Methotrexate inhibition of SARS-CoV-2 entry, infection and inflammation revealed by bioinformatics approach and a hamster model

Blood transcriptome analysis uncovered COVID-19-myocarditis crosstalk

BACKGROUND

The condition of COVID-19-related myocarditis has emerged as a prominent contributor to COVID-19 mortality. As the epidemic persists, its incidence continues to rise. Despite ongoing efforts, the elucidation of COVID-19-related myocarditis underlying molecular mechanisms still requires further investigation.

METHODS

Hub genes for COVID-19-related myocarditis were screened by integrating gene expression profile analysis via differential expression in COVID-19 (GSE196822) and myocarditis (GSE148153 and GSE147517). After verification with independent datasets (GSE211979, GSE167028, GSE178491 and GSE215865), the hub genes were studied using a range of systems-biology approaches, such as ceRNA, TF-mRNA networks and PPI networks, as well as gene ontology, pathway enrichment, immune infiltration analysis and drug target identification.

RESULTS

TBKBP1 and ERGIC1 were identified as COVID-19-related myocarditis hub genes via integrated bioinformatics analysis. In addition, receiver operating characteristic curves constructed based on the expression levels of TBKBP1 and ERGIC1 could effectively distinguish healthy control individuals from patients with COVID-19. Functional enrichment analysis suggested several enriched biological pathways related to inflammation and immune response. Immune cell changes correlated with TBKBP1 and ERGIC1 levels in patients with COVID-19 or patients with COVID-19 and myocarditis. Tamibarotene, methotrexate and theophylline were identified as a potential drug targeting TBKBP1 and ERGIC1.

CONCLUSION

TBKBP1 and ERGIC1 were identified as crucial genes in the development of COVID-19-related myocarditis and have demonstrated a strong association with innate antiviral immunity. The present work may be helpful for further investigation of the molecular mechanisms and new therapeutic drug targets correlated with myocarditis in COVID-19.

Methotrexate Inhibits the Binding of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Receptor Binding Domain to the Host-Cell Angiotensin-Converting Enzyme-2 (ACE-2) Receptor

As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus mutates, finding effective drugs becomes more challenging. In this study, we use ultrasensitive frequency locked microtoroid optical resonators in combination with in silico screening to search for COVID-19 drugs that can stop the virus from attaching to the human angiotensin-converting enzyme 2 (hACE2) receptor in the lungs. We found 29 promising candidates that could block the binding site and selected four of them that were likely to bind very strongly. We tested three of these candidates using frequency locked optical whispering evanescent resonator (FLOWER), a label-free sensing method based on microtoroid resonators. FLOWER has previously been used for sensing single macromolecules. Here we show, for the first time, that FLOWER can provide accurate binding affinities and sense the inhibition effect of small molecule drug candidates without labels, which can be prohibitive in drug discovery. One of the candidates, methotrexate, showed binding to the spike protein 1.8 million times greater than that to the receptor binding domain (RBD) binding to hACE2, making it difficult for the virus to enter cells. We tested methotrexate against different variants of the SARS-CoV-2 virus and found that it is effective against all four of the tested variants. People taking methotrexate for other conditions have also shown protection against the original SARS-CoV-2 virus. Normally, it is assumed that methotrexate inhibits the replication and release of the virus. However, our findings suggest that it may also block the virus from entering cells. These studies additionally demonstrate the possibility of extracting candidate ligands from large databases, followed by direct receptor-ligand binding experiments on the best candidates using microtoroid resonators, thus creating a workflow that enables the rapid discovery of new drug candidates for a variety of applications.