Network Pharmacology Study to Elucidate the Key Targets of Underlying Antihistamines against COVID-19.

Antihistamines have potent efficacy to alleviate COVID-19 (Coronavirus disease 2019) symptoms such as anti-inflammation and as a pain reliever. However, the pharmacological mechanism(s), key target(s), and drug(s) are not documented well against COVID-19. Thus, we investigated to decipher the most significant components and how its research methodology was utilized by network pharmacology. The list of 32 common antihistamines on the market were retrieved via drug browsing databases. The targets associated with the selected antihistamines and the targets that responded to COVID-19 infection were identified by the Similarity Ensemble Approach (SEA), SwissTargetPrediction (STP), and PubChem, respectively. We described bubble charts, the Pathways-Targets-Antihistamines (PTA) network, and the protein-protein interaction (PPI) network on the RPackage via STRING database. Furthermore, we utilized the AutoDock Tools software to perform molecular docking tests (MDT) on the key targets and drugs to evaluate the network pharmacological perspective. The final 15 targets were identified as core targets, indicating that Neuroactive ligand-receptor interaction might be the hub-signaling pathway of antihistamines on COVID-19 via bubble chart. The PTA network was constructed by the RPackage, which identified 7 pathways, 11 targets, and 30 drugs. In addition, GRIN2B, a key target, was identified via topological analysis of the PPI network. Finally, we observed that the GRIN2B-Loratidine complex was the most stable docking score with -7.3 kcal/mol through molecular docking test. Our results showed that Loratadine might exert as an antagonist on GRIN2B via the neuroactive ligand-receptor interaction pathway. To sum up, we elucidated the most potential antihistamine, a key target, and a key pharmacological pathway as alleviating components against COVID-19, supporting scientific evidence for further research.

The Promising Mechanisms of Low Molecular Weight Compounds of Panax Ginseng C.A. Meyer in Alleviating COVID-19: A Network Pharmacology Analysis

Panax Ginseng C.A. Meyer (PGCAM) is a well-known phytomedicine, but most of its compounds, such as ginsenoside derivatives, have poor absorption and bioavailability profile due to high molecular weight (≥500 Daltons), which is the major hurdle for their clinical application. Hence, this research explored the efficiency of low molecular weight compounds (LMWCs) (<500 Daltons) screened from PGCAM and their anti-COVID-19 mechanisms through network pharmacology. Molecular compounds from PGCAM were identified using public databases and filtered out by the drug-likeness evaluation. Genes interacted with these filtered compounds, and COVID-19-related genes were extracted from public databases. In addition, overlapping genes between compounds and interactive genes were identified using the Venn diagram. In parallel, the networking between compounds and overlapping genes was analyzed by RStudio. The pathway enrichment analysis of overlapping genes was determined by STRING. Finally, the key bioactive compounds were documented through virtual screening. The bubble chart suggested that the mechanisms of PGCAM against COVID-19 were related to 28 signaling pathways. The key molecular anti-COVID-19 mechanisms might be the anti-inflammation, anti-permeability, and pro-apoptosis by inactivating the PI3K-Akt signaling pathway. The six key genes and the five compounds related to the PI3K-Akt signaling pathway were RELA-paeonol, NFKB1-frutinone A, IL6-nepetin, MCL1-ramalic acid, VEGFA-trifolirhizin, and IL2-trifolirhizin. The docking between these key genes and compounds demonstrated promising binding affinity with a good binding score. Overall, our proposed LMWCs from PGCAM provide a fundamental basis with noteworthy pharmacological evidence to support the therapeutic efficacy of PGCAM in relieving the main symptoms of COVID-19.

Drug-repurposing against COVID-19 by targeting a key signaling pathway: An in silico study.

Currently, a plethora of information has been accumulated concerning COVID-19, including the transmission pathway of SARs-CoV-2. Thus, we retrieved targets associated with the development of COVID-19 via PubChem. A total of 517 targets were identified, and signaling pathways responded after infection of SARs-CoV-2 in humans constructed a bubble chart using RPackage. The bubble chart result suggested that the key signaling pathway against COVID-19 was the estrogen signaling pathway associated with AKT1, HSP90AB1, BCL2 targets. The three targets have the strongest affinity with three ligands-Akti-1/2, HSP990, S55746, respectively. In conclusion, this work provides three key elements to alleviate COVID-19 symptoms might be anti-inflammatory effects on SARs-CoV-2-infected lung cells.

Network pharmacology approach to decipher signaling pathways associated with target proteins of NSAIDs against COVID-19.

Non-steroidal anti-inflammatory drugs (NSAIDs) showed promising clinical efficacy toward COVID-19 (Coronavirus disease 2019) patients as potent painkillers and anti-inflammatory agents. However, the prospective anti-COVID-19 mechanisms of NSAIDs are not evidently exposed. Therefore, we intended to decipher the most influential NSAIDs candidate(s) and its novel mechanism(s) against COVID-19 by network pharmacology. FDA (U.S. Food & Drug Administration) approved NSAIDs (19 active drugs and one prodrug) were used for this study. Target proteins related to selected NSAIDs and COVID-19 related target proteins were identified by the Similarity Ensemble Approach, Swiss Target Prediction, and PubChem databases, respectively. Venn diagram identified overlapping target proteins between NSAIDs and COVID-19 related target proteins. The interactive networking between NSAIDs and overlapping target proteins was analyzed by STRING. RStudio plotted the bubble chart of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of overlapping target proteins. Finally, the binding affinity of NSAIDs against target proteins was determined through molecular docking test (MDT). Geneset enrichment analysis exhibited 26 signaling pathways against COVID-19. Inhibition of proinflammatory stimuli of tissues and/or cells by inactivating the RAS signaling pathway was identified as the key anti-COVID-19 mechanism of NSAIDs. Besides, MAPK8, MAPK10, and BAD target proteins were explored as the associated target proteins of the RAS. Among twenty NSAIDs, 6MNA, Rofecoxib, and Indomethacin revealed promising binding affinity with the highest docking score against three identified target proteins, respectively. Overall, our proposed three NSAIDs (6MNA, Rofecoxib, and Indomethacin) might block the RAS by inactivating its associated target proteins, thus may alleviate excessive inflammation induced by SARS-CoV-2.