CoV-2 exonuclease proofreader, providing a possible explanation for the synergy observed with nucleoside analog remdesivir. FDA-approved Hepatitis C therapeutics Epclusa® (velpatasvir/sofosbuvir) and Zepatier® (elbasvir/grazoprevir) could be further optimized to achieve potency and pharmacokinetic properties that support clinical evaluation in combination with remdesivir.

The current pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) demands rapid identification of new antiviral molecules from the existing drugs. Drug repurposing is a significant alternative for pandemics and emerging diseases because of the availability of preclinical data, documented safety in clinic and possibility of immediate production and scalable capacity and supply. Several drugs such as ivermectin and hydroxy chloroquine have been repurposed as anti-SARS-CoV-2 agents, but the effect of these compounds in treating the COVID-19 patients remains sub-optimal. In the present study repurposed drug libraries consisting of 560 compounds from two different sources have been screened against SARS-CoV-2 isolate USA-WA1/2020 in Vero-E6 cell line and 24 compounds were found active. The SARS-CoV-2 virus propagated in Vero E6 cell line and used in screening the drug libraries was sequenced by Next Generation Sequencing to identify any mutations that may have accumulated in the virus genome. The whole genome sequencing data of SARS-CoV-2 showed 9 and 6 single nucleotide polymorphisms in spike protein with reference to Wuhan-Hu-1(NC045512.2) and USA/WA-CDC-WA1/2020 (MN985325.1) isolates respectively. The present study identified 24 compounds active against SARS-CoV-2 isolate USA-WA1/2020 out of 560 repurposed drugs from two libraries. The IC-50 values of the identified hits range from 0.4 µM to 16 µM. Further studies on the repurposed drugs identified in the present screen may be helpful in the rapid development of antiviral drugs against SARS-CoV-2.

Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit. A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities.