Ticagrelor for COVID-19

SARS-CoV2 has caused the recent mortal pandemic known as COVID-19. The drug repurposing approach can be employed to find the potential drugs capable of binding SARS-CoV2 structural and nonstructural proteins. The present study aimed to repurpose some common FAD-approved antiviral and non-antiviral drugs computationally for SARS-CoV2 treatment. In the in silico study, 89 FDA-approved drugs and Remdesivir, as the control, were analyzed by molecular docking to inhibit the SARS-CoV2 spike (S) protein as the key player in virus-cell binding. First, the Uniport website was used to find receptor and ganglioside binding domains (RBD and GBD, respectively) of the S protein as the target. The structure of the target was downloaded from RCSB, and 'the ligands' structures were downloaded from PubChem. All structures were refined using SPDV and PyRx software. AutoDock Vina was employed for the docking process. The result showed that 8 drugs, including Ledipasvir, Montelukast, Domperidone, Aprepitant, Folic acid, Losartan, Ticagrelor, and Rivaroxaban, can bind S protein and then inhibit the protein function. In addition, Ledipasvir, Montelukast, and Domperidone can bind GBD of the S protein with higher binding energy (-8.2, -8, -7.9 kcal/mol, respectively). On the other hand, higher RBD binding energy was calculated for Ticagrelor (-6.9 kcal/mol), Folic acid, Montelukast, and Domperidone (-6.5 kcal/mol). Generally, the ligands could inhibit GBD more than RBD. According to the binding energy to S protein and low side effects of the studied medications, Ledipasvir and Losartan can be introduced as the most effective candidates for repurposed drugs. Also, Gly496 and Asn137 are the most engaged amino acids in the ligand-receptor interaction from RBD and GBD, respectively.

AbstractHuman organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single‐cell RNA sequencing (scRNA‐seq) technology and genome‐wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait‐relevant cell types or states. Here, we constructed a computational framework to integrate atlas‐level organoid scRNA‐seq data, GWAS summary statistics, expression quantitative trait loci, and gene–drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID‐19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID‐19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID‐19‐damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID‐19, and this cell subset showed a notable increase in cell‐to‐cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID‐19 in a cell‐type‐specific manner. Overall, our results showcase that host genetic determinants have cellular‐specific contribution to COVID‐19 severity, and identification of cell type‐specific drug targets may facilitate to develop effective therapeutics for treating severe COVID‐19 and its complications.

Abstract Using as a template the crystal structure of the SARS-CoV-2 main protease, we developed a pharmacophore model of functional centers of the protease inhibitor-binding pocket. With this model, we conducted data mining of the conformational database of FDA-approved drugs. This search brought 64 compounds that can be potential inhibitors of the SARS-CoV-2 protease. The conformations of these compounds undergone 3D fingerprint similarity clusterization. Then we conducted docking of possible conformers of these drugs to the binding pocket of the protease. We also conducted the same docking of random compounds. Free energies of the docking interaction for the selected compounds were clearly lower than random compounds. Three of the selected compounds were carfilzomib, cyclosporine A, and azithromycin—the drugs that already are tested for COVID-19 treatment. Among the selected compounds are two HIV protease inhibitors and two hepatitis C protease inhibitors. We recommend testing of the selected compounds for treatment of COVID-19.