Determining crucial genes associated with COVID-19 based on COPD Findings✶,✶✶

Sharma, Pooja; Pandey, Anuj Kumar; Bhattacharyya, Dhruba K.

doi:10.1016/j.compbiomed.2020.104126

Cited by 16 publications

(12 citation statements)

References 25 publications

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“…Moreover, a significant increase in expression of endothelial cell adhesion molecules e.g., intercellular adhesion molecule 1 ( ICAM1 ) in patients with severe COVID-19, is associated with COVID-19 severity and may cause coagulation disorders ( 168 ). Additionally, increased expression of ICAM1 in COVID-19 patients contributes to replication of SARS-CoV-2 and provides a favorable environment for its survival in humans ( 135 ). Therefore, ICAM1 protein can be considered a key target for treatment of COVID-19 patients ( 169 , 170 ).…”

Section: Discussionmentioning

confidence: 99%

“…The nuclear factor-kappa b subunit-1 (NFKB1), an important transcription factor belonging to the NF-kB family, stimulates transcription of proinflammatory cytokines such as IL6, TNF-a, and IL1 as well as chemokines such as IL8 (CXCL8), all with major roles in causing a COVID-19-induced cytokine storm (86,87,130,131). The inflammation regulator NFKB1 was significantly upregulated in response to SARS-CoV-2 infection; transcriptomic studies revealed its key role in regulation of differentially expressed genes (DEGs) between healthy individuals and patients with mild or severe COVID-19 (7,10,(132)(133)(134)(135)(136). Furthermore, by targeting NFKB1, miR-9 regulates inflammatory pathways related to COVID-19 pathogenesis (137).…”

Section: Blue Modulementioning

confidence: 99%

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Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

et al. 2021

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BackgroundThe recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.MethodsRNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.ResultsBased on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19’s main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.ConclusionThis study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.

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Section: Discussionmentioning

confidence: 99%

Section: Blue Modulementioning

confidence: 99%

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

et al. 2021

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“…ICAM1 is found in a significant proportion of bronchial asthma patients. ICAM1 offers a suitable atmosphere for the coronavirus to infiltrate and live inside the human nose (Winther et al, 2002;Sharma et al, 2021). Nagashima et al (2020) reported that COVID-19 endothelial cells overexpressed ICAM1 relative to controls, which might attract leukocytes (endotheliitis) and send intracellular signals leading to a pro-inflammatory state.…”

Section: Discussionmentioning

confidence: 99%

Network pharmacology and molecular docking-based investigations of Kochiae Fructus’s active phytomolecules, molecular targets, and pathways in treating COVID-19

Khan

Lee

2022

Front. Microbiol.

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COVID-19 disease is caused by SARS-CoV-2. Hyper-inflammation mediated by proinflammatory cytokines is humans’ primary etiology of SARS-CoV-2 infection. Kochiae Fructus is widely used in China as traditional Chinese medicine (TCM) to treat inflammatory diseases. Due to its anti-inflammatory properties, we hypothesized that Kochiae Fructus would be a promising therapeutic agent for COVID-19. The active phytomolecules, targets, and molecular pathways of Kochiae Fructus in treating COVID-19 have not been explored yet. Network pharmacology analysis was performed to determine the active phytomolecules, molecular targets, and pathways of Kochiae Fructus. The phytomolecules in Kochiae Fructus were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and their potential targets were predicted with the SwissTargetPrediction webserver. COVID-19-related targets were recovered from the GeneCards database. Intersecting targets were determined with the VENNY tool. The Protein-protein interaction (PPI) and Molecular Complex Detection (MCODE) network analyses were constructed using the Cytoscape software. Using the DAVID tool, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the intersecting targets. AutoDock Vina (version 1.2.0.) was used for molecular docking analysis. Six active phytomolecules and 165 their potential targets, 1,745 COVID-19-related targets, and 34 intersecting targets were identified. Network analysis determined 13 anti-COVID-19 core targets and three key active phytomolecules (Oleanolic acid, 9E,12Z-octadecadienoic acid, and 11,14-eicosadienoic acid). Three key pathways (pathways in cancer, the TNF signaling pathway, and lipid and atherosclerosis) and the top six anti-COVID-19 core targets (IL-6, PPARG, MAPK3, PTGS2, ICAM1, and MAPK1) were determined to be involved in the treatment of COVID-19 with active phytomolecules of Kochiae Fructus. Molecular docking analysis revealed that three key active phytomolecules of Kochiae Fructus had a regulatory effect on the identified anti-COVID-19 core targets. Hence, these findings offer a foundation for developing anti-COVID-19 drugs based on phytomolecules of Kochiae Fructus.

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“…We screened eight common immune target genes from nine Chinese medicine prescriptions. JUN, NFKBIA, and ICAM1 have been reported as key genes related to COVID-19 ( 26 ). ADRB2, FOS, and IL-6 were found to be associated with COVID-19 inflammation ( 27 – 29 ).…”

Section: Discussionmentioning

confidence: 99%

The Potential Bioactive Components of Nine TCM Prescriptions Against COVID-19 in Lung Cancer Were Explored Based on Network Pharmacology and Molecular Docking

Xiao

et al. 2022

Front. Med.

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ObjectiveThe purpose of this study was to screen active components and molecular targets of nine prescriptions recommended by the National Health Commission (NHC) of China by network pharmacology, and to explore the potential mechanism of the core active components against COVID-19 with molecular docking.MethodsDifferentially expressed genes of lung adenocarcinoma (LUAD) screened by edgeR analysis were overlapped with immune-related genes in MMPORT and COVID-19-related genes in GeneCards. The overlapped genes were also COVID-19 immune-related genes in LUAD. TCMSP platform was used to identify active ingredients of the prescription, potential targets were identified by the UniProt database, and the cross genes with COVID-19 immune-related genes in LUAD were used to construct a Chinese Medicine-Logy-immune target network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the target genes of each prescription. Finally, the key active components were selected for molecular docking simulation with ACE2.ResultsWe obtained 15 overlapping immunization target genes from FPQXZ, HSYFZ, HSZFZ, and QFPDT, 16 overlapping immunization target genes from QYLFZ, SDYFZ, SRYFZ, and YDBFZ, and 17 overlapping immunization target genes from QYLXZ. ADRB2, FOS, HMOX1, ICAM1, IL6, JUN, NFKBIA, and STAT1 also had the highest-ranked therapeutic targets for 9 prescriptions, and their expressions were positively correlated with TME-related stromal score, immune score, and ESTIMATE score. Among 9 compounds with the highest frequency of occurrence in the 9 prescriptions, baicalein had the highest ACE2 binding affinity and can be well-combined into the active pocket of ACE2 It is stabilized by forming hydrogen bonds with ASN290 and ILE291 in ACE2 and hydrophobic interaction with PHE438, ILE291, and PRO415.ConclusionThe nine Chinese medicine prescriptions may play an anti-SARS-CoV-2 role via regulating viral transcription and immune function through multi-component, multi-target, and multi-pathway.

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Determining crucial genes associated with COVID-19 based on COPD Findings✶,✶✶

Cited by 16 publications

References 25 publications

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

Network pharmacology and molecular docking-based investigations of Kochiae Fructus’s active phytomolecules, molecular targets, and pathways in treating COVID-19

The Potential Bioactive Components of Nine TCM Prescriptions Against COVID-19 in Lung Cancer Were Explored Based on Network Pharmacology and Molecular Docking

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