Evaluation of the Genes and Molecular Pathways Involved in Skin Lesions in Patients with COVID-19: Systems Biology and Bioinformatics Analysis Approach

Background: Coronavirus disease 2019 (COVID-19) was first identified in 2019 in Wuhan, China. Initially, although the number of COVID-19-infected individuals was very low, the infected cases increased as the virus spread worldwide. Skin manifestation is one of the symptoms observed in COVID-19 patients. Objectives: This study investigated the critical genes and molecular pathways involved in skin manifestations in COVID-19 patients through a biological system approach. Methods: In this study, the microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database and analyzed for identifying differentially expressed genes (DEGs). The enrichment analysis of DEGs was evaluated using the DAVID database. Afterward, protein-protein interaction (PPI) networks were constructed via the STRING database and visualized using Cytoscape software. The hub genes were recognized using the cytoHubba. The interaction of the microRNA (miRNA)-hub genes, transcription factor (TF)-hub genes, and drug-hub genes was also evaluated in this study. Results: After analysis, some genes with the highest degree of connectivity, which were involved in the pathogenesis of HELLP syndrome were identified, and they were known as hub genes. These genes are as follows: IFN-gamma CXCL1, CCL2, CCL3, TLR2, IL-1B, CXCL6, IL-6, CCL4, and CXCL2. has-mir-34a-5p, has-mir-20a-5p, and has-mir-27a-3p as miRNA, as well as RELA as TF had the most interaction with the hub genes. Conclusion: Finally, IL-6 and CXCL10 that were compared to the other hub genes had the highest interaction with other genes;therefore, their role in Shamgir's pathogenesis is significant. Targeting the cited genes would be a strategy to prevent symptom manifestation and better patient management.

Exploring the Potential Mechanism of Action of Ursolic Acid against Gastric Cancer and COVID-19 using Network Pharmacology and Bioinformatics Analysis.

BACKGROUND: Patients with gastric cancer (GC) are more likely to be infected with 2019 coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the prognosis is worse. It is urgent to find effective treatment methods. OBJECTIVE: This study aimed to explore the potential targets and mechanism of ursolic acid (UA) on GC and COVID-19 by network pharmacology and bioinformatics analysis. METHODS: The online public database and weighted co-expression gene network analysis (WGCNA) were used to screen the clinical related targets of GC. COVID-19-related targets were retrieved from online public databases. Then, a clinicopathological analysis was performed on GC and COVID-19 intersection genes. Following that, the related targets of UA and the intersection targets of UA and GC/COVID-19 were screened. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome Analysis (KEGG) pathway enrichment analyses were performed on the intersection targets. Core targets were screened using a constructed protein-protein interaction network. Finally, molecular docking and molecular dynamics simulation (MDS) of UA and core targets were performed to verify the accuracy of the prediction results. RESULTS: A total of 347 GC/COVID-19-related genes were obtained. The clinical features of GC/COVID-19 patients were revealed using clinicopathological analysis. Three potential biomarkers (TRIM25, CD59, MAPK14) associated with the clinical prognosis of GC/COVID-19 were identified. A total of 32 intersection targets of UA and GC/COVID-19 were obtained. The intersection targets were primarily enriched in FoxO, PI3K/Akt, and ErbB signaling pathways. HSP90AA1, CTNNB1, MTOR, SIRT1, MAPK1, MAPK14, PARP1, MAP2K1, HSPA8, EZH2, PTPN11, and CDK2 were identified as core targets. Molecular docking revealed that UA strongly binds to its core targets. The MDS results revealed that UA stabilizes the protein-ligand complexes of PARP1, MAPK14, and ACE2. CONCLUSION: This study found that in patients with gastric cancer and COVID-19, UA may bind to ACE2, regulate core targets such as PARP1 and MAPK14, and the PI3K/Akt signaling pathway, and participate in antiinflammatory, anti-oxidation, anti-virus, and immune regulation to exert therapeutic effects.

The Mechanisms of Luteolin in Treating COVID-19 Based on Bioinformatics Analysis and Molecular Docking

Luteolin is a natural flavonoid that has a variety of pharmacological activities, such as anti-inflammatory, anti-allergic, anti-bacterial, anti-viral, apoptosis inhibition, cell autophagy regulation, and anti-tumor activity. It is one of the main ingredients of an expert-recommended herbal formula for the prevention and treatment of coronavirus disease 2019 (COVID-19). This suggests that luteolin has strong pharmacological effects on the prevention and treatment of COVID-19. The aims of this study were to identify the molecular targets of luteolin and to infer the possible mechanisms by which it exerts its pharmacological effects. The GSE159787 data set was obtained from the Gene Expression Omnibus online database, and differentially expressed genes were analyzed. There were 22 upregulated differentially expressed genes enriched in the COVID-19 signaling pathway, suggesting that the upregulation of these genes may be closely related to the occurrence of COVID-19. Molecular docking results showed that luteolin had strong binding efficiency to 20 of these 22 key genes. Six of these genes (CFB, EIF2AK2, OAS1, MAPK11, OAS3, and STAT1) showed strong binding activity. Luteolin can regulate the COVID-19 signaling pathway by combining with these targets, which may have a therapeutic effect on COVID-19. © Wolters Kluwer Health, Inc. All rights reserved.

Potential Mechanism of Colchicine against COVID-19 and Non-Small Cell Lung Cancer based on Network Pharmacology and Bioinformatics Analysis

Colchicine is an alkaloid with antitumor effect isolated from Colchicum autumnale plants, it has been reported in multiple studies as a potential treatment for coronavirus disease-19 and this study applied network pharmacology and bioinformatics analysis to explore the potential mechanism of colchicine against non-small cell lung cancer and coronavirus disease-19. The R software was used to determine the differentially expressed genes of non-small cell lung cancer/coronavirus disease-19, and carry out prognostic analysis and clinical analysis of the differentially expressed genes, the targets of colchicine were obtained from various databases, the protein-protein interaction network of intersection targets of colchicine and non-small cell lung cancer/coronavirus disease-19 was constructed, enrichment analysis of gene ontology and kyoto encyclopedia of genes and genomes pathways was performed by Metascape database and the molecular docking and molecular dynamics simulation were completed. We obtained a total of 716 differentially expressed genes and identified 13 potential prognostic genes associated with the clinical characterization of non-small cell lung cancer/coronavirus disease-19 patients. C-C motif chemokine ligand 2, toll like receptor 4, intercellular adhesion molecule 1, peroxisome proliferator activated receptor gamma, interleukin 17A, interferon gamma, angiotensin I converting enzyme, fos proto-oncogene, nuclear factor kappa B inhibitor alpha, TIMP metallopeptidase inhibitor 1 and secreted phosphoprotein 1 were core targets. The intersection targets of colchicine and non-small cell lung cancer/coronavirus disease-19 were mainly enriched in biological processes such as inflammatory response, response to cytokine and response to lipopolysaccharide, as well as signal pathways such as interleukin 17 signaling pathway, hypoxia inducible factor 1 signaling pathway and nucleotide binding oligomerization domain-like receptor signaling pathway. The results of molecular docking showed that the colchicine is better combined with the core targets. Analysis of molecular dynamics simulation showed that the protein and ligand form a stabilizing effect. Based on bioinformatics analysis and network pharmacology, we obtained biomarkers that may be used for the prognosis of non-small cell lung cancer/coronavirus disease-19 patients and revealed that colchicine may play a potential role in the treatment of non-small cell lung cancer/coronavirus disease-19 by regulating multiple targets and multiple signaling pathways and participating in multiple biological processes.

Exploration of Potential Biomarkers and Mechanisms for COVID-19 and Asthma Based on Microarray Analysis

Aims: The aim of this study is to investigate the potential mechanisms of coronavirus disease (COVID-19) and asthma comor-bidities.Methods: GSE147507 and GSE143303 datasets were obtained from the Gene Expression Omnibus (GEO) database, the differ-ential expressed genes (DEGs) were identified, and the overlapping DEGs were obtained by determining the DEG intersection between the two datasets. A series of analyses of the shared DEGs were performed, including enrichment analysis, protein -protein interaction (PPI) network construction, construction of transcription factor (TF)/microRNA (miRNA)-gene interaction networks, drug-gene and disease-gene interactions, and receiver operating characteristic curve (ROC) analysis.Results: A total of 135 overlapping DEGs were obtained by determining the DEGs intersection between the GSE147507 and GSE143303 datasets. These overlapped DEGs were significantly enriched in the regulation of DNA-templated transcription, initi-ation, clathrin-sculpted gamma-aminobutyric acid transport vesicle, DNA binding, and eight KEGG (kyoto encyclopedia of genes and genomes) pathways. The PPI network revealed that HSPA8, SRSF1, NDUFAB1, PTEN, CCT8, HIST1H2BK, HIST2H2BE, DLAT, EIF3G, and WAC, with high scores, were the hub genes. In addition, 65 TFs (transcription factors) and 369 miRNAs tar-geted overlapping DEGs. Finally, these overlapped DEGs were also related to other diseases, such as hyperglycemia, metabolic acidosis, and lung neoplasm, and the top 10 drugs with the most significant potential included lanatoside C, digoxin, GW-8510, doxorubicin, daunorubicin, proscillaridin, anisomycin, helveticoside, ouabain, and bisacodyl. The ROC analysis results shown that these hub genes had good diagnostic performance.Conclusions: HSPA8, SRSF1, NDUFAB1, PTEN, CCT8, HIST1H2BK, HIST2H2BE, DLAT, EIF3G, WAC, FOXC1, GATA2, hsa-miR-93-5p, and hsa-miR-17-5p may play vital roles in COVID-19 (corona virus disease-2019)/asthma comorbidity. Lanatoside C, digoxin, GW-8510, doxorubicin, daunorubicin, proscillaridin, anisomycin, helveticoside, ouabain, and bisacodyl may serve as drug targets against COVID-19/asthma comorbidity.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis.

BACKGROUND: Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF. METHODS: We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes. RESULTS: A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B). CONCLUSIONS: This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

A Note on the Potential BCG Vaccination - COVID-19 Molecular Link

Objective: Our goal was to elucidate a potential molecular link between the past and current tuberculosis vaccine Bacillus Calmette-Guerin (BCG;a live attenuated strain of Mycobacterium bovis) immunization policies and COVID-19. Method(s): Our sequence homology analyses have demonstrated that there is an intriguing level of sequence homology between a few of the BCG and Sars-CoV-2 proteins. Result(s): The data suggest that the BCG-specific memory B-cells that are preserved in BCG-vaccinated patients cross-recognize SARS-CoV-2 and that this cross-recognition may affect the virus proliferation and COVID-19 severity. Conclusion(s): Our results can stimulate the sharply focused follow-up experimental studies.Copyright © 2020 Bentham Science Publishers.

Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases.

Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China. Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes' protein expression levels. Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC. Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.

Immunopharmacological Activities of Luteolin in Chronic Diseases.

Flavonoids have been shown to have anti-oxidative effects, as well as other health benefits (e.g., anti-inflammatory and anti-tumor functions). Luteolin (3', 4', 5,7-tetrahydroxyflavone) is a flavonoid found in vegetables, fruits, flowers, and herbs, including celery, broccoli, green pepper, navel oranges, dandelion, peppermint, and rosemary. Luteolin has multiple useful effects, especially in regulating inflammation-related symptoms and diseases. In this paper, we summarize the studies about the immunopharmacological activity of luteolin on anti-inflammatory, anti-cardiovascular, anti-cancerous, and anti-neurodegenerative diseases published since 2018 and available in PubMed or Google Scholar. In this review, we also introduce some additional formulations of luteolin to improve its solubility and bioavailability.

Identification of differentially expressed genes and pathways in kidney of ANCA-associated vasculitis by integrated bioinformatics analysis.

The antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a systematic of relatively rare autoimmune diseases with unknown cause. Kidney involvement is one of the most common clinical manifestations, and the degree of renal damage is closely associated with the development and prognosis of AAV. In this study, we utilized the Robust Rank Aggreg (RRA) method in R to integrate GSE104948, GSE104954, GSE108109, GSE108112, and GSE108113 profile datasets loaded from Gene Expression Omnibus (GEO) database and identified a set of differentially expressed genes (DEGs) in kidney between AAV patients and living donors. Then, the results of gene ontology (GO) functional annotation showed that immunity and metabolism involved process of AAV both in glomerulus and tubulointerstitial. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that following pathways, such as complement and coagulation cascades pathway; Staphylococcus aureus infection; disease-COVID-19; and systemic lupus erythematosus (SLE) pathway play a crucial role in AAV. Next, the results analyzed by protein-protein interaction (PPI) network and Cytoscape software exhibited the hub genes ALB, TYROBP, and CYBB existed in both glomerular and tubulointerstitial compartments datasets. Finally, KEGG analysis using genes of two most important modules also further validated complement and coagulation cascades pathway and S. aureus infection existed both in glomerulus and tubulointerstitial compartments datasets. In conclusion, this study identified key genes and pathways involved in kidney of AAV, which was benefit to further uncover the mechanisms underlying the development and progress of AAV, biomarkers, and potential therapeutic targets as well.

Study on college students' willingness to inoculate COVID-19 vaccine based on bioinformatics and KAP analysis.

Bioinformatics is a subject that analyzes and interprets the collection, processing, storage and dissemination of biological information, and explores biological problems by using information technology and related means. The outbreak of novel coronavirus pneumonia has been nearly three years. With the advancement of vaccine research and development in various countries, mass vaccination is bound to usher in a new turning point for epidemic control. China's policy of free vaccination for the new coronavirus vaccine will undoubtedly improve the vaccination rate, however, the vaccination rate still depends on people's will. This paper takes college students as the main research object. In the context of bioinformatics analysis, a questionnaire survey was conducted based on their knowledge, attitudes, and practice levels of COVID-19 vaccines. The results vividly illustrate five conclusions. Firstly, the reliability of information sources positively affected college students' cognitive level, degree of trust and inoculation intention of COVID-19 vaccination. Secondly, the professional degree of media positively affected college students' degree of trust and inoculation intention behavior of COVID-19 vaccine. Thirdly, the cognitive level and degree of trust about COVID-19 vaccine positively affected college students' intention behavior of COVID-19 vaccine vaccination. Fourthly, the positivity of information positively affected the willingness of college students to vaccinate against COVID-19 vaccine. Fifthly, there were significant differences in the willingness and behavior of college students with different genders in COVID-19 vaccination. Finally, three suggestions are given to improve college students' willingness to vaccinate against the coronavirus and to cope with similar incidents in the future.

Key Genes of Immunity Associated with Pterygium and Primary Sjögren's Syndrome.

Pterygium and primary Sjögren's Syndrome (pSS) share many similarities in clinical symptoms and ocular pathophysiological changes, but their etiology is unclear. To identify the potential genes and pathways related to immunity, two published datasets, GSE2513 containing pterygium information and GSE176510 containing pSS information, were selected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) of pterygium or pSS patients compared with healthy control conjunctiva, and the common DEGs between them were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted for common DEGs. The protein-protein interaction (PPI) network was constructed using the STRING database to find the hub genes, which were verified in clinical samples. There were 14 co-upregulated DEGs. The GO and KEGG analyses showed that these common DEGs were enriched in pathways correlated with virus infection, antigen processing and presentation, nuclear factor-kappa B (NF-κB) and Th17 cell differentiation. The hub genes (IL1R1, ICAM1, IRAK1, S100A9, and S100A8) were selected by PPI construction. In the era of the COVID-19 epidemic, the relationship between virus infection, vaccination, and the incidence of pSS and pterygium growth deserves more attention.

Exploring the mechanism of action of licorice in the treatment of COVID-19 through bioinformatics analysis and molecular dynamics simulation.

Purpose: The rapid worldwide spread of Corona Virus Disease 2019 (COVID-19) has become not only a global challenge, but also a lack of effective clinical treatments. Studies have shown that licorice can significantly improve clinical symptoms such as fever, dry cough and shortness of breath in COVID-19 patients with no significant adverse effects. However, there is still a lack of in-depth analysis of the specific active ingredients of licorice in the treatment of COVID-19 and its mechanism of action. Therefore, we used molecular docking and molecular dynamics to explore the mechanism of action of licorice in the treatment of COVID-19. Methods: We used bioinformatics to screen active pharmaceutical ingredients and potential targets, the disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulations were carried out to verify that active ingredients were stably combined with protein targets. The supercomputer platform was used to measure and analyze stability of protein targets at the residue level, solvent accessible surface area, number of hydrogen bonds, radius of gyration and binding free energy. Results: Licorice had 255 gene targets, COVID-19 had 4,628 gene targets, the intersection gene targets were 101. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene ontology (GO) analysis showed that licorice played an important role mainly through the signaling pathways of inflammatory factors and oxidative stress. Molecular docking showed that Glycyrol, Phaseol and Glyasperin F in licorice may playe a role in treating COVID-19 by acting on STAT3, IL2RA, MMP1, and CXCL8. Molecular dynamics were used to demonstrate and analyze the binding stability of active ingredients to protein targets. Conclusion: This study found that Phaseol in licorice may reduce inflammatory cell activation and inflammatory response by inhibiting the activation of CXCL8 and IL2RA; Glycyrol may regulate cell proliferation and survival by acting on STAT3. Glyasperin F may regulate cell growth by inhibiting the activation of MMP1, thus reducing tissue damage and cell death caused by excessive inflammatory response and promoting the growth of new tissues. Therefore, licorice is proposed as an effective candidate for the treatment of COVID-19 through STAT3, IL2RA, MMP1, and CXCL8.

Therapeutic targets and pharmacological mechanisms of Coptidis Rhizoma against ulcerative colitis: Findings of system pharmacology and bioinformatics analysis.

Evidence of the advantages of Coptidis Rhizoma (CR) for the treatment of ulcerative colitis (UC) is accumulating. However, research revealing the targets and molecular mechanisms of CR against UC is scarce. In this research, a bioinformatics analysis was performed to carry out the physicochemical properties and biological activities of phytochemicals in CR and analyze the binding activities, targets, biological functions and mechanisms of CR against UC. This research shows that the CR's key phytochemicals, which are named Coptisine, Berberrubine, Berlambine, Berberine, Epiberberine, Obacunone, Worenine, Quercetin, (R)-Canadine, Magnograndiolide, Palmatine and Moupinamide, have ideal physicochemical properties and bioactivity. A total of 1,904 potential phytochemical targets and 17,995 UC-related targets are identified, and we finally acquire 233 intersection targets between key phytochemicals and disease. A protein-protein interaction network of 233 common targets was constructed; and six hub targets were acquired with a degree greater than or equal to median, namely TP53, HSP90AA1, STAT3, ESR1, MYC, and RELA. The enrichment analysis suggested that the core targets may exert an impact on anti-inflammatory, immunoregulatory, anti-oxidant and anti-fibrosis functions mainly through the PI3K/ART signaling pathway, Th17 differentiation signaling pathway, inflammatory bowel disease signaling pathway, etcetera. Also, a molecular docking analysis shows that the key phytochemicals have strong affinity for binding to the core targets. Finally, the interaction network of CR, phytochemicals, targets, GO functions, KEGG pathways and UC is constructed. This study indicates that the key phytochemicals in CR have superior drug likeness and bioactivity, and the molecular mechanism of key phytochemicals against UC may be via the signaling pathway mentioned above. The potential and critical pharmacological mechanisms provide a direction for future research.

Molecular docking and molecular dynamics study Lianhua Qingwen granules (LHQW) treats COVID-19 by inhibiting inflammatory response and regulating cell survival.

Purpose: 2019 Coronavirus disease (COVID-19) is endangering health of populations worldwide. Latest research has proved that Lianhua Qingwen granules (LHQW) can reduce tissue damage caused by inflammatory reactions and relieve patients' clinical symptoms. However, the mechanism of LHQW treats COVID-19 is currently lacking. Therefore, we employed computer simulations to investigate the mechanism of LHQW treats COVID-19 by modulating inflammatory response. Methods: We employed bioinformatics to screen active ingredients in LHQW and intersection gene targets. PPI, GO and KEGG was used to analyze relationship of intersection gene targets. Molecular dynamics simulations validated the binding stability of active ingredients and target proteins. Binding free energy, radius of gyration and the solvent accessible surface area were analyzed by supercomputer platform. Results: COVID-19 had 4628 gene targets, LHQW had 1409 gene targets, intersection gene targets were 415. Bioinformatics analysis showed that intersection targets were closely related to inflammation and immunomodulatory. Molecular docking suggested that active ingredients (including: licopyranocoumarin, Glycyrol and 3-3-Oxopropanoic acid) in LHQW played a role in treating COVID-19 by acting on CSF2, CXCL8, CCR5, NLRP3, IFNG and TNF. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets. Conclusion: The mechanism of active ingredients in LHQW treats COVID-19 was investigated by computer simulations. We found that active ingredients in LHQW not only reduce cell damage and tissue destruction by inhibiting the inflammatory response through CSF2, CXCL8, CCR5 and IFNG, but also regulate cell survival and growth through NLRP3 and TNF thereby reducing apoptosis.

Mechanism of N-0385 blocking SARS-CoV-2 to treat COVID-19 based on molecular docking and molecular dynamics.

Purpose: 2019 Coronavirus disease (COVID-19) has caused millions of confirmed cases and deaths worldwide. TMPRSS2-mediated hydrolysis and maturation of spike protein is essential for SARS-CoV-2 infection in vivo. The latest research found that a TMPRSS2 inhibitor called N-0385 could effectively prevent the infection of the SARS-CoV-2 and its variants. However, it is not clear about the mechanism of N-0385 treatment COVID-19. Therefore, this study used computer simulations to investigate the mechanism of N-0385 treatment COVID-19 by impeding SARS-CoV-2 infection. Methods: The GeneCards database was used to search disease gene targets, core targets were analyzed by PPI, GO and KEGG. Molecular docking and molecular dynamics were used to validate and analyze the binding stability of small molecule N-0385 to target proteins. The supercomputer platform was used to simulate and analyze the number of hydrogen bonds, binding free energy, stability of protein targets at the residue level, radius of gyration and solvent accessible surface area. Results: There were 4,600 COVID-19 gene targets from GeneCards database. PPI, GO and KEGG analysis indicated that signaling pathways of immune response and inflammation played crucial roles in COVID-19. Molecular docking showed that N-0385 could block SARS-CoV-2 infection and treat COVID-19 by acting on ACE2, TMPRSS2 and NLRP3. Molecular dynamics was used to demonstrate that the small molecule N-0385 could form very stable bindings with TMPRSS2 and TLR7. Conclusion: The mechanism of N-0385 treatment COVID-19 was investigated by molecular docking and molecular dynamics simulation. We speculated that N-0385 may not only inhibit SARS-CoV-2 invasion directly by acting on TMPRSS2, ACE2 and DPP4, but also inhibit the immune recognition process and inflammatory response by regulating TLR7, NLRP3 and IL-10 to prevent SARS-CoV-2 invasion. Therefore, these results suggested that N-0385 may act through multiple targets to reduce SARS-CoV-2 infection and damage caused by inflammatory responses.

One health system supporting surveillance during COVID-19 epidemic in Abruzzo region, southern Italy.

The Istituti Zooprofilattici Sperimentali (IZSs) are public health institutes dealing with the aetiology and pathogenesis of infectious diseases of domestic and wild animals. During Coronavirus Disease 2019 epidemic, the Italian Ministry of Health appointed the IZSs to carry out diagnostic tests for the detection of SARS-CoV-2 in human samples. In particular, the IZS of Abruzzo and Molise (IZS-Teramo) was involved in the diagnosis of SARS-CoV-2 through testing nasopharyngeal swabs by Real Time RT-PCR. Activities and infrastructures were reorganised to the new priorities, in a "One Health" framework, based on interdisciplinary, laboratory promptness, accreditation of the test for the detection of the RNA of SARS-CoV-2 in human samples, and management of confidentiality of sensitive data. The laboratory information system - SILAB - was implemented with a One Health module for managing data of human origin, with tools for the automatic registration of information improving the quality of the data. Moreover, the "National Reference Centre for Whole Genome Sequencing of microbial pathogens - database and bioinformatics analysis" - GENPAT - formally established at the IZS-Teramo, developed bioinformatics workflows and IT dashboard with ad hoc surveillance tools to support the metagenomics-based SARS-CoV-2 surveillance, providing molecular sequencing analysis to quickly intercept the variants circulating in the area. This manuscript describes the One Health system developed by adapting and integrating both SILAB and GENPAT tools for supporting surveillance during COVID-19 epidemic in the Abruzzo region, southern Italy. The developed dashboard permits the health authorities to observe the SARS-CoV-2 spread in the region, and by combining spatio-temporal information with metagenomics provides early evidence for the identification of emerging space-time clusters of variants at the municipality level. The implementation of the One Health module was designed to be easily modelled and adapted for the management of other diseases and future hypothetical events of pandemic nature.

Bioinformatics and systems biology approaches to identify molecular targeting mechanism influenced by COVID-19 on heart failure.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a contemporary hazard to people. It has been known that COVID-19 can both induce heart failure (HF) and raise the risk of patient mortality. However, the mechanism underlying the association between COVID-19 and HF remains unclear. The common molecular pathways between COVID-19 and HF were identified using bioinformatic and systems biology techniques. Transcriptome analysis was performed to identify differentially expressed genes (DEGs). To identify gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways, common DEGs were used for enrichment analysis. The results showed that COVID-19 and HF have several common immune mechanisms, including differentiation of T helper (Th) 1, Th 2, Th 17 cells; activation of lymphocytes; and binding of major histocompatibility complex class I and II protein complexes. Furthermore, a protein-protein interaction network was constructed to identify hub genes, and immune cell infiltration analysis was performed. Six hub genes (FCGR3A, CD69, IFNG, CCR7, CCL5, and CCL4) were closely associated with COVID-19 and HF. These targets were associated with immune cells (central memory CD8 T cells, T follicular helper cells, regulatory T cells, myeloid-derived suppressor cells, plasmacytoid dendritic cells, macrophages, eosinophils, and neutrophils). Additionally, transcription factors, microRNAs, drugs, and chemicals that are closely associated with COVID-19 and HF were identified through the interaction network.

Bioinformatics analysis on structure and function and expression vector construction of SARS-CoV-2 related protein TMPRSS2

Aim Human TMPRSS2 is a transmembrane serine protease.In this paper, the structure and function of the protein were systematically analyzed by bioinformatics, the codon was optimized and the pro- karvotie expression vector was constructed to explore the molecular mechanism of SARS-CoV-2 infecting host cells.Methods The recombinant expression vector pET-22b-TMPRSS2 was generated by molecular cloning technology.The homology, functional sites, subcellular localization, three-dimensional structure and evolutionary characteristics of TMPRSS2 protein were systematically analyzed by using analytical tools such as Protparam, NetPhos3.1, Blast, Clustal X2 and MEGA7.0.Results The prokarvotic expression plas- mid was constructed correctly;TMPRSS2 belongs to medium molecular weight protein, which is composed of 492 amino acid residues.The theoretical isoelectric point is 8.12, the molecular extinction coefficient is 118 145 L * mol~1 * cm"1 , and the half-life is 30 h;TMPRSS2 has 15 potential glycosylation sites and 49 possible phosphorylation sites.It is a transmembrane hydrophilie protein without signal sequenee.In addition, the protein has 13 potential B-cell epitopes and 7 T-eell epitopes.Seeondarv structure analysis showed that random coil accounted for the highest proportion of TMPRSS2 protein ( 0.453 3) , followed by extended strand (0.252 0).Sequence comparison and evolutionary analysis showed that the highest sequence consistency and closest genetic relationship with human TMPRSS2 was Pan troglodytes, followed by gorilla.Conclusions Human-derived TMPRSS2 protein is ev- olutionarilv conserved and functionally important.Hie results of this study can help to reveal the structure and mechanism of action of TMPRSS2 protein, provide ideas for the diagnosis and treatment of COYID-19, and accelerate the research and development process of new drugs targeting TMPRSS2 protein. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.

Identification of the Hub Genes and the Signaling Pathways in Human iPSC-Cardiomyocytes Infected by SARS-CoV-2.

Severe Acute Respiratory Syndrome Coronavirus Type 2 (SARS-CoV-2) is an enveloped single-stranded RNA virus that can lead to respiratory symptoms and damage many organs such as heart, kidney, intestine, brain and liver. It has not been clearly documented whether myocardial injury is caused by direct infection of cardiomyocytes, lung injury, or other unknown mechanisms. The gene expression profile of GSE150392 was obtained from the Gene Expression Omnibus (GEO) database. The processing of high-throughput sequencing data and the screening of differentially expressed genes (DEGs) were implemented by R software. The R software was employed to analyze the Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The protein-protein interaction (PPI) network of the DEGs was constructed by the STRING website. The Cytoscape software was applied for the visualization of PPI network and the identification of hub genes. The statistical analysis was performed by the GraphPad Prism software to verify the hub genes. A total of 516 up-regulated genes and 191 down-regulated genes were screened out. The top 1 enrichment items of GO in biological process (BP), Cellular Component (CC), and Molecular Function (MF) were type I interferon signaling pathway, sarcomere, and receptor ligand activity, respectively. The top 10 enrichment pathways, including TNF signaling pathway, were identified by KEGG enrichment analysis. A PPI network was established, consisting of 613 nodes and 3,993 edges. The 12 hub genes were confirmed as statistically significant, which was verified by GSE151879 dataset. In conclusion, the hub genes of human iPSC-cardiomyocytes infected with SARS-CoV-2 were identified through bioinformatics analysis, which may be used as biomarkers for further research.