Objective: Severe cases of coronavirus disease 2019 (COVID-19) are expected to have a worse prognosis than mild cases. Shenhuang Granule (SHG) has been shown to be a safe and effective treatment for severe COVID-19 in a previous randomized clinical trial, but the active chemical constituents and underlying mechanisms of action remain unknown. The goal of this study is to explore the chemical basis and mechanisms of SHG in the treatment of severe COVID-19, using network pharmacology.
Methods: Ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry was employed to screen chemical constituents of SHG. Putative therapeutic targets were predicted by searching traditional Chinese medicine system pharmacology database and analysis platform, SwissTargetPrediction, and Gene Expression Omnibus (GEO) databases. The target protein-protein interaction network and enrichment analysis were performed to investigate the hub genes and presumptive mechanisms. Molecular docking and molecular dynamics simulations were used to verify the stability and interaction between the key chemical constituents of SHG and COVID-19 protein targets.
Results: Forty-five chemical constituents of SHG were identified along with 131 corresponding therapeutic targets, including hub genes such as HSP90AA1, MMP9, CXCL8, PTGS2, IFNG, DNMT1, TYMS, MDM2, HDAC3 and ABCB1. Functional enrichment analysis indicated that SHG mainly acted on the neuroactive ligand-receptor interaction, calcium signaling pathway and cAMP signaling pathway. Molecular docking showed that the key constituents had a good affinity with the severe acute respiratory syndrome coronavirus 2 protein targets. Molecular dynamics simulations indicated that ginsenoside Rg4 formed a stable protein-ligand complex with helicase.
Conclusion: Multiple components of SHG regulated multiple targets to inhibit virus invasion and cytokine storm through several signaling pathways; this provides a scientific basis for clinical applications and further experiments.

Key words: COVID-19, SARS-CoV-2, Shenhuang Granule, Mechanism, Network pharmacology, Molecular docking, Molecular dynamics simulation