Emerging nanomaterials applied for tackling the COVID-19 cytokine storm

COVID-19 Virus Structural Details: Optical and Electrochemical Detection

The increasing viral species have ruined people's health and the world's economy. Therefore, it is urgent to design bio-responsive materials to provide a vast platform for detecting a different family's passive or active virus. One can design a reactive functional unit for that moiety based on the particular bio-active moieties in viruses. Nanomaterials as optical and electrochemical biosensors have enabled better tools and devices to develop rapid virus detection. Various material science platforms are available for real-time monitoring and detecting COVID-19 and other viral loads. In this review, we discuss the recent advances of nanomaterials in developing the tools for optical and electrochemical sensing COVID-19. In addition, nanomaterials used to detect other human viruses have been studied, providing insights for developing COVID-19 sensing materials. The basic strategies for nanomaterials develop as virus sensors, fabrications, and detection performances are studied. Moreover, the new methods to enhance the virus sensing properties are discussed to provide a gateway for virus detection in variant forms. The study will provide systematic information and working of virus sensors. In addition, the deep discussion of structural properties and signal changes will offer a new gate for researchers to develop new virus sensors for clinical applications.

Functionalized SPION immobilized on graphene-oxide: Anticancer and antiviral study

The progressive and fatal outbreak of some diseases such as cancer and coronavirus necessitates using advanced materials to bring such devastating illnesses under control. In this study, graphene oxide (GO) is decorated by superparamagnetic iron oxide nanoparticles (SPION) (GO/SPION) as well as polyethylene glycol functionalized SPION (GO/SPION@PEG), and chitosan functionalized SPION (GO/SPION@CS). Field emission scanning electron microscopic (FESEM) images show the formation of high density uniformly distributed SPION nanoparticles on the surface of GO sheets. The structural and chemical composition of nanostructures is confirmed by X-ray diffraction and Fourier transform infrared spectroscopy. The saturation magnetization of GO/SPION, GO/SPION@PEG and GO- SPION@CS are found to be 20, 19 and 8 emu/g using vibrating sample magnetometer. Specific absorption rate (SAR) values of 305, 283, and 199 W/g and corresponding intrinsic loss power (ILP) values of 9.4, 8.7, and 6.2 nHm²kg^-1 are achieved for GO/SPION, GO/SPION@PEG and GO/SPION@CS, respectively. The In vitro cytotoxicity assay indicates higher than 70% cell viability for all nanostructures at 100, 300, and 500 ppm after 24 and 72 h. Additionally, cancerous cell (EJ138 human bladder carcinoma) ablation is observed using functionalized GO/SPION under applied magnetic field. More than 50% cancerous cell death has been achieved for GO/SPION@PEG at 300 ppm concentration. Furthermore, Surrogate virus neutralization test is applied to investigate neutralizing property of the synthesized nanostructures through analysis of SARS-CoV-2 receptor-binding domain and human angiotensin-converting enzyme 2 binding. The highest level of SARS-CoV-2 virus inhibition is related to GO/SPION@CS (86%) due to the synergistic exploitation of GO and chitosan. Thus, GO/SPION and GO/SPION@PEG with higher SAR and ILP values could be beneficial for cancer treatment, while GO/SPION@CS with higher virus suppression has potential to use against coronaviruses. Thus, the developed nanocomposites have a potential in the efficient treatment of cancer and coronavirus.

Glycyrrhetinic acid: A potential drug for the treatment of COVID-19 cytokine storm

BACKGROUND

The cytokine storm (CS) triggered by coronavirus disease 2019 (COVID-19) has caused serious harm to health of humanity and huge economic burden to the world, and there is a lack of effective methods to treat this complication.

PURPOSE

In this research, we used network pharmacology and molecular docking to reveal the interaction mechanism in the glycyrrhetinic acid (GA) for the treatment of CS, and validated the effect of GA intervention CS by experiments.

STUDY DESIGN

First, we screened corresponding target of GA and CS from online databases, and obtained the action target genes through the Venn diagram. Then, protein-protein interaction (PPI) network, Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the action target genes were acquired by R language to predict its mechanism. Next, molecular docking was performed on core targets. Finally, experiments in which GA intervened in lipopolysaccharide (LPS)-induced CS were implemented.

RESULTS

84 action target genes were obtained from online database. The PPI network of target genes showed that TNF, IL6, MAPK3, PTGS2, ESR1 and PPARG were considered as the core genes. The results of GO and KEGG showed that action target genes were closely related to inflammatory and immune related signaling pathways, such as TNF signaling pathway, IL-17 signaling pathway, Human cytomegalovirus infection, PPAR signaling pathway and so on. Molecule docking results prompted that GA had fine affinity with IL6 and TNF proteins. Finally, in vivo and in vitro experimental results showed that GA could significantly inhibit LPS-induced CS.

CONCLUSION

GA has a potential inhibitory effect on CS, which is worthy of further exploration.

Inspiration for COVID-19 Treatment: Network Analysis and Experimental Validation of Baicalin for Cytokine Storm

Background: Cytokine storm (CS) is a systemic inflammatory syndrome and a major cause of multi-organ failure and even death in COVID-19 patients. With the increasing number of COVID-19 patients, there is an urgent need to develop effective therapeutic strategies for CS. Baicalin is an anti-inflammatory and antiviral traditional Chinese medicine. In the present study, we aimed to evaluate the therapeutic mechanism of baicalin against CS through network analysis and experimental validation, and to detect key targets of CS that may bind closely to baicalin through molecular docking.

Method: Access to potential targets of baicalin and CS in public databases. We constructed the protein-protein interaction (PPI) network of baicalin and CS by Cytoscape 9.0 software and performed network topology analysis of the potential targets. Then, the hub target was identified by molecular docking technique and validated in the CS model. Finally, GO and KEGG pathway functional enrichment analysis of common targets were confirmed using R language, and the location of overlapping targets in key pathways was queried via KEGG Mapper.

Result: A total of 86 overlapping targets of baicalin and CS were identified, among which MAPK14, IL2, FGF2, CASP3, PTGS2, PIK3CA, EGFR, and TNF were the core targets. Moreover, it was found that baicalin bound most closely to TNF through molecular docking, and demonstrated that baicalin can effectively inhibit the elevation of TNF-α in vitro and in vivo. Furthermore, bioenrichment analysis revealed that the TNF signaling pathway and IL-17 signaling pathway may be potential key pathways for baicalin to treat CS.

Conclusion: Based on this study, baicalin was identified as a potential drug for the alleviation of CS, and the possible key targets and pathways of baicalin for the treatment of CS were elucidated to reveal the main pharmacological mechanisms.