Paricalcitol for COVID-19

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.

The new strain of Coronaviruses (SARS-CoV-2), and the resulting Covid-19 disease has spread swiftly across the globe after its initial detection in late December 2019 in Wuhan, China, resulting in a pandemic status declaration by WHO within 3 months. Given the heavy toll of this pandemic, researchers are actively testing various strategies including new and repurposed drugs as well as vaccines. In the current brief report, we adopted a repositioning approach using insilico molecular modeling screening using FDA approved drugs with established safety profiles for potential inhibitory effects on Covid-19 virus. We started with structure based drug design by screening more than 2000 FDA approved drugsagainst Covid-19 virus main protease enzyme (Mpro) substrate-binding pocket to identify potential hits based on their binding energies, binding modes, interacting amino acids, and therapeutic indications. In addition, we elucidate preliminary pharmacophore features for candidates bound to Covid-19 virus Mpro substratebinding pocket. The top hits include anti-viral drugs such as Darunavir, Nelfinavirand Saquinavir, some of which are already being tested in Covid-19 patients. Interestingly, one of the most promising hits in our screen is the hypercholesterolemia drug Rosuvastatin. These results certainly do not confirm or indicate antiviral activity, but can rather be used as a starting point for further in vitro and in vivo testing, either individually or in combination.

AbstractTo identify potential therapeutic stop-gaps for SARS-CoV-2, we evaluated a library of 1,670 approved and reference compounds in an unbiased, cellular image-based screen for their ability to suppress the broad impacts of the SARS-CoV-2 virus on phenomic profiles of human renal cortical epithelial cells using deep learning. In our assay, remdesivir is the only antiviral tested with strong efficacy, neither chloroquine nor hydroxychloroquine have any beneficial effect in this human cell model, and a small number of compounds not currently being pursued clinically for SARS-CoV-2 have efficacy. We observed weak but beneficial class effects of β-blockers, mTOR/PI3K inhibitors and Vitamin D analogues and a mild amplification of the viral phenotype with β-agonists.