Two-dimensional transition metal carbides/carbonitrides known as MXenes are rapidly growing as multimodal nanoplatforms in biomedicine. Here, taking SARS-CoV-2 as a model, we explored the antiviral properties and immune-profile of a large panel of four highly stable and well-characterized MXenes - Ti 3 C 2 T x , Ta 4 C 3 T x , Mo 2 Ti 2 C 3 T x and Nb 4 C 3 T x . To start with antiviral assessment, we first selected and deeply analyzed four different SARS-CoV-2 genotypes, common in most countries and carrying the wild type or mutated spike protein. When inhibition of the viral infection was tested in vitro with four viral clades, Ti 3 C 2 T x in particular, was able to significantly reduce infection only in SARS-CoV-2/clade GR infected Vero E6 cells. This difference in the antiviral activity, among the four viral particles tested, highlights the importance of considering the viral genotypes and mutations while testing antiviral activity of potential drugs and nanomaterials. Among the other MXenes tested, Mo 2 Ti 2 C 3 T x also showed antiviral properties. Proteomic, functional annotation analysis and comparison to the already published SARS-CoV-2 protein interaction map revealed that MXene-treatment exerts specific inhibitory mechanisms. Envisaging future antiviral MXene-based drug nano-formulations and considering the central importance of the immune response to viral infections, the immune impact of MXenes was evaluated on human primary immune cells by flow cytometry and single-cell mass cytometry on 17 distinct immune subpopulations. Moreover, 40 secreted cytokines were analyzed by Luminex technology. MXene immune profiling revealed i) the excellent bio and immune compatibility of the material, as well as the ability of MXene ii) to inhibit monocytes and iii) to reduce the release of pro-inflammatory cytokines, suggesting an anti-inflammatory effect elicited by MXene. We here report a selection of MXenes and viral SARS-CoV-2 genotypes/mutations, a series of the computational, structural and molecular data depicting deeply the SARS-CoV-2 mechanism of inhibition, as well as high dimensional single-cell immune-MXene profiling. Taken together, our results provide a compendium of knowledge for new developments of MXene-based multi-functioning nanosystems as antivirals and immune-modulators.

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Ribavirin is a guanosine analog and has a broad-spectrum antiviral activity against RNA viruses. Based on this, we aimed to show the anti-SARS-CoV-2 activity of this drug molecule via in vitro, in silico and molecular techniques. Ribavirin showed antiviral activity in Vero E6 cells following SARS-CoV-2 infection whereas the drug itself did not show any toxic effect over the concentration range tested. In silico analysis suggested that Ribarivin has a broad-spectrum impact on SARS-CoV-2, acting at different viral proteins. According to the detailed molecular techniques, Ribavirin was shown to decrease the expression of TMPRSS2 both at mRNA and protein levels 48 hours after treatment. The suppressive effect of Ribavirin in ACE2 protein expression was shown to be dependent on cell types. Finally, proteolytic activity assays showed that Ribavirin also showed an inhibitory effect on TMPRSS2 enzyme. Based on these results, we hypothesized that Ribavirin may inhibit the expression of TMPRSS2 by modulating the formation of inhibitory G-quadruplex structures at the TMPRSS2 promoter. As a conclusion, Ribavirin is a potential antiviral drug for the treatment against SARS-CoV-2, and it interferes with the effect of TMPRSS2 and ACE2 expression.

Ribavirin is a guanosine analog and has a broad-spectrum antiviral activity against RNA viruses. Based on this, we aimed to show the anti-SARS-CoV-2 activity of this drug molecule via in vitro, in silico and molecular techniques. Ribavirin showed antiviral activity in Vero E6 cells following SARS-CoV-2 infection. In silico analysis suggested that Ribarivin has a broad-spectrum impact on Vero E6 cells. According to the detailed molecular techniques, Ribavirin was shown to decrease TMPRSS2 expression both at mRNA and protein level 48 hours after treatment. The suppressive effect of Ribavirin in ACE2 protein expression was shown to be dependent on cell types. Finally, proteolytic activity assays showed that Ribavirin also showed an inhibitory effect on TMPRSS2 enzyme. As a conclusion, Ribavirin is a potential antiviral drug for the treatment against SARS-CoV-2, and it interferes with the effect of TMPRSS2 and ACE2 expression.

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.