SARS-CoV-2 intervened by NSAIDs: A network pharmacology approach to decipher signaling pathway and interactive genes

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Adnan, Dong Ha Cho This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-111615/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) showed promising clinical efficacy toward COVID-19 patients as 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 potent NSAIDs candidate(s) and its novel mechanism(s) against COVID-19 by network pharmacology. Method: FDA (U.S. Food & Drug Administration) approved twenty NSAIDs were used for this study. Genes related to selected NSAIDs and COVID-19 related genes were identified by the Similarity Ensemble Approach, Swiss Target Prediction, and PubChem databases . Venn diagram identified overlapping genes between NSAIDs and COVID-19 related genes. The interactive networking between NSAIDs and overlapping genes was analyzed by STRING. RStudio plotted the bubble chart of KEGG pathway enrichment analysis of overlapping genes . Finally, the binding affinity of NSAIDs against target genes was determined through molecular docking analysis. Results: Geneset enrichment analysis exhibited 26 signaling pathways against COVID-19. Inhibition of proinflammatory stimuli of tissues and/or cells by inactivating RAS signaling pathway was identified as the key anti-COVID-19 mechanism of NSAIDs. Besides, MAPK8, MAPK10, and BAD genes were explored as the associated genes of the RAS. Among twenty NSAIDs, 6MNA, rofecoxib, and indomethacin revealed promising binding affinity with the highest docking score against three identified genes, respectively. Conclusions : Overall, our proposed three NSAIDs (6MNA, rofecoxib, and indomethacin) might block the RAS by inactivating its associated genes, thus may alleviate excessive inflammation induced by SARS-CoV-2. Health Policy Clinical Pharmacology Non-Steroidal Anti-Inflammatory Drugs COVID-19 MAPK8-MAPK10-BAD 6MNA-Rofecoxib-Indomethacin RAS signaling pathway Network pharmacology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction An initial outbreak of pneumonia caused by unknown etiology was first reported at Wuhan in Hubei Province, China, and alerted to the World Health Organization (WHO) by the Wuhan Municipal Health Commission on 31 December 2019 1 . Later, the infectious disease experts detected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can rapidly transmit from person to person through interaction or respiratory droplets 2 . As a consequence of its tremendous spread in the world, WHO announced a changing level from epidemic to pandemic disease (COVID-19) on March 11, 2020 3 . Although the symptoms are identical to pneumonia, however, a considerable number of COVID-19 infected patients showed no physical sign, thus can transmit the virus to others, as silently spread 4 . Due to the unavailability of a reliable vaccine, clinicians are utilizing anti-viral drugs and NSAIDs as a significant viable option for COVID-19 patients 5 . A recent study has reported that use of NSAIDs is safe for COVID-19 treatment without exposing specific negative side effects 6 . Though there is a lack of evidence whether combined NSAIDs treatment could worsen COVID-19 symptoms 7 , but researchers suggested that anti-inflammatory therapies might suppress the fatal cytokine storm of COVID-19 patients 8 . Additionally, WHO announced that no evidence of unwanted side effects was reported, particularly the risk of death with the administration of NSAIDs in COVID-19 patients 9 . Commonly, NSAIDs are used to treat diverse anti-inflammatory symptoms due to its good therapeutic efficacy 10 . However, one potential drug of interest is indomethacin which possesses both anti-inflammatory and antiviral properties. Its antiviral potentiality was first identified in 2006 during the outbreak of SARS-CoV 11 and subsequent attribution was also observed against SARS-CoV-2 12 . A study on canine coronavirus (in vitro) revealed that indomethacin could significantly suppress virus replication, thus protecting host cell from virus induced damage. Similar antiviral effect was also observed during in vivo assessment where normal anti-inflammatory dose was found very effective 12,13 . Although there are many NSAIDs which may have possible therapeutic interventions against COVID-19, lack of scientific evidence has limited their broad application to COVID-19 patients. Hence, we aimed to identify the most potent NSAIDs and their mechanism(s) against COVID-19 through network pharmacology. Network pharmacology can decode the mechanism(s) of drug action with an overall viewpoint , which focuses on pattern changing form “single protein target, single drug” to “multiple protein targets, multiple drugs” 14 . Currently, network pharmacology has been extensively utilized to explore multiple targets and unknown additional mechanism(s) against diverse diseases 15 . In this research, network pharmacology was applied to investigate the most potent NSAIDs and their novel mechanisms of action against COVID-19. Firstly, a total of 20 approved NSAIDs was selected via using public websites. The 20 NSAIDs and COVID-19 related genes were also identified using public databases. Next, the selected overlapping genes were discovered as target genes for analyzing anti-COVID-19. Finally, pathway enrichment analysis was performed to reveal the mechanism(s) of the most potent NSAIDs against COVID-19. Figure 1 shows overall workflow . Results Information of NSAIDs A total of twenty FDA approved NSAIDs was selected. Table 1 and Figure 2 display the chemical information and structure of these NSAIDs. Among the twenty NSAIDs, nineteen NSAIDs were found as active drug and one “nabumetone” was a prodrug and its metabolite form is 6-methoxy-2-naphthylacetic acid (6MNA). Figure 3 shows nabumetone oxidized into 6MNA. NSAIDs linked to the 781 genes or COVID-19 related genes By screening from two public databases (SEA and STP), a total of 781 NSAIDs related genes were identified (see Supplementary Table S1 ) . The overlapping genes (228 genes) selected from the two databases were shown (see Supplementary Table S2). Figure 4 displays the result of the overlapping genes. From the PubChem database, 466 COVID-19 related genes were identified (see Supplementary Table S3). The 26 overlapping genes were extracted between the 228 overlapped genes and 466 COVID-19 related genes (see Supplementary Table S4). Figure 5 shows the result of overlapping genes. Pathway enrichment analysis of overlapping genes and identification of significant genes against COVID-19 Figure 6 displays the identified overlapping 26 genes were linked closely to each other through utilizing STRING. Based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis with “ Homo sapiens ” mode, 26 signaling pathways from the 26 genes were revealed against COVID-19. Figure 7 shows the signaling pathways were plotted in the bubble chart through Rstudio. Table 2 provides the detailed description of the 26 signaling. Figure 8 shows that both MAPK8 and MAPK10 linked to 22 out of 26 signaling pathways, were determined as hub genes of NSAIDs against COVID-19. Coincidently, both MAPK8 and MAPK10 play major roles in all of the 22 signaling pathways by the RAS signaling pathways, suggesting that BAD (Bcl-2-associated death promoter) gene and the two hub genes (MAPK8 and MAPK10) are associated with the RAS signaling pathway against COVID-19. The interactions between NSAIDs and each gene were visualized with RStudio (see Supplementary Figure S1). Affinity binding energy score on three genes of the most potent NSAIDs against COVID-19 From the SEA and STP databases, it was revealed that MAPK8 gene is associated with three NSAIDs (6MNA, Mefenamic acid, and Etodolac), MAPK10 gene is related to twelve NSAIDs (Mefenamic acid, Naproxen, Tolmetin, Fenoprofen, Ketorolac, Ketoprofen, Ibuprofen, Flurbiprofen, Oxaprozin, Sulindac, Diclofenac, and Rofecoxib), BAD gene is involved with two NSAIDs (6MNA and Indomethacin). Figure 9 displays the molecular docking was performed to evaluate the binding mode of these three genes against their associated NSAIDs, respectively, and the docking figures are depicted in Molecular docking score of M1-M3 on MAPK8 protein (PDB ID: 4YR8) was analyzed in the “ Homo Sapiens ” mode. Based on the docking score, the order of priority of binding energy is given: M1>M2>M3. The three-affinity binding energy of M1-MAPK8, M2-MAPK8, and M3-MAPK8 indicated -7.1, -6.4, and -6.3 kcal/mol, respectively. The 6MNA (M1) had the strongest affinity on MAPK8. Interaction analysis of best-docked compound namely “6MNA” resulted one hydrogen bond (Lys-218) and seven hydrophobic bonds (Gly-88, Leu-86, Met-0, Val-44, Cys-1, Gly-46, and ASP-47). Table 3 provides the detailed information of binding energy and interactions. Molecular docking score of R1-R12 on MAPK10 protein (PDB ID: 3TTJ) was demonstrated in the “ Homo sapiens ” mode. Based on the docking score, the priority of affinity binding energy is as follows: R12>R10> R9= R5> R8> R3= R11> R4 =R6 >R1 >R2 >R7. The twelve affinity binding energy of R1-MAPK10, R2-MAPK10, R3-MAPK10, R4 -MAPK10, R5-MAPK10, R6-MAPK10, R7-MAPK10, R8-MAPK10, R9-MAPK10, R10-MAPK10, R11-MAPK10, and R12-MAPK10 revealed -6.4, -6.1, -6.7, -6.5, -7.1, -6.5, -7.1, -6.5, -5.6, -6.9, -7.1, -7.4, -6.7, and -7.5 kcal/mol, respectively. The rofecoxib (R12) had the strongest affinity on MAPK10. Interaction analysis of best-docked compound namely “Rofecoxib” resulted three hydrogen bonds (Asn-194, Lys-191, Ser-217) and seven hydrophobic bonds (Asp-189, Arg-230, Thr-203, Leu-210, Gly-209, Ala-211, Arg-107). Table 4 provides the detailed information of binding energy and interactions. Molecular docking score of B1-B2 on BAD protein (PDB ID: 1G5J) was also analyzed in the “ Homo Sapiens ” mode. Based on the docking score, the order of priority of binding energy is given: B2>B1. The two-affinity binding energy of B1-BAD and B2-BAD demonstrated -6.8 and -7.1 kcal/mol, respectively. The indomethacin (B2) had the strongest affinity on BAD. Interaction analysis of best-docked compound namely “Indomethacin” resulted one hydrogen bond (Asp-180) and eight hydrophobic bonds (Arg-169, Tyr-124, Phe-127, Val-131, Glu-128, His-181, Thr-176, Trp-173). Table 5 provides the detailed information of binding energy and interactions. Figure 10 depicts that the three NSAIDs (6MNA, Rofecoxib, and Indomethacin) might be the potential anti-inflammatory agents against COVID-19 Materials And Methods NSAIDs linked to selected genes or COVID-19 related genes Based on SMILES, targeted genes of the NSAIDs approved by FDA (U.S. Food & Drug Administration) were identified utilizing Similarity Ensemble Approach (SEA) (http://sea.bkslab.org/) and Swiss Target Prediction (STP) (http://www.swisstargetprediction.ch/) with the “ Homo sapience ” mode. COVID-19 related genes were identified by browsing PubChem (https://pubchem.ncbi.nlm.nih.gov/). The overlapping genes between NSAIDs targeted genes and COVID-19 related genes were identified and visualized by Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/) Network construction of interactions between NSAIDs targeted genes and COVID - 19 related genes The overlapping genes interactions between NSAIDs targeted genes and COVID-19 related genes were analyzed by STRING (https://string-db.org/). Signaling pathway enrichment analysis of overlapping genes Genes-genes interaction figure was visualized by STRING (https://string-db.org/). RStudio plotted the bubble chart of KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of overlapping genes. Using RStudio, the most significant genes among signaling pathways and correlation of NSAIDs on the most significant genes were analyzed. The results suggest a hint at the unknown molecular mechanism(s) of the most potent NSAIDs against COVID-19. Binding affinity energy value of the most potent NSAIDs on genes in silico The binding affinity energy measurement of the uttermost NSAIDs on key genes was established by Autodock (http://autodock.scripps.edu/), Vina (http://vina.scripps.edu/), Pymol (https://pymol.org/2/). Discussion NSAIDs-genes networking analysis demonstrated that the clinical effect of NSAIDs on COVID-19 was directly related to 26 genes. The results of KEGG pathway enrichment analysis of 26 genes suggested that 26 signaling pathways were associated with the occurrence and development of the COVID-19 symptoms. The correlations of 26 signaling pathways with COVID-19 symptoms were succinctly discussed as follows. PPAR ( Peroxisome Proliferator-Activated Receptor ) signaling pathway: A report shows that PPARγ ( Peroxisome Proliferator-Activated Receptor-gamma) , PPARα ( Peroxisome Proliferator-Activated Receptor-alpha) , and PPARβ/δ ( Peroxisome Proliferator-Activated Receptor-beta/delta ) agonists have anti-inflammatory and immunomodulatory functions 16 . MAPK ( Mitogen-Activated Protein Kinase) signaling pathway: The mechanisms of p38 MAPK inactivation might be a significant therapy against the SARS infected cells 17 . Additionally, MAPK stimulates cytokine production such as IL-10 (Interleukin 10), TNF- α (Tumor Necrosis Factor-Alpha), IL-4 (Interleukin 4), and IFN- γ (Interferon gamma) 18 . This report shows a coincidence with our suggested strategy in this study. ErbB (Erythroblastic Leukemia Viral Oncogene Homolog) signaling pathway: ErbB signaling reduces the proinflammatory activation in cardiac cells 19 . RAS (Renin Angiotensin System) signaling pathway: Inactivation of RAS can reduce tissue damage in COVID-19 patients. In addition, ACE (Angiotensin Converting Enzyme) antagonists block the response of RAS system 20 . cGMP-PKG (Cyclic GMP-Protein Kinase G) signaling pathway: The activation of cGMP-PKG signaling inhibits inflammatory response in the prostate, and also decreases CCL5 (C-C Motif Chemokine Ligand 5) release in CD8 + T cells (Cluster of Differentiation 8 T cells) 21 . cAMP (Cyclic Adenosine Monophosphate) signaling pathway: The elevation of cAMP leads to diverse cellular effects, such as airway smooth muscle relaxation, repressed effects on cellular inflammation, and immune responses 22 . NF-κB (Nuclear Factor kappa-light-chain-enhancer of activated B cells) signaling pathway: Activation of the NF-κB signaling pathway gives rise to the inflammation induced by the SARS-CoV infection. In contrast, NF-κB inhibitors are the potential antivirals against SARS-CoV, and can also contribute to other pathogenic human coronaviruses 23 . FOXO (Forkhead box protein O1) signaling pathway: Decrease of FOXO3 (Forkhead box protein O3) in T cells inhibits apoptosis, enhances multifunction of CD8 cells, and elevates viral control 24 . Sphingolipid signaling pathway: Sphingolipids play a vital role to protect lung from damages, and the control of sphingolipid signaling pathways may give a good therapeutic efficacy 25 . Wnt (Wingless/Integrated) signaling pathway: Wnt signaling involves with the prime inflammatory pathways like intestinal inflammation. Also, elucidating the mutual modes of Wnt ligands and cytokines manifest new treatment strategies for chronic colitis and other inflammatory diseases 26 . VEGF (Vascular Endothelial Growth Factor) signaling pathway: A report suggested that VEGFA (Vascular Endothelial Growth Factor A) is inhibited by the activation of ACE2 (Angiotensin-Converting Enzyme 2). However, ACE2 is downregulated by the attack of COVID-19. Subsequently, activation of VEGFA elevates vascular permeability and severity of endothelial damage 27 . TLR (Toll-like receptor) signaling pathway: Toll-like receptors (TLRs) play a pivotal role in the innate immune system and contribute to defend host cells by recognizing PAMPs (Pathogen-Associated Molecular Patterns) induced by various microbes 28 . The activation of TLRs triggers an array of response resulting into expression of different cytokines and chemokines, phagocytosis, and even apoptotic case activation to induce programmed cell death 29 . NOD-like receptor (NLR) signaling pathway: Nod-like receptors (NLRs) have been revealed as the major microbial signals that take part in the universal immune responses to infection, and also contribute to the prevention of infections 30 . RIG-I-like receptor (RLR) signaling pathway: RIG-I-like receptors (RLRs) play a vital role in pathogen sensor of RNA virus infection, which enhances the antiviral immunity by sensing foreign RNA 31 . IL-17 (Interleukin-17) signaling pathway: IL-17 receptor inhibitors are widely used to ameliorate the inflammatory acuteness to date. Furthermore, it is a potential target to suppress severe inflammation induced by COVID-19 32 . Fc epsilon RI signaling pathway: Fc epsilon RI interconnecting causes mast cell degranulation and synthesis of proinflammatory mediators 33 . TNF (Tumor Necrosis Factor) signaling pathway: TNF deficit is associated with dysfunctional secretion of inflammatory cytokine, leading to lung pathology and death during respiratory poxvirus infection, and thus TNF is very significant element for regulating inflammation 34 . Neurotrophin signaling pathway: COVID-19 causes severe brain damage and destruction of central nervous system derived from neurotrophin (Huang and Reichardt 2001). Insulin signaling pathway: Obesity-oriented insulin resistance is associated with the induction of proinflammatory macrophage, leads to inflammation of adipose tissue 37 . GnRH (Gonadotropin-Releasing Hormone) signaling pathway: Disrupted BBB (Blood Brain Barrier) by viral infection, lymphocytes (B and T cells), monocytes, and granulocytes can penetrate in the brain parenchyma which induce inflammation, resulting in dysregulation of GnRH neurons. Additionally, the inflammation of GnRH neurons inhibits GnRH transport through proinflammatory cytokines by impairing the cytoskeleton 38 . Prolactin signaling pathway: HIV (Human Immunodeficiency Virus) patients have greater prolactin quantity compared to others. Besides, prolactin is regarded as a cytokine to react in immune system 39,40 . Adipocytokine signaling pathway: Adipocytokines stimulate inflammation and disrupting immune response which cause tissue damage. Adipocytokines might also induce proinflammation in RA (Rheumatoid Arthritis) patients and thus lead to the development of bone damage 41 . Oxytocin signaling pathway: Oxytocin interrupts the production of proinflammatory cytokines by inactivating of the eIF-2α–ATF4 (Eukaryotic Initiation Factor -2 alpha- Activating Transcription Factor 4) pathway 42 . Relaxin signaling pathway: Relaxin inhibitors are good therapeutic targets to suppress inflammation caused by airway dysfunction 43 . AGE-RAGE (Advanced Glycation End product -Receptor of Advanced Glycation End product) signaling pathway in diabetic complications: The binding of AGE to its receptor RAGE can trigger the cytokine production, thus, can cause tissue damages, while the blockage of AGE-RAGE can effectively curtail the inflammation 44 . Epithelial cell signaling in Helicobacter pylori infection: Helicobacter pylori interrupts T and B cell signaling to set immune system. It is apparent that COVID-19 patients with Helicobacter pylori might be vulnerable to inflammatory responses 45 . Generally, SARS-CoV-2 invades in the lungs and throat, induces excessive inflammation, which causes the secretion of cytokines, resulting in severe complications like acute respiratory failure, pneumonia, and acute liver injury (Reyes and Peniche 2019; Nile et al. 2020). Researchers suggested that RAS is a potential route for SARS-CoV-2 induced cellular infection which may be linked to the imbalance of RAS. It was discovered that ACE-2 is the functional receptor for the SARS-CoV-2 to trigger infection in the lung alveolar epithelial cells. The internalization of virus leads to downregulate the ACE-2 on host cell surface that could cause the elevation and demotion of the angiotensin-II (AII) and angiotensin 1-7 (A 1-7 ) respectively. Such an imbalance between these angiotensins may induce deleterious effects in the lung and heart. Thus, the SARS-CoV-2 affects humans through this mechanism 49–52 . Therefore, blockade of the RAS may restore the RAS balance by reducing the deleterious effects associated with angiotensin-II 53 . Recent evidence showed that RAS inhibitors might be a promising target for relieving acute-severe pneumonia caused by the COVID-19 54 . Interestingly, our study identified that the three genes (MAPK 8, MAPK 10, and BAD) are mainly associated with the RAS signaling pathway. MAPK 8 and MAPK 10 are members of the MAPK family which are the key mediators of the inflammation, vasoconstriction, and thrombosis. Besides, overwhelming heart and lung injury in COVID-19 infection might be due to the overactivation of MAPK 55 . Therefore, inactivation of these genes can also be a viable strategy for relieving COVID-19 induced organ injury. In addition, disposal of inflammatory cells by promoting the cell death can be an innovative approach to control excessive inflammation. In this regard, inhibition of the anti-apoptotic Bcl-2 gene can also be a potential target to lessen inflammation 56,57 . Our findings also explored that MAPK8, MAPK10 and BAD genes are related to three, twelve, and two NSAIDs, respectively. During the molecular docking analysis, 6MNA, rofecoxib, and indomethacin revealed promising binding affinity along with highest docking score against MAPK8, MAPK10 and BAD genes, respectively, which indicated that the three (6MNA, Rofecoxib, and Indomethacin) NSAIDs are very potential among all others, may possibly block the RAS signaling pathway by inactivating its associated genes (MAPK8, MAPK10 and BAD), and subsequently suppress SARS-CoV-2 induced cytokine storm. Among various NSAIDs, indomethacin is a current drug of interest to the clinicians. Primary care physicians (New York) reported that indomethacin had been prescribed to a large number of COVID-19 patients and observed quick recovery from cough, pain, and other symptoms. Such improvements and well-being benefits were not evident in the case of ibuprofen and hydroxychloroquine implementation (Vaduganathan et al. 2020b; Little 2020). Importantly, many researchers previously reported varying degrees of antiviral activity of indomethacin against herpesvirus 60 , pseudorabies virus 61 , cytomegalovirus 62 , hepatitis B virus 63 , vesicular stomatitis virus 64 , rotavirus 65 , and canine coronavirus 11 . In contrast, 6MNA (active metabolite of nabumetone) and Rofecoxib are also the potential anti-inflammatory drugs, but studies disclosed that they are less potent compared to the indomethacin 66,67 . Hence, such compelling outcomes indicate that indomethacin can be considered to use alone or in combination for antiviral therapy which may assist in combating human coronavirus (SARS-CoV-2). In summary, NSAIDs-genes network suggested that the therapeutic effect of NSAIDs on COVID-19 was associated with 26 signaling pathways. This study suggests that 6MNA, rofecoxib, and indomethacin are the most potent NSAIDs against COVID-19. The basis of this research is an understanding of how these NSAIDs (which stimulates anti-inflammatory processes against COVID-19) work on COVID-19 patients. That scientific evidence informs the selection of NSAIDs, in turn, provides for clinical design against COVID-19. Our research suggests that the inhibition of BAD-Indomethacin with other two hub genes MAPK8-6MNA, MAPK10-Rofecoxib might play cumulative actions by inactivating the RAS signaling pathway against COVID-19. Most recently, efficacy of indomethacin against COVID-19 has been approved clinically. Our study presents that indomethacin is a potent therapeutic candidate to relieve COVID-19 symptoms, which is in line with the many previous studies. However, further clinical trial on indomethacin should be warranted in COVID-19 patients in order to slow down the progression of SARS-CoV-2 and mitigating the severity as well. Abbreviations ACE: Angiotensin-Converting Enzyme; ACE2: Angiotensin-Converting Enzyme 2; AGE-RAGE: Advanced Glycation End product /Receptor of Advanced Glycation End product; BAD: Bcl-2-Associated Death promoter; BBB: Blood Brain Barrier; cAMP: Cyclic Adenosine MonoPhosphate; CCL5 (C-C Motif Chemokine Ligand 5); CD8 + T cells: Cluster of Differentiation 8 T cells; cGMP-PKG: cyclic Guanosine MonoPhosphate - Protein Kinase G; COVID-19: SARS-CoV-2 virus; eIF-2α–ATF4 (Eukaryotic Initiation Factor -2 alpha- Activating Transcription Factor 4); ErbB: Erythroblastic Leukemia Viral Oncogene Homolog; FDA: U.S. Food & Drug Administration; FOXO: FOrkhead boX protein O; GnRH: Gonadotropin-Releasing Hormone; HIV: Human Immunodeficiency Virus; IFN- γ: Interferon gamma; IL-4: Interleukin 4; IL-10: Interleukin 10; IL-17: Interleukin 17; KEGG: Kyoto Encyclopedia of Genes and Genomes; MAPK: Mitogen-Activated Protein Kinase; MAPK8: Mitogen-Activated Protein Kinase 8; MAPK10: Mitogen-Activated Protein Kinase 10; NF- κB: Nuclear Factor Kappa-light-chain-enhancer of activated B cells; NLR: Nod-Like Receptor; NLRs: Nod-Like Receptors; NSAIDs: Non-Steroidal Anti-Inflammatory Drugs; PPAR: Peroxisome Proliferator-Activated Receptors; PPARα: Peroxisome Proliferator-Activated Receptor-alpha; PPARγ: Peroxisome Proliferator-Activated Receptor-gamma; PPARβ/δ: Peroxisome Proliferator-Activated Receptor-beta/delta; PAMPs: Pathogen-Associated Molecular Patterns; RA: Rheumatoid Arthritis; RAS: Renin Angiotensin System; RLR: RIG-I-Like Receptor; RLRs: RIG-I-Like Receptors; SARS-CoV-2: Severe Acute Respiratory Syndrome CoronaVirus 2; SEA: Similarity Ensemble Approach; STP: Swiss Target Prediction; TLR: Toll-like receptor; TLRs: Toll-like receptors; TNF: Tumor Necrosis Factor; TNF-α: Tumor Necrosis Factor-Alpha; VEGF: Vascular Endothelial Growth Factor; VEGFA: Vascular Endothelial Growth Factor A; WHO: World Health Organization; Wnt: Wingless/Integrated Declarations Data availability All data generated or analysed during this study are included in this published article (and its Supplementary Information files). Acknowledgements This research was acknowledged by the Department of Bio-Health Technology, Kangwon National University, Chuncheon 24341, Republic of Korea. Author contribution Ki Kwang Oh and Md. Adnan : Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing - Original Draft. Ki Kwang Oh and Md. Adnan : Software, Investigation, Data Curation. Ki Kwang Oh and Md. Adnan : Validation, Writing - Review & Editing. Dong Ha Cho : Supervision, Project administration Competing interests The authors declare no competing interests. References Harapan, H. et al. Coronavirus disease 2019 (COVID-19): A literature review. J. Infect. Public Health (2020). Pericàs, J. M. et al. COVID-19: From epidemiology to treatment. Eur. Heart J. (2020) doi:10.1093/eurheartj/ehaa462. Astuti, I. & Ysrafil. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): An overview of viral structure and host response. Diabetes Metab. Syndr. Clin. Res. Rev. 14 , 407–412 (2020). Oran, D. P. & Topol, E. J. Prevalence of Asymptomatic SARS-CoV-2 Infection. Ann. Intern. Med. (2020) doi:10.7326/m20-3012. Wu, R. et al. An Update on Current Therapeutic Drugs Treating COVID-19. Current Pharmacology Reports vol. 6 56–70 (2020). Ozili, P. COVID-19 in Africa: socio-economic impact, policy response and opportunities. Int. J. Sociol. Soc. Policy (2020) doi:10.1108/IJSSP-05-2020-0171. Capuano, A., Scavone, C., Racagni, G. & Scaglione, F. NSAIDs in patients with viral infections, including Covid-19: Victims or perpetrators? Pharmacol. Res. 157 , 104849 (2020). Zhang, W. et al. The use of anti-inflammatory drugs in the treatment of people with severe coronavirus disease 2019 (COVID-19): The experience of clinical immunologists from China. Clin. Immunol. 108393 (2020). Sodhi, M. & Etminan, M. Safety of Ibuprofen in Patients With COVID-19: Causal or Confounded? Chest vol. 158 55–56 (2020). Meek, I. L., van de Laar, M. A. F. J. & Vonkeman, H. E. Non-steroidal anti-inflammatory drugs: An overview of cardiovascular risks. Pharmaceuticals vol. 3 2146–2162 (2010). Amici, C. et al. Indomethacin has a potent antiviral activity against SARS coronavirus. Antivir. Ther. 11 , 1021 (2006). Xu, T., Gao, X., Wu, Z., Selinger, D. W. & Zhou, Z. Indomethacin has a potent antiviral activity against SARS CoV-2 in vitro and canine coronavirus in vivo. bioRxiv (2020). Russell, B., Moss, C., Rigg, A. & Van Hemelrijck, M. COVID-19 and treatment with NSAIDs and corticosteroids: should we be limiting their use in the clinical setting? Ecancermedicalscience 14 , (2020). Oh, K. K., Adnan, M. & Cho, D. H. Network pharmacology approach to bioactive chemical compounds identified from Lespedeza bicolor lignum methanol extract by GC–MS for amelioration of hepatitis. Gene Reports 100851 (2020). Tang, J. & Aittokallio, T. Network Pharmacology Strategies Toward Multi-Target Anticancer Therapies: From Computational Models to Experimental Design Principles. Curr. Pharm. Des. 20 , 23–36 (2014). Belvisi, M. G. & Mitchell, J. A. Targeting PPAR receptors in the airway for the treatment of inflammatory lung disease. British Journal of Pharmacology vol. 158 994–1003 (2009). Mizutani, T., Fukushi, S., Saijo, M., Kurane, I. & Morikawa, S. Phosphorylation of p38 MAPK and its downstream targets in SARS coronavirus-infected cells. Biochem. Biophys. Res. Commun. 319 , 1228–1234 (2004). De Souza, A. P. et al. MAPK involvement in cytokine production in response to Corynebacterium pseudotuberculosis infection. BMC Microbiol. 14 , (2014). Ryzhov, S. et al. ERBB signaling attenuates proinflammatory activation of nonclassical monocytes. Am. J. Physiol. Circ. Physiol. 312 , H907–H918 (2017). Aleksova, A. et al. COVID-19 and renin-angiotensin system inhibition: role of angiotensin converting enzyme 2 (ACE2) - Is there any scientific evidence for controversy? Journal of Internal Medicine (2020) doi:10.1111/joim.13101. Jin, S. et al. Activation of cGMP/PKG/p65 signaling associated with PDE5‐Is downregulates CCL5 secretion by CD8 + T cells in benign prostatic hyperplasia. Prostate 79 , 909–919 (2019). Yan, K., Gao, L. N., Cui, Y. L., Zhang, Y. & Zhou, X. The cyclic AMP signaling pathway: Exploring targets for successful drug discovery (review). Mol. Med. Rep. 13 , 3715–3723 (2016). DeDiego, M. L. et al. Inhibition of NF- B-Mediated Inflammation in Severe Acute Respiratory Syndrome Coronavirus-Infected Mice Increases Survival. J. Virol. 88 , 913–924 (2014). Sullivan, J. A., Kim, E. H., Plisch, E. H. & Suresh, M. FOXO3 Regulates the CD8 T Cell Response to a Chronic Viral Infection. J. Virol. 86 , 9025–9034 (2012). Abu-Farha, M. et al. The role of lipid metabolism in COVID-19 virus infection and as a drug target. International Journal of Molecular Sciences vol. 21 (2020). Moparthi, L. & Koch, S. Wnt signaling in intestinal inflammation. Differentiation vol. 108 24–32 (2019). Turkia, M. COVID-19 As An Endothelial Disease and Its Relationship to Vascular Endothelial Growth Factor (VEGF) and Iodide. SSRN Electron. J. (2020) doi:10.2139/ssrn.3604987. Kawasaki, T. & Kawai, T. Toll-like receptor signaling pathways. Frontiers in Immunology vol. 5 (2014). Ashayeri Ahmadabad, R., Khaleghi Ghadiri, M. & Gorji, A. The role of Toll-like receptor signaling pathways in cerebrovascular disorders: The impact of spreading depolarization. Journal of Neuroinflammation vol. 17 1–13 (2020). Carneiro, L. A. M., Travassos, L. H. & Girardin, S. E. Nod-like receptors in innate immunity and inflammatory diseases. Annals of Medicine vol. 39 581–593 (2007). Chan, Y. K. & Gack, M. U. RIG-I-like receptor regulation in virus infection and immunity. Current Opinion in Virology vol. 12 7–14 (2015). Pacha, O., Sallman, M. A. & Evans, S. E. COVID-19: a case for inhibiting IL-17? Nature Reviews Immunology vol. 20 345–346 (2020). Klemm, S. & Ruland, J. Inflammatory signal transduction from the FcεRI to NF-κB. Immunobiology vol. 211 815–820 (2006). Junaliah Tuazon Kels, M. et al. TNF deficiency dysregulates inflammatory cytokine production leading to lung pathology and death during respiratory poxvirus infection. bioRxiv 2019.12.22.883728 (2019) doi:10.1101/2019.12.22.883728. COVID-19: Severe brain damage possible even with mild symptoms | Science| In-depth reporting on science and technology | DW | 09.07.2020. https://www.dw.com/en/coronavirus-brain-damage/a-54111054. Huang, E. J. & Reichardt, L. F. Neurotrophins: Roles in neuronal development and function. Annual Review of Neuroscience vol. 24 677–736 (2001). Shimobayashi, M. et al. Insulin resistance causes inflammation in adipose tissue. J. Clin. Invest. 128 , 1538–1550 (2018). Barabás, K., Szabó-Meleg, E. & Ábrahám, I. M. Effect of inflammation on female gonadotropin-releasing hormone (GnRH) neurons: Mechanisms and consequences. International Journal of Molecular Sciences vol. 21 (2020). Acharya, S., Fernando, R. & Gama, R. Case Report Gynaecomastia, hyperprolactinaemia and HIV infection . Borba, V. V., Zandman-Goddard, G. & Shoenfeld, Y. Prolactin and autoimmunity: The hormone as an inflammatory cytokine. Best Practice and Research: Clinical Endocrinology and Metabolism vol. 33 101324 (2019). Ruscitti, P. et al. Adipocytokines in rheumatoid arthritis: The hidden link between inflammation and cardiometabolic comorbidities. Journal of Immunology Research vol. 2018 (2018). Inoue, T. et al. Oxytocin Suppresses Inflammatory Responses Induced by Lipopolysaccharide through Inhibition of the eIF-2α–ATF4 Pathway in Mouse Microglia. Cells (2019) doi:10.3390/cells8060527. Martin, B. et al. Relaxin reverses inflammatory and immune signals in aged hearts. PLoS One (2018) doi:10.1371/journal.pone.0190935. Ramasamy, R., Yan, S. F. & Schmidt, A. M. Receptor for AGE (RAGE): Signaling mechanisms in the pathogenesis of diabetes and its complications. Ann. N. Y. Acad. Sci. 1243 , 88–102 (2011). Reyes, V. E. & Peniche, A. G. Helicobacter pylori deregulates T and B cell signaling to trigger immune evasion. in Current Topics in Microbiology and Immunology vol. 421 229–265 (Springer Verlag, 2019). Coronavirus: What Happens To People’s Body If They Get Infected. https://www.webmd.com/lung/coronavirus-covid-19-affects-body#2. Nile, S. H. et al. COVID-19: Pathogenesis, cytokine storm and therapeutic potential of interferons. Cytokine and Growth Factor Reviews vol. 53 66–70 (2020). What Are the Complications of Coronavirus (COVID-19)? https://www.webmd.com/lung/coronavirus-complications#1. Vaduganathan, M. et al. Renin–angiotensin–aldosterone system inhibitors in patients with Covid-19. N. Engl. J. Med. 382 , 1653–1659 (2020). Sama, I. E. et al. Circulating plasma concentrations of angiotensin-converting enzyme 2 in men and women with heart failure and effects of renin–angiotensin–aldosterone inhibitors. Eur. Heart J. 41 , 1810–1817 (2020). Bloch, M. J. Renin-Angiotensin System Blockade in COVID-19: Good, Bad, or Indifferent?∗. J. Am. Coll. Cardiol. 76 , 277 (2020). Mascolo, A. et al. Renin-angiotensin system and Coronavirus disease 2019: A narrative review. Front. Cardiovasc. Med. 7 , (2020). Xu, X. et al. Effective treatment of severe COVID-19 patients with tocilizumab. Proc. Natl. Acad. Sci. U. S. A. 117 , 10970–10975 (2020). Sun, M. L., Yang, J. M., Sun, Y. P. & Su, G. H. [Inhibitors of RAS Might Be a Good Choice for the Therapy of COVID-19 Pneumonia]. Zhonghua Jie He He Hu Xi Za Zhi 43 , 219–222 (2020). Grimes, J. M. & Grimes, K. V. p38 MAPK inhibition: A promising therapeutic approach for COVID-19. J. Mol. Cell. Cardiol. 144 , 63–65 (2020). Bulanova, D. et al. Antiviral properties of chemical inhibitors of cellular anti-apoptotic Bcl-2 proteins. Viruses 9 , 271 (2017). Tian, B. et al. Bcl-2 inhibitors reduce steroid-insensitive airway inflammation. J. Allergy Clin. Immunol. 140 , 418–430 (2017). Repurposing indomethacin for COVID-19 - Hospital Healthcare EuropeHospital Healthcare Europe. https://hospitalhealthcare.com/covid-19/repurposing-indomethacin-for-covid-19/. Little, P. Non-steroidal anti-inflammatory drugs and covid-19. The BMJ vol. 368 (2020). Reynolds, A. E. & Enquist, L. W. Biological interactions between herpesviruses and cyclooxygenase enzymes. Rev. Med. Virol. 16 , 393–403 (2006). Ray, N., Bisher, M. E. & Enquist, L. W. Cyclooxygenase-1 and-2 are required for production of infectious pseudorabies virus. J. Virol. 78 , 12964–12974 (2004). Schröer, J. & Shenk, T. Inhibition of cyclooxygenase activity blocks cell-to-cell spread of human cytomegalovirus. Proc. Natl. Acad. Sci. 105 , 19468–19473 (2008). Bahrami, H. et al. Effects of indomethacin on viral replication markers in asymptomatic carriers of hepatitis B: a randomized, placebo-controlled trial. Am. J. Gastroenterol. 100 , 856–861 (2005). Chen, N., Warner, J. L. & Reiss, C. S. NSAID treatment suppresses VSV propagation in mouse CNS. Virology 276 , 44–51 (2000). Rossen, J. W. A., Bouma, J., Raatgeep, R. H. C., Büller, H. A. & Einerhand, A. W. C. Inhibition of cyclooxygenase activity reduces rotavirus infection at a postbinding step. J. Virol. 78 , 9721–9730 (2004). Melarange, R. et al. Anti-inflammatory and gastrointestinal effects of nabumetone or its active metabolite, 6MNA (6-methoxy-2-naphthylacetic acid): comparison with indomethacin. Agents Actions 36 , C82–C83 (1992). Van Der Heide, H. J. L., Rijnberg, W. J., Van Sorge, A., Van Kampen, A. & Schreurs, B. W. Similar effects of rofecoxib and indomethacin on the incidence of heterotopic ossification after hip arthroplasty. Acta Orthop. 78 , 90–94 (2007). Supporting Information Supplementary Table S1 (PDF) Supplementary Table S2 (PDF) Supplementary Table S3 (PDF) Supplementary Table S4 (PDF) Supplementary Figure S1 (PDF) Tables Table 1. A list of 20 NSAIDs approved by FDA No. Drug name PubChem CID Mechanism of action 1 Flubiprofen 3394 Nonselective COX inhibitor 2 Ibuprofen 3672 Nonselective COX inhibitor 3 Indomethacin 3715 Nonselective COX inhibitor 4 Ketorolac 3826 Nonselective COX inhibitor 5 Mefenamic acid 4044 Nonselective COX inhibitor 6 Piroxicam 54676228 Nonselective COX inhibitor 7 Diflunisal 3059 Prostaglandin synthesis inhibitor 8 Fenoprofen 3342 Prostaglandin synthesis inhibitor 9 Naproxen 156391 Prostaglandin synthesis inhibitor 10 Sulindac 1548887 Prostaglandin synthesis inhibitor 11 Tolmetin 5509 Prostaglandin synthesis inhibitor 12 Ketoprofen 3825 Selective COX-1 inhibitor 13 Oxaprozin 4614 Selective COX-1 inhibitor 14 Celecoxib 2662 Selective COX-2 inhibitor 15 Rofecoxib 5090 Selective COX-2 inhibitor 16 Valdecoxib 119607 Selective COX-2 inhibitor 17 Diclofenac 3033 Selective COX-2 inhibitor 18 Etodolac 3308 Selective COX-2 inhibitor 19 Meloxicam 54677470 Selective COX-2 inhibitor 20* 6MNA 32176 Selective COX-2 inhibitor * 6MNA (Active form) of Nabumetone (Prodrug) Table 2. Target genes in 26 signaling pathways enrichment related to COVID-19. KEGG ID & Description Target genes RichFactor False discovery rate hsa04014: Ras signaling pathway MAPK8,MAPK10,BAD 0.013157895 0.0071 hsa04921: Oxytocin signaling pathway PTGS2,PPP1CA 0.013422819 0.0294 hsa04010: MAPK signaling pathway MAPK8,MAPK10,MAPK14,CASP3 0.013651877 0.0016 hsa04310: Wnt signaling pathway MAPK8,MAPK10 0.013986014 0.0276 hsa04022: cGMP -PKG signaling pathway ENDRA,BAD,PPP1CA 0.01875 0.003 hsa04064: NF-kappa B signaling pathway CXCL8,PTGS2 0.021505376 0.0136 hsa04926: Relaxin signaling pathway MAPK8,MAPK10,MAPK14 0.023076923 0.0018 hsa04068: FoxO signaling pathway MAPK8,MAPK10,MAPK14 0.023076923 0.0018 hsa04071: Sphingolipid signaling pathway MAPK8,MAPK10,MAPK14 0.025862069 0.0014 hsa04910: Insulin signaling pathway MAPK8,MAPK10,BAD,PPP1CA 0.029850746 0.00013 hsa04621: NOD-like receptor signaling pathway MAPK8,MAPK10,MAPK14,CXCL8,CASP1 0.030120482 0.0000197 hsa04024: cAMP signaling pathway ENDRA,MAPK8,BAD,MAPK10,PPP1CA,PPARA 0.030769231 0.00000373 hsa04912: GnRH signaling pathway MAPK8,MAPK10,MAPK14 0.034090909 0.00072 hsa04722: Neurotrophin signaling pathway MAPK8,MAPK10,MAPK14,BAD 0.034482759 0.00000853 hsa04012: ErbB signaling pathway MAPK8,MAPK10,BAD 0.036144578 0.00062 hsa04620: Toll-like receptor signaling pathway MAPK8,MAPK10,MAPK14,CXCL8 0.039215686 0.0000581 hsa03320: PPAR signaling pathway PPARA,PPARG,FABP2 0.041666667 0.00044 hsa04920: Adipocytokine signaling pathway MAPK8,MAPK10,PPARA 0.043478261 0.00041 hsa04917: Prolactin signaling pathway MAPK8,MAPK10,MAPK14 0.043478261 0.00041 hsa04664: Fc epsilon RI signaling pathway MAPK8,MAPK10,MAPK14 0.044776119 0.00039 hsa04668: TNF signaling pathway MAPK8,MAPK10,MAPK14,CASP3,PTGS2 0.046296296 0.00000413 hsa04370: VEGF signaling pathway MAPK8,MAPK10,BAD 0.050847458 0.00029 hsa04933: AGE-RAGE signaling pathway in diabetic complications MAPK8,MAPK10,MAPK14,CXCL8,CASP1 0.051020408 0.00000373 hsa04622: RIG-I-like receptor signaling pathway MAPK8,MAPK10,MAPK14,CXCL8 0.057142857 0.0000197 hsa04657: IL-17 signaling pathway MAPK8,MAPK10,MAPK14,CXCL8,CASP3,PTGS2 0.065217391 0.000000135 hsa05120: Epithelial cell signaling in Helicobacter pylori infection MAPK8,MAPK10,MAPK14,CXCL8,CASP3 0.075757576 0.000000954 Table 3 . Binding energy and interactions of potential three NSAIDs on MAPK8 (PDB ID:4YR8) Hydrogen Bond Interactions Hydrophobic Interactions Protein Ligand PubChem ID Symbol Binding energy(kcal/mol) Amino Acid Residue Amino Acid Residue 4YR8 6MNA 32176 M1 -7.1 Lys-218 Pro-221, Gly-199 Pro-254, Phe215 Cys-216, Gln-253 Pro-210, Lys-218 Glu-217, Lys-225 Mefenamic acid 4044 M2 -6.4 Glu-217 Trp-222, Val-211 Arg-208, Cys-216 Asn-193, Lys-218 Pro-211 Etodolac 3308 M3 -6.3 n/a Tyr-202, Lys-203 Met-200, Gly-201 Pro-221, Lys-218 Lys-251, Ser-307 Ala-306 Table 4 . Binding energy and interactions of potential twelve NSAIDs on MAPK10 (PDB ID: 3TTJ) Hydrogen Bond Interactions Hydrophobic Interactions Protein Ligand PubChem ID Symbol Binding energy(kcal/mol) Amino Acid Residue Amino Acid Residue 3TTJ Mefenamic acid 32176 R1 -6.4 Arg-107 Asp-207, Gln-75 Leu-206, Lys-93 Asn-194, Asp-207 Naproxen 4044 R2 -6.1 Asn-194, Lys-93 Arg-107, Asp-189 Val-225, Lys-191 Gln-75, Gly-73 Tolmetin 3308 R3 -6.7 Asn-194, Asp-189 Lys-106, Leu-210 Ala-211, Arg-110 Arg-230, Lys-191 Arg-107, Thr-103 Fenoprofen 3342 R4 -6.5 Lys-93, Lys-191 Ser-193, Ser-72 Asn-194 Val-78, Gly-73 Gln-75, Ala-74 Arg-107 Ketorolac 3826 R5 -7.1 Glu-111, Arg-107 Asp-207, Leu-206 Asn-194, Lys-93 Gln-75, Ser-193 Ser-72, Val-78 Gly-73 Ketoprofen 3825 R6 -6.5 Lys-93, Asn-194 Val-78, Leu-206 Ser-193 Arg-107, Gln-75 Gly-73 Ibuprofen 3672 R7 -5.6 Lys-93, Ser-193 Leu-206, Ala-74 Asn-194 Gly-73, Gln-75 Val-78 Flubiprofen 3394 R8 -6.9 Lys-191, Asp-189 Lys-93, Val-78 Asn-194 Gly-73, Arg-107 Gln-75 Oxaprozin 4614 R9 -7.1 Asn-194, Arg-107 Asp-189, Thr-103 Lys-191 Ser-217, Val-225 Arg-230 Sulindac 1548887 R10 -7.4 Asn-152 Arg-107, Asn-194 Lys-93, Ser-72 Gly-73, Ser-193 Ala-74 Diclofenac 3033 R11 -6.7 Asn-194 Ser-72, Gly-73 Ser-193, Gln-75 Arg-107, Lys-93 Leu-206, Val-78 Gly-71 Rofecoxib 5090 R12 -7.5 Asn-194, Lys-191 Asp-189, Arg-230 Ser-217 Thr-203, Leu-210 Gly-209, Ala-211 Arg-107 Table 5 . Binding energy and interactions of potential two NSAIDs on BAD (PDB ID: 1G5J) Hydrogen Bond Interactions Hydrophobic Interactions Protein Ligand PubChem ID Symbol Binding energy(kcal/mol) Amino Acid Residue Amino Acid Residue 1G5J 6MNA 32176 B1 -6.8 Trp-173, His-181 Arg-169, Tyr-124 Phe-127, Tyr-177 Thr-176 Indomethacin 3715 B2 -7.1 Asp-180 Arg-169, Tyr-124 Phe-127, Val-131 Glu-128, His-181 Thr-176, Trp-173 Supplementary Files SupplementaryFigureS1.pdf SupplementaryFigureS1.pdf SupplementaryTableS1.pdf SupplementaryTableS1.pdf SupplementaryTableS2.pdf SupplementaryTableS2.pdf SupplementaryTableS3.pdf SupplementaryTableS3.pdf SupplementaryTableS4.pdf SupplementaryTableS4.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 01 Mar, 2021 Reviews received at journal 25 Jan, 2021 Reviewers agreed at journal 23 Jan, 2021 Reviewers agreed at journal 08 Jan, 2021 Reviewers invited by journal 14 Dec, 2020 Editor assigned by journal 25 Nov, 2020 Editor invited by journal 25 Nov, 2020 Submission checks completed at journal 25 Nov, 2020 First submitted to journal 19 Nov, 2020 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-111615","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":5344971,"identity":"c26eb637-30eb-4f5b-86af-c3d0e14a1b32","order_by":0,"name":"Ki Kwang Oh","email":"","orcid":"","institution":"Kangwon National University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ki","middleName":"Kwang","lastName":"Oh","suffix":""},{"id":5344972,"identity":"fcdbf766-e60a-4ef6-8e11-05f58f55509b","order_by":1,"name":"Md. 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","description":"","filename":"Fig3.JPG","url":"https://assets-eu.researchsquare.com/files/rs-111615/v1/f3e426b511289402bb64c0c7.JPG"},{"id":3903032,"identity":"c6ce4ea7-486d-4231-b8d2-4de114b153fd","added_by":"auto","created_at":"2020-11-30 23:27:23","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":36549,"visible":true,"origin":"","legend":"Overlapping genes (228 genes) of NSAIDs related genes identified from SEA (529 genes) and STP (480 genes). ","description":"","filename":"Fig4.JPG","url":"https://assets-eu.researchsquare.com/files/rs-111615/v1/c46ad14b34bca2e1408d24b5.JPG"},{"id":3903035,"identity":"a0998557-913e-44ce-9e32-dda86ad026e4","added_by":"auto","created_at":"2020-11-30 23:27:23","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":35036,"visible":true,"origin":"","legend":"Overlapping genes (26 genes) between NSAIDs related 228 overlapped genes (A) and COVID-19 related 466 genes (B).","description":"","filename":"Fig5.JPG","url":"https://assets-eu.researchsquare.com/files/rs-111615/v1/878d4a35591db18a447fedf3.JPG"},{"id":3903038,"identity":"cad4bf46-8283-4790-b8bc-5dab0b64fbda","added_by":"auto","created_at":"2020-11-30 23:27:24","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":52875,"visible":true,"origin":"","legend":"Gene-gene interaction with 26 nodes and 78 edges in NSAIDs against COVID-19 via STRING analysis.\nNode: The number of networks of compounds\nEdge: The number of interactions between compounds and genes","description":"","filename":"Fig6.JPG","url":"https://assets-eu.researchsquare.com/files/rs-111615/v1/4c792601cf60494ec867edc3.JPG"},{"id":3903039,"identity":"c5ea7409-455d-4df7-b05d-8cb7986e282f","added_by":"auto","created_at":"2020-11-30 23:27:24","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":79125,"visible":true,"origin":"","legend":"Bubble chart of 26 signaling pathways related to the occurrence and progression of COVID-19.","description":"","filename":"Fig7.JPG","url":"https://assets-eu.researchsquare.com/files/rs-111615/v1/47c3f6f3ae0d7d235be3ee36.JPG"},{"id":3903040,"identity":"e62e7736-1942-4009-8b4c-a94858eeeaba","added_by":"auto","created_at":"2020-11-30 23:27:25","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":58422,"visible":true,"origin":"","legend":"Degree values of 12 genes associated with KEGG pathway in 26 signaling pathways.\nDegree value: The number of KEGG ID interacted with gene. \n","description":"","filename":"Fig8.JPG","url":"https://assets-eu.researchsquare.com/files/rs-111615/v1/5dcf8142c6573ea728ab5183.JPG"},{"id":3903041,"identity":"b767f959-53f0-4f00-9d24-9a17396983e0","added_by":"auto","created_at":"2020-11-30 23:27:25","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":491447,"visible":true,"origin":"","legend":"Molecular docking interaction between best docked NSAIDs and target proteins.\n(A)\t6MNA on 4YR8 (B) Rofecoxib on 3TTJ (C) Indomethacin on 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23:27:24","extension":"pdf","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":226953,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-111615/v1/dd9287f9b6d91b18d8cea7a9.pdf"}],"financialInterests":"","formattedTitle":"SARS-CoV-2 intervened by NSAIDs: A network pharmacology approach to decipher signaling pathway and interactive genes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAn initial outbreak of pneumonia caused by unknown etiology was first reported at Wuhan in Hubei Province, China, and alerted to the World Health Organization (WHO) by the Wuhan Municipal Health Commission on 31 December 2019 \u003csup\u003e1\u003c/sup\u003e. Later, the infectious disease experts detected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can rapidly transmit from person to person through interaction or respiratory droplets \u003csup\u003e2\u003c/sup\u003e. As a consequence of its tremendous spread in the world, WHO announced a changing level from epidemic to pandemic disease (COVID-19) on March 11, 2020 \u003csup\u003e3\u003c/sup\u003e. Although the symptoms are identical to pneumonia, however, a considerable number of COVID-19 infected patients showed no physical sign, thus can transmit the virus to others, as silently spread \u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eDue to the unavailability of a reliable vaccine, clinicians are utilizing anti-viral drugs and NSAIDs as a significant viable option for COVID-19 patients \u003csup\u003e5\u003c/sup\u003e. A recent study has reported that use of NSAIDs is safe for COVID-19 treatment without exposing specific negative side effects \u003csup\u003e6\u003c/sup\u003e. Though there is a lack of evidence whether combined NSAIDs treatment could worsen COVID-19 symptoms \u003csup\u003e7\u003c/sup\u003e, but researchers suggested that anti-inflammatory therapies might suppress the fatal cytokine storm of COVID-19 patients \u003csup\u003e8\u003c/sup\u003e. Additionally, WHO announced that no evidence of unwanted side effects was reported, particularly the risk of death with the administration of NSAIDs in COVID-19 patients \u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eCommonly, NSAIDs are used to treat diverse anti-inflammatory symptoms due to its good therapeutic efficacy \u003csup\u003e10\u003c/sup\u003e. However, one potential drug of interest is indomethacin which possesses both anti-inflammatory and antiviral properties. Its antiviral potentiality was first identified in 2006 during the outbreak of SARS-CoV \u003csup\u003e11\u003c/sup\u003e and subsequent attribution was also observed against SARS-CoV-2 \u003csup\u003e12\u003c/sup\u003e. A study on canine coronavirus \u003cem\u003e(in vitro)\u003c/em\u003e revealed that indomethacin could significantly suppress virus replication, thus protecting host cell from virus induced damage. Similar antiviral effect was also observed during \u003cem\u003ein vivo\u003c/em\u003e assessment where normal anti-inflammatory dose was found very effective \u003csup\u003e12,13\u003c/sup\u003e. Although there are many NSAIDs which may have possible therapeutic interventions against COVID-19, lack of scientific evidence has limited their broad application to COVID-19 patients. Hence, we aimed to identify the most potent NSAIDs and their mechanism(s) against COVID-19 through network pharmacology.\u003c/p\u003e\n\u003cp\u003eNetwork pharmacology can decode the mechanism(s) of drug action with an overall viewpoint , which focuses on pattern changing form \u0026ldquo;single protein target, single drug\u0026rdquo; to \u0026ldquo;multiple protein targets, multiple drugs\u0026rdquo; \u003csup\u003e14\u003c/sup\u003e. Currently, network pharmacology has been extensively utilized to explore multiple targets and unknown additional mechanism(s) against diverse diseases \u003csup\u003e15\u003c/sup\u003e. In this research, network pharmacology was applied to investigate the most potent NSAIDs and their novel mechanisms of action against COVID-19. Firstly, a total of 20 approved NSAIDs was selected via using public websites. The 20 NSAIDs and COVID-19 related genes were also identified using public databases. Next, the selected overlapping genes were discovered as target genes for analyzing anti-COVID-19. Finally, pathway enrichment analysis was performed to reveal the mechanism(s) of the most potent NSAIDs against COVID-19. Figure 1 shows overall workflow\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eInformation of NSAIDs \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of twenty FDA approved NSAIDs was selected. Table 1 and Figure 2 display the chemical information and structure of these NSAIDs. Among the twenty NSAIDs, nineteen NSAIDs were found as active drug and one \u0026ldquo;nabumetone\u0026rdquo; was a prodrug and its metabolite form is 6-methoxy-2-naphthylacetic acid (6MNA). Figure 3 shows nabumetone oxidized into 6MNA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNSAIDs linked to the 781 genes or COVID-19 related genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBy screening from two public databases (SEA and STP), a total of 781 NSAIDs related genes were identified (see Supplementary Table S1\u003cstrong\u003e)\u003c/strong\u003e. The overlapping genes (228 genes) selected from the two databases were shown (see Supplementary Table S2). Figure 4 displays the result of the overlapping genes. From the PubChem database, 466 COVID-19 related genes were identified (see Supplementary Table S3). The 26 overlapping genes were extracted between the 228 overlapped genes and 466 COVID-19 related genes (see Supplementary Table S4). Figure 5 shows the result of overlapping genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePathway enrichment analysis of overlapping genes and identification of significant genes against COVID-19 \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 6 displays the identified overlapping 26 genes were linked closely to each other through utilizing STRING. Based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis with \u0026ldquo;\u003cem\u003eHomo sapiens\u003c/em\u003e\u0026rdquo; mode, 26 signaling pathways from the 26 genes were revealed against COVID-19. Figure 7 shows the signaling pathways were plotted in the bubble chart through Rstudio. Table 2 provides the detailed description of the 26 signaling. Figure 8 shows that both MAPK8 and MAPK10 linked to 22 out of 26 signaling pathways, were determined as hub genes of NSAIDs against COVID-19. Coincidently, both MAPK8 and MAPK10 play major roles in all of the 22 signaling pathways by the RAS signaling pathways, suggesting that BAD (Bcl-2-associated death promoter) gene and the two hub genes (MAPK8 and MAPK10) are associated with the RAS signaling pathway against COVID-19. The interactions between NSAIDs and each gene were visualized with RStudio (see Supplementary Figure S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAffinity binding energy score on three genes of the most potent NSAIDs against\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOVID-19\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom the SEA and STP databases, it was revealed that MAPK8 gene is associated with three NSAIDs (6MNA, Mefenamic acid, and Etodolac), MAPK10 gene is related to twelve NSAIDs (Mefenamic acid, Naproxen, Tolmetin, Fenoprofen, Ketorolac, Ketoprofen, Ibuprofen, Flurbiprofen, Oxaprozin, Sulindac, Diclofenac, and Rofecoxib), BAD gene is involved with two NSAIDs (6MNA and Indomethacin).\u003c/p\u003e\n\u003cp\u003eFigure 9 displays the molecular docking was performed to evaluate the binding mode of these three genes against their associated NSAIDs, respectively, and the docking figures are depicted in Molecular docking score of M1-M3 on MAPK8 protein (PDB ID: 4YR8) was analyzed in the \u0026ldquo;\u003cem\u003eHomo Sapiens\u003c/em\u003e\u0026rdquo; mode. Based on the docking score, the order of priority of binding energy is given: M1\u0026gt;M2\u0026gt;M3. The three-affinity binding energy of M1-MAPK8, M2-MAPK8, and M3-MAPK8 indicated -7.1, -6.4, and -6.3 kcal/mol, respectively. The 6MNA (M1) had the strongest affinity on MAPK8. Interaction analysis of best-docked compound namely \u0026ldquo;6MNA\u0026rdquo; resulted one hydrogen bond (Lys-218) and seven hydrophobic bonds (Gly-88, Leu-86, Met-0, Val-44, Cys-1, Gly-46, and ASP-47). Table 3 provides the detailed information of binding energy and interactions. Molecular docking score of R1-R12 on MAPK10 protein (PDB ID: 3TTJ) was demonstrated in the \u0026ldquo;\u003cem\u003eHomo\u003c/em\u003e\u003cem\u003esapiens\u003c/em\u003e\u0026rdquo; mode. Based on the docking score, the priority of affinity binding energy is as follows: R12\u0026gt;R10\u0026gt; R9= R5\u0026gt; R8\u0026gt; R3= R11\u0026gt; R4 =R6 \u0026gt;R1 \u0026gt;R2 \u0026gt;R7. The twelve affinity binding energy of R1-MAPK10, R2-MAPK10, R3-MAPK10, R4 -MAPK10, R5-MAPK10, R6-MAPK10, R7-MAPK10, R8-MAPK10, R9-MAPK10, R10-MAPK10, R11-MAPK10, and R12-MAPK10 revealed -6.4, -6.1, -6.7, -6.5, -7.1, -6.5, -7.1, -6.5, -5.6, -6.9, -7.1, -7.4, -6.7, and -7.5 kcal/mol, respectively. The rofecoxib (R12) had the strongest affinity on MAPK10. Interaction analysis of best-docked compound namely \u0026ldquo;Rofecoxib\u0026rdquo; resulted three hydrogen bonds (Asn-194, Lys-191, Ser-217) and seven hydrophobic bonds (Asp-189, Arg-230, Thr-203, Leu-210, Gly-209, Ala-211, Arg-107). Table 4 provides the detailed information of binding energy and interactions. Molecular docking score of B1-B2 on BAD protein (PDB ID: 1G5J) was also analyzed in the \u0026ldquo;\u003cem\u003eHomo Sapiens\u003c/em\u003e\u0026rdquo; mode. Based on the docking score, the order of priority of binding energy is given: B2\u0026gt;B1. The two-affinity binding energy of B1-BAD and B2-BAD demonstrated -6.8 and -7.1 kcal/mol, respectively. The indomethacin (B2) had the strongest affinity on BAD. Interaction analysis of best-docked compound namely \u0026ldquo;Indomethacin\u0026rdquo; resulted one hydrogen bond (Asp-180) and eight hydrophobic bonds (Arg-169, Tyr-124, Phe-127, Val-131, Glu-128, His-181, Thr-176, Trp-173). Table 5 provides the detailed information of binding energy and interactions. Figure 10 depicts that the three NSAIDs (6MNA, Rofecoxib, and Indomethacin) might be the potential anti-inflammatory agents against COVID-19\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003eNSAIDs linked to selected genes or COVID-19 related genes \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on SMILES, targeted genes of the NSAIDs approved by FDA (U.S. Food \u0026amp; Drug Administration) were identified utilizing Similarity Ensemble Approach (SEA) (http://sea.bkslab.org/) and Swiss Target Prediction (STP) (http://www.swisstargetprediction.ch/) with the \u0026ldquo;\u003cem\u003eHomo\u003c/em\u003e\u003cem\u003esapience\u003c/em\u003e\u0026rdquo; mode. COVID-19 related genes were identified by browsing PubChem (https://pubchem.ncbi.nlm.nih.gov/). The overlapping genes between NSAIDs targeted genes and COVID-19 related genes were identified and visualized by Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNetwork construction of interactions between \u003c/strong\u003e\u003cstrong\u003eNSAIDs targeted genes\u003c/strong\u003e\u003cstrong\u003eand COVID\u003c/strong\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003cstrong\u003e19\u003c/strong\u003e\u003cstrong\u003erelated genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overlapping genes interactions between NSAIDs targeted genes and COVID-19 related genes were analyzed by STRING (https://string-db.org/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSignaling pathway enrichment analysis of overlapping genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenes-genes interaction figure was visualized by STRING (https://string-db.org/). RStudio plotted the bubble chart of KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of overlapping genes. Using RStudio, the most significant genes among signaling pathways and correlation of NSAIDs on the most significant genes were analyzed. The results suggest a hint at the unknown molecular mechanism(s) of the most potent NSAIDs against COVID-19.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBinding affinity energy value of the most potent NSAIDs on genes \u003cem\u003ein silico\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe binding affinity energy measurement of the uttermost NSAIDs on key genes was established by Autodock (http://autodock.scripps.edu/), Vina (http://vina.scripps.edu/), Pymol (https://pymol.org/2/).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eNSAIDs-genes networking analysis demonstrated that the clinical effect of NSAIDs on COVID-19 was directly related to 26 genes. The results of KEGG pathway enrichment analysis of 26 genes suggested that 26 signaling pathways were associated with the occurrence and development of the COVID-19 symptoms. The correlations of 26 signaling pathways with COVID-19 symptoms were succinctly discussed as follows. PPAR (\u003cem\u003ePeroxisome Proliferator-Activated Receptor\u003c/em\u003e) signaling pathway: A report shows that PPAR\u0026gamma; (\u003cem\u003ePeroxisome Proliferator-Activated Receptor-gamma)\u003c/em\u003e, PPAR\u0026alpha; (\u003cem\u003ePeroxisome Proliferator-Activated Receptor-alpha)\u003c/em\u003e, and PPAR\u0026beta;/\u0026delta; (\u003cem\u003ePeroxisome Proliferator-Activated Receptor-beta/delta\u003c/em\u003e) agonists have anti-inflammatory and immunomodulatory functions \u003csup\u003e16\u003c/sup\u003e. MAPK (\u003cem\u003eMitogen-Activated Protein Kinase)\u003c/em\u003e signaling pathway: The mechanisms of p38 MAPK inactivation might be a significant therapy against the SARS infected cells \u003csup\u003e17\u003c/sup\u003e. Additionally, MAPK stimulates cytokine production such as IL-10 (Interleukin 10), TNF- \u0026alpha; (Tumor Necrosis Factor-Alpha), IL-4 (Interleukin 4), and IFN- \u0026gamma; (Interferon gamma) \u003csup\u003e18\u003c/sup\u003e. This report shows a coincidence with our suggested strategy in this study. ErbB (Erythroblastic Leukemia Viral Oncogene Homolog) signaling pathway: ErbB signaling reduces the proinflammatory activation in cardiac cells \u003csup\u003e19\u003c/sup\u003e. RAS (Renin Angiotensin System) signaling pathway: Inactivation of RAS can reduce tissue damage in COVID-19 patients. In addition, ACE (Angiotensin Converting Enzyme) antagonists block the response of RAS system \u003csup\u003e20\u003c/sup\u003e. cGMP-PKG (Cyclic GMP-Protein Kinase G) signaling pathway: The activation of cGMP-PKG signaling inhibits inflammatory response in the prostate, and also decreases CCL5 (C-C Motif Chemokine Ligand 5) release in CD8\u0026nbsp;\u003csup\u003e+\u003c/sup\u003e\u0026nbsp;T cells (Cluster of Differentiation 8 T cells) \u003csup\u003e21\u003c/sup\u003e. cAMP (Cyclic Adenosine Monophosphate) signaling pathway:\u0026nbsp;The elevation of cAMP leads to diverse cellular effects, such as airway smooth muscle relaxation, repressed effects on cellular inflammation, and immune responses \u003csup\u003e22\u003c/sup\u003e. NF-\u0026kappa;B (Nuclear Factor\u0026nbsp;kappa-light-chain-enhancer of activated B cells) signaling pathway: Activation of the NF-\u0026kappa;B signaling pathway gives rise to the inflammation induced by the SARS-CoV infection. In contrast, NF-\u0026kappa;B inhibitors are the potential antivirals against SARS-CoV, and can also contribute to other pathogenic human coronaviruses \u003csup\u003e23\u003c/sup\u003e. FOXO (Forkhead box protein O1) signaling pathway: Decrease of FOXO3 (Forkhead box protein O3) in T cells inhibits apoptosis, enhances multifunction of CD8 cells, and elevates viral control \u003csup\u003e24\u003c/sup\u003e. Sphingolipid signaling pathway: Sphingolipids play a vital role to protect lung from damages, and the control of sphingolipid signaling pathways may give a good therapeutic efficacy \u003csup\u003e25\u003c/sup\u003e. Wnt (Wingless/Integrated) signaling pathway: Wnt signaling involves with the prime inflammatory pathways like intestinal inflammation. Also, elucidating the mutual modes of Wnt ligands and cytokines manifest new treatment strategies for chronic colitis and other inflammatory diseases \u003csup\u003e26\u003c/sup\u003e. VEGF (Vascular Endothelial Growth Factor) signaling pathway: A report suggested that VEGFA (Vascular Endothelial Growth Factor A) is inhibited by the activation of ACE2 (Angiotensin-Converting Enzyme 2). However, ACE2 is downregulated by the attack of COVID-19. Subsequently, activation of VEGFA elevates vascular permeability and severity of endothelial damage \u003csup\u003e27\u003c/sup\u003e. TLR (Toll-like receptor) signaling pathway: Toll-like receptors (TLRs) play a pivotal role in the innate immune system and contribute to defend host cells by recognizing PAMPs (Pathogen-Associated Molecular Patterns) induced by various microbes \u003csup\u003e28\u003c/sup\u003e. The activation of TLRs triggers an array of response resulting into expression of different cytokines and chemokines, phagocytosis, and even apoptotic case activation to induce programmed cell death \u003csup\u003e29\u003c/sup\u003e. NOD-like receptor (NLR) signaling pathway: Nod-like receptors (NLRs) have been revealed as the major microbial signals that take part in the universal immune responses to infection, and also contribute to the prevention of infections \u003csup\u003e30\u003c/sup\u003e. RIG-I-like receptor (RLR) signaling pathway: RIG-I-like receptors (RLRs) play a vital role in pathogen sensor of RNA virus infection, which enhances the antiviral immunity by sensing foreign RNA \u003csup\u003e31\u003c/sup\u003e. IL-17 (Interleukin-17) signaling pathway: IL-17 receptor inhibitors are widely used to ameliorate the inflammatory acuteness to date. Furthermore, it is a potential target to suppress severe inflammation induced by COVID-19 \u003csup\u003e32\u003c/sup\u003e. Fc epsilon RI signaling pathway: Fc epsilon RI interconnecting causes mast cell degranulation and synthesis of proinflammatory mediators \u003csup\u003e33\u003c/sup\u003e.\u0026nbsp;TNF (Tumor Necrosis Factor) signaling pathway: TNF deficit is associated with dysfunctional secretion of inflammatory cytokine, leading to lung pathology and death during respiratory poxvirus infection, and thus TNF is very significant element for regulating inflammation \u003csup\u003e34\u003c/sup\u003e. Neurotrophin signaling pathway: COVID-19 causes severe brain damage and destruction of central nervous system derived from neurotrophin (Huang and Reichardt 2001). Insulin signaling pathway: Obesity-oriented insulin resistance is associated with the induction of proinflammatory macrophage, leads to inflammation of adipose tissue \u003csup\u003e37\u003c/sup\u003e. GnRH (Gonadotropin-Releasing Hormone) signaling pathway: Disrupted BBB (Blood Brain Barrier) by viral infection, lymphocytes (B and T cells), monocytes, and granulocytes can penetrate in the brain parenchyma which induce inflammation, resulting in dysregulation of GnRH neurons. Additionally, the inflammation of GnRH neurons inhibits GnRH transport through proinflammatory cytokines by impairing the cytoskeleton \u003csup\u003e38\u003c/sup\u003e. Prolactin signaling pathway: HIV (Human Immunodeficiency Virus) patients have greater prolactin quantity compared to others. Besides, prolactin is regarded as a cytokine to react in immune system \u003csup\u003e39,40\u003c/sup\u003e. Adipocytokine signaling pathway: Adipocytokines stimulate inflammation and disrupting immune response which cause tissue damage. Adipocytokines might also induce proinflammation in RA (Rheumatoid Arthritis) patients and thus lead to the development of bone damage \u003csup\u003e41\u003c/sup\u003e. Oxytocin signaling pathway: Oxytocin interrupts the production of proinflammatory cytokines by inactivating of the eIF-2\u0026alpha;\u0026ndash;ATF4 (Eukaryotic Initiation Factor -2 alpha- Activating Transcription Factor 4) pathway \u003csup\u003e42\u003c/sup\u003e. Relaxin signaling pathway: Relaxin inhibitors are good therapeutic targets to suppress inflammation caused by airway dysfunction \u003csup\u003e43\u003c/sup\u003e. AGE-RAGE (Advanced Glycation End product -Receptor of Advanced Glycation End product) signaling pathway in diabetic complications: The binding of AGE to its receptor RAGE can trigger the cytokine production, thus, can cause tissue damages, while the blockage of AGE-RAGE can effectively curtail the inflammation \u003csup\u003e44\u003c/sup\u003e. Epithelial cell signaling in \u003cem\u003eHelicobacter pylori\u003c/em\u003e infection: \u003cem\u003eHelicobacter pylori \u003c/em\u003einterrupts T and B cell signaling to set immune system. It is apparent that COVID-19 patients with \u003cem\u003eHelicobacter pylori\u003c/em\u003e might be vulnerable to inflammatory responses \u003csup\u003e45\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eGenerally, SARS-CoV-2 invades in the lungs and throat, induces excessive inflammation, which causes the secretion of cytokines, resulting in severe complications like acute respiratory failure, pneumonia, and acute liver injury (Reyes and Peniche 2019; Nile et al. 2020). Researchers suggested that RAS is a potential route for SARS-CoV-2 induced cellular infection which may be linked to the imbalance of RAS. It was discovered that ACE-2 is the functional receptor for the SARS-CoV-2 to trigger infection in the lung alveolar epithelial cells. The internalization of virus leads to downregulate the ACE-2 on host cell surface that could cause the elevation and demotion of the angiotensin-II (AII) and angiotensin 1-7 (A\u003csub\u003e1-7\u003c/sub\u003e) respectively. Such an imbalance between these angiotensins may induce deleterious effects in the lung and heart. Thus, the SARS-CoV-2 affects humans through this mechanism \u003csup\u003e49\u0026ndash;52\u003c/sup\u003e. Therefore, blockade of the RAS may restore the RAS balance by reducing the deleterious effects associated with angiotensin-II \u003csup\u003e53\u003c/sup\u003e. Recent evidence showed that RAS inhibitors might be a promising target for relieving acute-severe pneumonia caused by the COVID-19 \u003csup\u003e54\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eInterestingly, our study identified that the three genes (MAPK 8, MAPK 10, and BAD) are mainly associated with the RAS signaling pathway. MAPK 8 and MAPK 10 are members of the MAPK family which are the key mediators of the inflammation, vasoconstriction, and thrombosis. Besides, overwhelming heart and lung injury in COVID-19 infection might be due to the overactivation of MAPK \u003csup\u003e55\u003c/sup\u003e. Therefore, inactivation of these genes can also be a viable strategy for relieving COVID-19 induced organ injury. In addition, disposal of inflammatory cells by promoting the cell death can be an innovative approach to control excessive inflammation. In this regard, inhibition of the anti-apoptotic Bcl-2 gene can also be a potential target to lessen inflammation \u003csup\u003e56,57\u003c/sup\u003e. Our findings also explored that MAPK8, MAPK10 and BAD genes are related to three, twelve, and two NSAIDs, respectively. During the molecular docking analysis, 6MNA, rofecoxib, and indomethacin revealed promising binding affinity along with highest docking score against MAPK8, MAPK10 and BAD genes, respectively, which indicated that the three (6MNA, Rofecoxib, and Indomethacin) NSAIDs are very potential among all others, may possibly block the RAS signaling pathway by inactivating its associated genes (MAPK8, MAPK10 and BAD), and subsequently suppress SARS-CoV-2 induced cytokine storm.\u003c/p\u003e\n\u003cp\u003eAmong various NSAIDs, indomethacin is a current drug of interest to the clinicians. Primary care physicians (New York) reported that indomethacin had been prescribed to a large number of COVID-19 patients and observed quick recovery from cough, pain, and other symptoms. Such improvements and well-being benefits were not evident in the case of ibuprofen and hydroxychloroquine implementation (Vaduganathan et al. 2020b; Little 2020). Importantly, many researchers previously reported varying degrees of antiviral activity of indomethacin against herpesvirus \u003csup\u003e60\u003c/sup\u003e, pseudorabies virus \u003csup\u003e61\u003c/sup\u003e, cytomegalovirus \u003csup\u003e62\u003c/sup\u003e, hepatitis B virus \u003csup\u003e63\u003c/sup\u003e, vesicular stomatitis virus \u003csup\u003e64\u003c/sup\u003e, rotavirus \u003csup\u003e65\u003c/sup\u003e, and canine coronavirus \u003csup\u003e11\u003c/sup\u003e. In contrast, 6MNA (active metabolite of nabumetone) and Rofecoxib are also the potential anti-inflammatory drugs, but studies disclosed that they are less potent compared to the indomethacin \u003csup\u003e66,67\u003c/sup\u003e. Hence, such compelling outcomes indicate that indomethacin can be considered to use alone or in combination for antiviral therapy which may assist in combating human coronavirus (SARS-CoV-2).\u003c/p\u003e\n\u003cp\u003eIn summary, NSAIDs-genes network suggested that the therapeutic effect of NSAIDs on COVID-19 was associated with 26 signaling pathways. This study suggests that 6MNA, rofecoxib, and indomethacin are the most potent NSAIDs against COVID-19. The basis of this research is an understanding of how these NSAIDs (which stimulates anti-inflammatory processes against COVID-19) work on COVID-19 patients. That scientific evidence informs the selection of NSAIDs, in turn, provides for clinical design against COVID-19. Our research suggests that the inhibition of BAD-Indomethacin with other two hub genes MAPK8-6MNA, MAPK10-Rofecoxib might play cumulative actions by inactivating the RAS signaling pathway against COVID-19. Most recently, efficacy of indomethacin against COVID-19 has been approved clinically. Our study presents that indomethacin is a potent therapeutic candidate to relieve COVID-19 symptoms, which is in line with the many previous studies. However, further clinical trial on indomethacin should be warranted in COVID-19 patients in order to slow down the progression of SARS-CoV-2 and mitigating the severity as well.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACE: Angiotensin-Converting Enzyme;\u003c/p\u003e\n\u003cp\u003eACE2:\u0026nbsp;Angiotensin-Converting Enzyme 2;\u003c/p\u003e\n\u003cp\u003eAGE-RAGE: Advanced Glycation End product /Receptor of Advanced Glycation End product;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBAD: Bcl-2-Associated Death promoter;\u003c/p\u003e\n\u003cp\u003eBBB: Blood Brain Barrier;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ecAMP: Cyclic Adenosine MonoPhosphate;\u003c/p\u003e\n\u003cp\u003eCCL5 (C-C Motif Chemokine Ligand 5);\u003c/p\u003e\n\u003cp\u003eCD8 \u003csup\u003e+\u003c/sup\u003e T cells: Cluster of Differentiation 8 T cells;\u003c/p\u003e\n\u003cp\u003ecGMP-PKG:\u0026nbsp;cyclic Guanosine MonoPhosphate - Protein Kinase G;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCOVID-19: SARS-CoV-2\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003evirus;\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eeIF-2\u0026alpha;\u0026ndash;ATF4\u0026nbsp;(Eukaryotic Initiation Factor -2 alpha- Activating Transcription Factor 4);\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eErbB:\u0026nbsp;\u003c/em\u003eErythroblastic Leukemia Viral Oncogene Homolog;\u003c/p\u003e\n\u003cp\u003eFDA: U.S. Food \u0026amp; Drug Administration;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFOXO: FOrkhead boX protein O;\u003c/p\u003e\n\u003cp\u003eGnRH:\u0026nbsp;Gonadotropin-Releasing Hormone;\u003c/p\u003e\n\u003cp\u003eHIV: Human Immunodeficiency Virus;\u003c/p\u003e\n\u003cp\u003eIFN- \u0026gamma;: Interferon gamma;\u003c/p\u003e\n\u003cp\u003eIL-4: Interleukin 4;\u003c/p\u003e\n\u003cp\u003eIL-10: Interleukin 10;\u003c/p\u003e\n\u003cp\u003eIL-17: Interleukin 17;\u003c/p\u003e\n\u003cp\u003eKEGG: Kyoto Encyclopedia of Genes and Genomes;\u003c/p\u003e\n\u003cp\u003eMAPK: \u003cem\u003eMitogen-Activated Protein Kinase;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMAPK8: \u003cem\u003eMitogen-Activated Protein Kinase\u0026nbsp;8;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMAPK10: \u003cem\u003eMitogen-Activated Protein Kinase\u0026nbsp;10;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNF- \u0026kappa;B: Nuclear Factor Kappa-light-chain-enhancer of activated B cells;\u003c/p\u003e\n\u003cp\u003eNLR: Nod-Like Receptor;\u003c/p\u003e\n\u003cp\u003eNLRs: Nod-Like Receptors;\u003c/p\u003e\n\u003cp\u003eNSAIDs: Non-Steroidal Anti-Inflammatory Drugs;\u003c/p\u003e\n\u003cp\u003ePPAR:\u003cem\u003e\u0026nbsp;\u003cem\u003ePeroxisome Proliferator-Activated Receptors;\u003c/em\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePPAR\u0026alpha;: \u003cem\u003ePeroxisome Proliferator-Activated Receptor-alpha;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePPAR\u0026gamma;: \u003cem\u003ePeroxisome Proliferator-Activated Receptor-gamma;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePPAR\u0026beta;/\u0026delta;: \u003cem\u003ePeroxisome Proliferator-Activated Receptor-beta/delta;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePAMPs: Pathogen-Associated Molecular Patterns;\u003c/p\u003e\n\u003cp\u003eRA: Rheumatoid Arthritis;\u003c/p\u003e\n\u003cp\u003eRAS: Renin Angiotensin System;\u003c/p\u003e\n\u003cp\u003eRLR: RIG-I-Like Receptor;\u003c/p\u003e\n\u003cp\u003eRLRs: RIG-I-Like Receptors;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSARS-CoV-2: Severe Acute Respiratory Syndrome CoronaVirus 2;\u003c/p\u003e\n\u003cp\u003eSEA: Similarity Ensemble Approach;\u003c/p\u003e\n\u003cp\u003eSTP: Swiss Target Prediction;\u003c/p\u003e\n\u003cp\u003eTLR: Toll-like receptor;\u003c/p\u003e\n\u003cp\u003eTLRs: Toll-like receptors;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTNF: Tumor Necrosis Factor;\u003c/p\u003e\n\u003cp\u003eTNF-\u0026alpha;: Tumor Necrosis Factor-Alpha;\u003c/p\u003e\n\u003cp\u003eVEGF: \u003cem\u003eVascular Endothelial Growth Factor;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eVEGFA:\u003cem\u003e\u0026nbsp;\u003cem\u003eVascular Endothelial Growth Factor A;\u003c/em\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization;\u003c/p\u003e\n\u003cp\u003eWnt: Wingless/Integrated\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article (and its Supplementary Information files).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was acknowledged by the Department of Bio-Health Technology, Kangwon National University, Chuncheon 24341, Republic of Korea.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKi Kwang Oh and Md. Adnan\u003c/strong\u003e: Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing - Original Draft. \u003cstrong\u003eKi Kwang Oh and Md. Adnan\u003c/strong\u003e: Software, Investigation, Data Curation. \u003cstrong\u003eKi Kwang Oh and Md. Adnan\u003c/strong\u003e: Validation, Writing - Review \u0026amp; Editing. \u003cstrong\u003eDong Ha Cho\u003c/strong\u003e: Supervision, Project administration\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHarapan, H. \u003cem\u003eet al.\u003c/em\u003e Coronavirus disease 2019 (COVID-19): A literature review. \u003cem\u003eJ. Infect. Public Health\u003c/em\u003e (2020).\u003c/li\u003e\n\u003cli\u003ePeric\u0026agrave;s, J. M. \u003cem\u003eet al.\u003c/em\u003e COVID-19: From epidemiology to treatment. \u003cem\u003eEur. Heart J.\u003c/em\u003e (2020) doi:10.1093/eurheartj/ehaa462.\u003c/li\u003e\n\u003cli\u003eAstuti, I. \u0026amp; Ysrafil. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): An overview of viral structure and host response. \u003cem\u003eDiabetes Metab. Syndr. Clin. Res. Rev.\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, 407\u0026ndash;412 (2020).\u003c/li\u003e\n\u003cli\u003eOran, D. P. \u0026amp; Topol, E. J. Prevalence of Asymptomatic SARS-CoV-2 Infection. \u003cem\u003eAnn. Intern. Med.\u003c/em\u003e (2020) doi:10.7326/m20-3012.\u003c/li\u003e\n\u003cli\u003eWu, R. \u003cem\u003eet al.\u003c/em\u003e An Update on Current Therapeutic Drugs Treating COVID-19. \u003cem\u003eCurrent Pharmacology Reports\u003c/em\u003e vol. 6 56\u0026ndash;70 (2020).\u003c/li\u003e\n\u003cli\u003eOzili, P. COVID-19 in Africa: socio-economic impact, policy response and opportunities. \u003cem\u003eInt. J. Sociol. Soc. Policy\u003c/em\u003e (2020) doi:10.1108/IJSSP-05-2020-0171.\u003c/li\u003e\n\u003cli\u003eCapuano, A., Scavone, C., Racagni, G. \u0026amp; Scaglione, F. NSAIDs in patients with viral infections, including Covid-19: Victims or perpetrators? \u003cem\u003ePharmacol. Res.\u003c/em\u003e\u003cstrong\u003e157\u003c/strong\u003e, 104849 (2020).\u003c/li\u003e\n\u003cli\u003eZhang, W. \u003cem\u003eet al.\u003c/em\u003e The use of anti-inflammatory drugs in the treatment of people with severe coronavirus disease 2019 (COVID-19): The experience of clinical immunologists from China. \u003cem\u003eClin. Immunol.\u003c/em\u003e 108393 (2020).\u003c/li\u003e\n\u003cli\u003eSodhi, M. \u0026amp; Etminan, M. Safety of Ibuprofen in Patients With COVID-19: Causal or Confounded? \u003cem\u003eChest\u003c/em\u003e vol. 158 55\u0026ndash;56 (2020).\u003c/li\u003e\n\u003cli\u003eMeek, I. L., van de Laar, M. A. F. J. \u0026amp; Vonkeman, H. E. Non-steroidal anti-inflammatory drugs: An overview of cardiovascular risks. \u003cem\u003ePharmaceuticals\u003c/em\u003e vol. 3 2146\u0026ndash;2162 (2010).\u003c/li\u003e\n\u003cli\u003eAmici, C. \u003cem\u003eet al.\u003c/em\u003e Indomethacin has a potent antiviral activity against SARS coronavirus. \u003cem\u003eAntivir. Ther.\u003c/em\u003e\u003cstrong\u003e11\u003c/strong\u003e, 1021 (2006).\u003c/li\u003e\n\u003cli\u003eXu, T., Gao, X., Wu, Z., Selinger, D. W. \u0026amp; Zhou, Z. Indomethacin has a potent antiviral activity against SARS CoV-2 in vitro and canine coronavirus in vivo. \u003cem\u003ebioRxiv\u003c/em\u003e (2020).\u003c/li\u003e\n\u003cli\u003eRussell, B., Moss, C., Rigg, A. \u0026amp; Van Hemelrijck, M. COVID-19 and treatment with NSAIDs and corticosteroids: should we be limiting their use in the clinical setting? \u003cem\u003eEcancermedicalscience\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, (2020).\u003c/li\u003e\n\u003cli\u003eOh, K. K., Adnan, M. \u0026amp; Cho, D. H. Network pharmacology approach to bioactive chemical compounds identified from Lespedeza bicolor lignum methanol extract by GC\u0026ndash;MS for amelioration of hepatitis. \u003cem\u003eGene Reports\u003c/em\u003e 100851 (2020).\u003c/li\u003e\n\u003cli\u003eTang, J. \u0026amp; Aittokallio, T. Network Pharmacology Strategies Toward Multi-Target Anticancer Therapies: From Computational Models to Experimental Design Principles. \u003cem\u003eCurr. Pharm. Des.\u003c/em\u003e\u003cstrong\u003e20\u003c/strong\u003e, 23\u0026ndash;36 (2014).\u003c/li\u003e\n\u003cli\u003eBelvisi, M. G. \u0026amp; Mitchell, J. A. Targeting PPAR receptors in the airway for the treatment of inflammatory lung disease. \u003cem\u003eBritish Journal of Pharmacology\u003c/em\u003e vol. 158 994\u0026ndash;1003 (2009).\u003c/li\u003e\n\u003cli\u003eMizutani, T., Fukushi, S., Saijo, M., Kurane, I. \u0026amp; Morikawa, S. Phosphorylation of p38 MAPK and its downstream targets in SARS coronavirus-infected cells. \u003cem\u003eBiochem. Biophys. Res. Commun.\u003c/em\u003e\u003cstrong\u003e319\u003c/strong\u003e, 1228\u0026ndash;1234 (2004).\u003c/li\u003e\n\u003cli\u003eDe Souza, A. P. \u003cem\u003eet al.\u003c/em\u003e MAPK involvement in cytokine production in response to Corynebacterium pseudotuberculosis infection. \u003cem\u003eBMC Microbiol.\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eRyzhov, S. \u003cem\u003eet al.\u003c/em\u003e ERBB signaling attenuates proinflammatory activation of nonclassical monocytes. \u003cem\u003eAm. J. Physiol. Circ. Physiol.\u003c/em\u003e\u003cstrong\u003e312\u003c/strong\u003e, H907\u0026ndash;H918 (2017).\u003c/li\u003e\n\u003cli\u003eAleksova, A. \u003cem\u003eet al.\u003c/em\u003e COVID-19 and renin-angiotensin system inhibition: role of angiotensin converting enzyme 2 (ACE2) - Is there any scientific evidence for controversy? \u003cem\u003eJournal of Internal Medicine\u003c/em\u003e (2020) doi:10.1111/joim.13101.\u003c/li\u003e\n\u003cli\u003eJin, S. \u003cem\u003eet al.\u003c/em\u003e Activation of cGMP/PKG/p65 signaling associated with PDE5‐Is downregulates CCL5 secretion by CD8 \u003csup\u003e+\u003c/sup\u003e T cells in benign prostatic hyperplasia. \u003cem\u003eProstate\u003c/em\u003e\u003cstrong\u003e79\u003c/strong\u003e, 909\u0026ndash;919 (2019).\u003c/li\u003e\n\u003cli\u003eYan, K., Gao, L. N., Cui, Y. L., Zhang, Y. \u0026amp; Zhou, X. The cyclic AMP signaling pathway: Exploring targets for successful drug discovery (review). \u003cem\u003eMol. Med. Rep.\u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e, 3715\u0026ndash;3723 (2016).\u003c/li\u003e\n\u003cli\u003eDeDiego, M. L. \u003cem\u003eet al.\u003c/em\u003e Inhibition of NF-\u0026nbsp;B-Mediated Inflammation in Severe Acute Respiratory Syndrome Coronavirus-Infected Mice Increases Survival. \u003cem\u003eJ. Virol.\u003c/em\u003e\u003cstrong\u003e88\u003c/strong\u003e, 913\u0026ndash;924 (2014).\u003c/li\u003e\n\u003cli\u003eSullivan, J. A., Kim, E. H., Plisch, E. H. \u0026amp; Suresh, M. FOXO3 Regulates the CD8 T Cell Response to a Chronic Viral Infection. \u003cem\u003eJ. Virol.\u003c/em\u003e\u003cstrong\u003e86\u003c/strong\u003e, 9025\u0026ndash;9034 (2012).\u003c/li\u003e\n\u003cli\u003eAbu-Farha, M. \u003cem\u003eet al.\u003c/em\u003e The role of lipid metabolism in COVID-19 virus infection and as a drug target. \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e vol. 21 (2020).\u003c/li\u003e\n\u003cli\u003eMoparthi, L. \u0026amp; Koch, S. Wnt signaling in intestinal inflammation. \u003cem\u003eDifferentiation\u003c/em\u003e vol. 108 24\u0026ndash;32 (2019).\u003c/li\u003e\n\u003cli\u003eTurkia, M. COVID-19 As An Endothelial Disease and Its Relationship to Vascular Endothelial Growth Factor (VEGF) and Iodide. \u003cem\u003eSSRN Electron. J.\u003c/em\u003e (2020) doi:10.2139/ssrn.3604987.\u003c/li\u003e\n\u003cli\u003eKawasaki, T. \u0026amp; Kawai, T. Toll-like receptor signaling pathways. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e vol. 5 (2014).\u003c/li\u003e\n\u003cli\u003eAshayeri Ahmadabad, R., Khaleghi Ghadiri, M. \u0026amp; Gorji, A. The role of Toll-like receptor signaling pathways in cerebrovascular disorders: The impact of spreading depolarization. \u003cem\u003eJournal of Neuroinflammation\u003c/em\u003e vol. 17 1\u0026ndash;13 (2020).\u003c/li\u003e\n\u003cli\u003eCarneiro, L. A. M., Travassos, L. H. \u0026amp; Girardin, S. E. Nod-like receptors in innate immunity and inflammatory diseases. \u003cem\u003eAnnals of Medicine\u003c/em\u003e vol. 39 581\u0026ndash;593 (2007).\u003c/li\u003e\n\u003cli\u003eChan, Y. K. \u0026amp; Gack, M. U. RIG-I-like receptor regulation in virus infection and immunity. \u003cem\u003eCurrent Opinion in Virology\u003c/em\u003e vol. 12 7\u0026ndash;14 (2015).\u003c/li\u003e\n\u003cli\u003ePacha, O., Sallman, M. A. \u0026amp; Evans, S. E. COVID-19: a case for inhibiting IL-17? \u003cem\u003eNature Reviews Immunology\u003c/em\u003e vol. 20 345\u0026ndash;346 (2020).\u003c/li\u003e\n\u003cli\u003eKlemm, S. \u0026amp; Ruland, J. Inflammatory signal transduction from the Fc\u0026epsilon;RI to NF-\u0026kappa;B. \u003cem\u003eImmunobiology\u003c/em\u003e vol. 211 815\u0026ndash;820 (2006).\u003c/li\u003e\n\u003cli\u003eJunaliah Tuazon Kels, M. \u003cem\u003eet al.\u003c/em\u003e TNF deficiency dysregulates inflammatory cytokine production leading to lung pathology and death during respiratory poxvirus infection. \u003cem\u003ebioRxiv\u003c/em\u003e 2019.12.22.883728 (2019) doi:10.1101/2019.12.22.883728.\u003c/li\u003e\n\u003cli\u003eCOVID-19: Severe brain damage possible even with mild symptoms | Science| In-depth reporting on science and technology | DW | 09.07.2020. https://www.dw.com/en/coronavirus-brain-damage/a-54111054.\u003c/li\u003e\n\u003cli\u003eHuang, E. J. \u0026amp; Reichardt, L. F. Neurotrophins: Roles in neuronal development and function. \u003cem\u003eAnnual Review of Neuroscience\u003c/em\u003e vol. 24 677\u0026ndash;736 (2001).\u003c/li\u003e\n\u003cli\u003eShimobayashi, M. \u003cem\u003eet al.\u003c/em\u003e Insulin resistance causes inflammation in adipose tissue. \u003cem\u003eJ. Clin. Invest.\u003c/em\u003e\u003cstrong\u003e128\u003c/strong\u003e, 1538\u0026ndash;1550 (2018).\u003c/li\u003e\n\u003cli\u003eBarab\u0026aacute;s, K., Szab\u0026oacute;-Meleg, E. \u0026amp; \u0026Aacute;brah\u0026aacute;m, I. M. Effect of inflammation on female gonadotropin-releasing hormone (GnRH) neurons: Mechanisms and consequences. \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e vol. 21 (2020).\u003c/li\u003e\n\u003cli\u003eAcharya, S., Fernando, R. \u0026amp; Gama, R. \u003cem\u003eCase Report Gynaecomastia, hyperprolactinaemia and HIV infection\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eBorba, V. V., Zandman-Goddard, G. \u0026amp; Shoenfeld, Y. Prolactin and autoimmunity: The hormone as an inflammatory cytokine. \u003cem\u003eBest Practice and Research: Clinical Endocrinology and Metabolism\u003c/em\u003e vol. 33 101324 (2019).\u003c/li\u003e\n\u003cli\u003eRuscitti, P. \u003cem\u003eet al.\u003c/em\u003e Adipocytokines in rheumatoid arthritis: The hidden link between inflammation and cardiometabolic comorbidities. \u003cem\u003eJournal of Immunology Research\u003c/em\u003e vol. 2018 (2018).\u003c/li\u003e\n\u003cli\u003eInoue, T. \u003cem\u003eet al.\u003c/em\u003e Oxytocin Suppresses Inflammatory Responses Induced by Lipopolysaccharide through Inhibition of the eIF-2\u0026alpha;\u0026ndash;ATF4 Pathway in Mouse Microglia. \u003cem\u003eCells\u003c/em\u003e (2019) doi:10.3390/cells8060527.\u003c/li\u003e\n\u003cli\u003eMartin, B. \u003cem\u003eet al.\u003c/em\u003e Relaxin reverses inflammatory and immune signals in aged hearts. \u003cem\u003ePLoS One\u003c/em\u003e (2018) doi:10.1371/journal.pone.0190935.\u003c/li\u003e\n\u003cli\u003eRamasamy, R., Yan, S. F. \u0026amp; Schmidt, A. M. Receptor for AGE (RAGE): Signaling mechanisms in the pathogenesis of diabetes and its complications. \u003cem\u003eAnn. N. Y. Acad. Sci.\u003c/em\u003e\u003cstrong\u003e1243\u003c/strong\u003e, 88\u0026ndash;102 (2011).\u003c/li\u003e\n\u003cli\u003eReyes, V. E. \u0026amp; Peniche, A. G. Helicobacter pylori deregulates T and B cell signaling to trigger immune evasion. in \u003cem\u003eCurrent Topics in Microbiology and Immunology\u003c/em\u003e vol. 421 229\u0026ndash;265 (Springer Verlag, 2019).\u003c/li\u003e\n\u003cli\u003eCoronavirus: What Happens To People\u0026rsquo;s Body If They Get Infected. https://www.webmd.com/lung/coronavirus-covid-19-affects-body#2.\u003c/li\u003e\n\u003cli\u003eNile, S. H. \u003cem\u003eet al.\u003c/em\u003e COVID-19: Pathogenesis, cytokine storm and therapeutic potential of interferons. \u003cem\u003eCytokine and Growth Factor Reviews\u003c/em\u003e vol. 53 66\u0026ndash;70 (2020).\u003c/li\u003e\n\u003cli\u003eWhat Are the Complications of Coronavirus (COVID-19)? https://www.webmd.com/lung/coronavirus-complications#1.\u003c/li\u003e\n\u003cli\u003eVaduganathan, M. \u003cem\u003eet al.\u003c/em\u003e Renin\u0026ndash;angiotensin\u0026ndash;aldosterone system inhibitors in patients with Covid-19. \u003cem\u003eN. Engl. J. Med.\u003c/em\u003e\u003cstrong\u003e382\u003c/strong\u003e, 1653\u0026ndash;1659 (2020).\u003c/li\u003e\n\u003cli\u003eSama, I. E. \u003cem\u003eet al.\u003c/em\u003e Circulating plasma concentrations of angiotensin-converting enzyme 2 in men and women with heart failure and effects of renin\u0026ndash;angiotensin\u0026ndash;aldosterone inhibitors. \u003cem\u003eEur. Heart J.\u003c/em\u003e\u003cstrong\u003e41\u003c/strong\u003e, 1810\u0026ndash;1817 (2020).\u003c/li\u003e\n\u003cli\u003eBloch, M. J. Renin-Angiotensin System Blockade in COVID-19: Good, Bad, or Indifferent?\u0026lowast;. \u003cem\u003eJ. Am. Coll. Cardiol.\u003c/em\u003e\u003cstrong\u003e76\u003c/strong\u003e, 277 (2020).\u003c/li\u003e\n\u003cli\u003eMascolo, A. \u003cem\u003eet al.\u003c/em\u003e Renin-angiotensin system and Coronavirus disease 2019: A narrative review. \u003cem\u003eFront. Cardiovasc. Med.\u003c/em\u003e\u003cstrong\u003e7\u003c/strong\u003e, (2020).\u003c/li\u003e\n\u003cli\u003eXu, X. \u003cem\u003eet al.\u003c/em\u003e Effective treatment of severe COVID-19 patients with tocilizumab. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e\u003cstrong\u003e117\u003c/strong\u003e, 10970\u0026ndash;10975 (2020).\u003c/li\u003e\n\u003cli\u003eSun, M. L., Yang, J. M., Sun, Y. P. \u0026amp; Su, G. H. [Inhibitors of RAS Might Be a Good Choice for the Therapy of COVID-19 Pneumonia]. \u003cem\u003eZhonghua Jie He He Hu Xi Za Zhi\u003c/em\u003e\u003cstrong\u003e43\u003c/strong\u003e, 219\u0026ndash;222 (2020).\u003c/li\u003e\n\u003cli\u003eGrimes, J. M. \u0026amp; Grimes, K. V. p38 MAPK inhibition: A promising therapeutic approach for COVID-19. \u003cem\u003eJ. Mol. Cell. Cardiol.\u003c/em\u003e\u003cstrong\u003e144\u003c/strong\u003e, 63\u0026ndash;65 (2020).\u003c/li\u003e\n\u003cli\u003eBulanova, D. \u003cem\u003eet al.\u003c/em\u003e Antiviral properties of chemical inhibitors of cellular anti-apoptotic Bcl-2 proteins. \u003cem\u003eViruses\u003c/em\u003e\u003cstrong\u003e9\u003c/strong\u003e, 271 (2017).\u003c/li\u003e\n\u003cli\u003eTian, B. \u003cem\u003eet al.\u003c/em\u003e Bcl-2 inhibitors reduce steroid-insensitive airway inflammation. \u003cem\u003eJ. Allergy Clin. Immunol.\u003c/em\u003e\u003cstrong\u003e140\u003c/strong\u003e, 418\u0026ndash;430 (2017).\u003c/li\u003e\n\u003cli\u003eRepurposing indomethacin for COVID-19 - Hospital Healthcare EuropeHospital Healthcare Europe. https://hospitalhealthcare.com/covid-19/repurposing-indomethacin-for-covid-19/.\u003c/li\u003e\n\u003cli\u003eLittle, P. Non-steroidal anti-inflammatory drugs and covid-19. \u003cem\u003eThe BMJ\u003c/em\u003e vol. 368 (2020).\u003c/li\u003e\n\u003cli\u003eReynolds, A. E. \u0026amp; Enquist, L. W. Biological interactions between herpesviruses and cyclooxygenase enzymes. \u003cem\u003eRev. Med. Virol.\u003c/em\u003e\u003cstrong\u003e16\u003c/strong\u003e, 393\u0026ndash;403 (2006).\u003c/li\u003e\n\u003cli\u003eRay, N., Bisher, M. E. \u0026amp; Enquist, L. W. Cyclooxygenase-1 and-2 are required for production of infectious pseudorabies virus. \u003cem\u003eJ. Virol.\u003c/em\u003e\u003cstrong\u003e78\u003c/strong\u003e, 12964\u0026ndash;12974 (2004).\u003c/li\u003e\n\u003cli\u003eSchr\u0026ouml;er, J. \u0026amp; Shenk, T. Inhibition of cyclooxygenase activity blocks cell-to-cell spread of human cytomegalovirus. \u003cem\u003eProc. Natl. Acad. Sci.\u003c/em\u003e\u003cstrong\u003e105\u003c/strong\u003e, 19468\u0026ndash;19473 (2008).\u003c/li\u003e\n\u003cli\u003eBahrami, H. \u003cem\u003eet al.\u003c/em\u003e Effects of indomethacin on viral replication markers in asymptomatic carriers of hepatitis B: a randomized, placebo-controlled trial. \u003cem\u003eAm. J. Gastroenterol.\u003c/em\u003e\u003cstrong\u003e100\u003c/strong\u003e, 856\u0026ndash;861 (2005).\u003c/li\u003e\n\u003cli\u003eChen, N., Warner, J. L. \u0026amp; Reiss, C. S. NSAID treatment suppresses VSV propagation in mouse CNS. \u003cem\u003eVirology\u003c/em\u003e\u003cstrong\u003e276\u003c/strong\u003e, 44\u0026ndash;51 (2000).\u003c/li\u003e\n\u003cli\u003eRossen, J. W. A., Bouma, J., Raatgeep, R. H. C., B\u0026uuml;ller, H. A. \u0026amp; Einerhand, A. W. C. Inhibition of cyclooxygenase activity reduces rotavirus infection at a postbinding step. \u003cem\u003eJ. Virol.\u003c/em\u003e\u003cstrong\u003e78\u003c/strong\u003e, 9721\u0026ndash;9730 (2004).\u003c/li\u003e\n\u003cli\u003eMelarange, R. \u003cem\u003eet al.\u003c/em\u003e Anti-inflammatory and gastrointestinal effects of nabumetone or its active metabolite, 6MNA (6-methoxy-2-naphthylacetic acid): comparison with indomethacin. \u003cem\u003eAgents Actions\u003c/em\u003e\u003cstrong\u003e36\u003c/strong\u003e, C82\u0026ndash;C83 (1992).\u003c/li\u003e\n\u003cli\u003eVan Der Heide, H. J. L., Rijnberg, W. J., Van Sorge, A., Van Kampen, A. \u0026amp; Schreurs, B. W. Similar effects of rofecoxib and indomethacin on the incidence of heterotopic ossification after hip arthroplasty. \u003cem\u003eActa Orthop.\u003c/em\u003e\u003cstrong\u003e78\u003c/strong\u003e, 90\u0026ndash;94 (2007).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supporting Information ","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Table S1 \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(PDF)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table S2 \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(PDF)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table S3 \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(PDF)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table S4 \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(PDF)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S1 \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(PDF)\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. A list of 20 NSAIDs approved by FDA \u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" width=\"586\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e\u003cstrong\u003eNo.\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003e\u003cstrong\u003eDrug name\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e\u003cstrong\u003ePubChem CID\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003e\u003cstrong\u003eMechanism of action\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eFlubiprofen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3394\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eNonselective COX inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eIbuprofen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3672\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eNonselective COX inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eIndomethacin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3715\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eNonselective COX inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eKetorolac\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3826\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eNonselective COX inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eMefenamic acid\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e4044\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eNonselective COX inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003ePiroxicam\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e54676228\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eNonselective COX inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eDiflunisal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3059\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eProstaglandin synthesis inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eFenoprofen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3342\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eProstaglandin synthesis inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eNaproxen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e156391\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eProstaglandin synthesis inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eSulindac\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1548887\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eProstaglandin synthesis inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eTolmetin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e5509\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eProstaglandin synthesis inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eKetoprofen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3825\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-1 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eOxaprozin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e4614\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-1 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eCelecoxib\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2662\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-2 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eRofecoxib\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e5090\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-2 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eValdecoxib\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e119607\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-2 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eDiclofenac\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3033\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-2 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eEtodolac\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3308\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-2 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003eMeloxicam\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e54677470\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-2 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e20*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"189\"\u003e\n\u003cp\u003e\u003cstrong\u003e6MNA\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e32176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003eSelective COX-2 inhibitor\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e* \u003c/strong\u003e\u003cstrong\u003e6MNA\u003c/strong\u003e\u003cstrong\u003e (Active form) of Nabumetone (Prodrug) \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. \u003c/strong\u003eTarget genes in 26 signaling pathways enrichment related to COVID-19.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"595\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003e\u003cstrong\u003eKEGG ID \u0026amp; Description \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003e\u003cstrong\u003eTarget genes\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eRichFactor\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u003cstrong\u003eFalse discovery rate\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04014: Ras signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,BAD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.013157895\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0071\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04921: Oxytocin signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003ePTGS2,PPP1CA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.013422819\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0294\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04010: MAPK signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,CASP3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.013651877\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0016\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04310: Wnt signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.013986014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0276\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04022: cGMP -PKG signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eENDRA,BAD,PPP1CA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.01875\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04064: NF-kappa B signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eCXCL8,PTGS2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.021505376\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0136\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04926: Relaxin signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.023076923\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0018\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04068: FoxO signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.023076923\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0018\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04071: Sphingolipid signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.025862069\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0014\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04910: Insulin signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,BAD,PPP1CA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.029850746\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00013\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04621: NOD-like receptor signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,CXCL8,CASP1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.030120482\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0000197\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04024: cAMP signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eENDRA,MAPK8,BAD,MAPK10,PPP1CA,PPARA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.030769231\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00000373\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04912: GnRH signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.034090909\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00072\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04722: Neurotrophin signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,BAD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.034482759\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00000853\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04012: ErbB signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,BAD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.036144578\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00062\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04620: Toll-like receptor signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,CXCL8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.039215686\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0000581\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa03320: PPAR signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003ePPARA,PPARG,FABP2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.041666667\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00044\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04920: Adipocytokine signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,PPARA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.043478261\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00041\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04917: Prolactin signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.043478261\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00041\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04664: Fc epsilon RI signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.044776119\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00039\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04668: TNF signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,CASP3,PTGS2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.046296296\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00000413\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04370: VEGF signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,BAD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.050847458\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00029\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04933: AGE-RAGE signaling pathway in diabetic complications\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,CXCL8,CASP1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.051020408\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.00000373\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04622: RIG-I-like receptor signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,CXCL8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.057142857\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0000197\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa04657: IL-17 signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,CXCL8,CASP3,PTGS2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.065217391\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.000000135\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"246\"\u003e\n\u003cp\u003ehsa05120: Epithelial cell signaling in Helicobacter pylori infection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"208\"\u003e\n\u003cp\u003eMAPK8,MAPK10,MAPK14,CXCL8,CASP3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e0.075757576\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.000000954\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e. Binding energy and interactions of potential three NSAIDs on MAPK8 (PDB ID:4YR8)\u003c/p\u003e\n\u003ctable border=\"1\" width=\"595\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\n\u003cp\u003e\u003cstrong\u003eHydrogen Bond Interactions\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e\u003cstrong\u003eHydrophobic Interactions \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\n\u003cp\u003e\u003cstrong\u003eProtein\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e\u003cstrong\u003eLigand\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003ePubChem ID\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e\u003cstrong\u003eSymbol\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\n\u003cp\u003e\u003cstrong\u003eBinding energy(kcal/mol)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\n\u003cp\u003e\u003cstrong\u003eAmino Acid Residue\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e\u003cstrong\u003eAmino Acid Residue\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\n\u003cp\u003e4YR8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e6MNA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e32176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eM1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\n\u003cp\u003e-7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\n\u003cp\u003eLys-218\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003ePro-221, Gly-199\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003ePro-254, Phe215\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eCys-216, Gln-253\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003ePro-210, Lys-218\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eGlu-217, Lys-225\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003eMefenamic acid\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e4044\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eM2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\n\u003cp\u003e-6.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\n\u003cp\u003eGlu-217\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eTrp-222, Val-211\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eArg-208, Cys-216\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eAsn-193, Lys-218\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003ePro-211\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003eEtodolac\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e3308\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003eM3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\n\u003cp\u003e-6.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\n\u003cp\u003en/a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eTyr-202, Lys-203\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eMet-200, Gly-201\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003ePro-221, Lys-218\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eLys-251, Ser-307\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"39\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"57\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"129\"\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eAla-306\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e. Binding energy and interactions of potential twelve NSAIDs on MAPK10 (PDB ID: 3TTJ)\u003c/p\u003e\n\u003ctable border=\"1\" width=\"569\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"35\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\n\u003cp\u003e\u003cstrong\u003eHydrogen Bond Interactions\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"101\"\u003e\n\u003cp\u003e\u003cstrong\u003eHydrophobic Interactions \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eProtein\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eLigand\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003ePubChem ID\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eSymbol\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eBinding energy(kcal/mol)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eAmino Acid Residue\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eAmino Acid Residue\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e3TTJ\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eMefenamic acid\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e32176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-6.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsp-207, Gln-75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLeu-206, Lys-93\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194, Asp-207\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eNaproxen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e4044\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-6.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194, Lys-93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-107, Asp-189\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eVal-225, Lys-191\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGln-75, Gly-73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eTolmetin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3308\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-6.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194, Asp-189\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLys-106, Leu-210\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAla-211, Arg-110\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-230, Lys-191\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-107, Thr-103\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eFenoprofen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3342\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-6.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLys-93, Lys-191\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSer-193, Ser-72\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eVal-78, Gly-73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGln-75, Ala-74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-107\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eKetorolac\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3826\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGlu-111, Arg-107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsp-207, Leu-206\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194, Lys-93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGln-75, Ser-193\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSer-72, Val-78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGly-73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eKetoprofen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3825\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-6.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLys-93, Asn-194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eVal-78, Leu-206\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSer-193\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-107, Gln-75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGly-73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eIbuprofen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3672\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-5.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLys-93, Ser-193\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLeu-206, Ala-74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGly-73, Gln-75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eVal-78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eFlubiprofen\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3394\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-6.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLys-191, Asp-189\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLys-93, Val-78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGly-73, Arg-107\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGln-75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eOxaprozin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e4614\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194, Arg-107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsp-189, Thr-103\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLys-191\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSer-217, Val-225\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-230\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSulindac\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e1548887\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-7.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-152\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-107, Asn-194\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLys-93, Ser-72\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGly-73, Ser-193\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAla-74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eDiclofenac\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3033\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-6.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSer-72, Gly-73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSer-193, Gln-75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-107, Lys-93\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLeu-206, Val-78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGly-71\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eRofecoxib\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e5090\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eR12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-7.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsn-194, Lys-191\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsp-189, Arg-230\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSer-217\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eThr-203, Leu-210\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGly-209, Ala-211\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-107\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e. Binding energy and interactions of potential two NSAIDs on BAD (PDB ID: 1G5J)\u003c/p\u003e\n\u003ctable border=\"1\" width=\"549\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"37\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"43\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"124\"\u003e\n\u003cp\u003e\u003cstrong\u003eHydrogen Bond Interactions\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"117\"\u003e\n\u003cp\u003e\u003cstrong\u003eHydrophobic Interactions \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eProtein\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eLigand\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003ePubChem ID\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eSymbol\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eBinding energy(kcal/mol)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eAmino Acid Residue\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u003cstrong\u003eAmino Acid Residue\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e1G5J\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e6MNA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e32176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eB1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-6.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eTrp-173, His-181\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-169, Tyr-124\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003ePhe-127, Tyr-177\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eThr-176\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eIndomethacin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e3715\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eB2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e-7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eAsp-180\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eArg-169, Tyr-124\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003ePhe-127, Val-131\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eGlu-128, His-181\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e \u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eThr-176, Trp-173\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Non-Steroidal Anti-Inflammatory Drugs, COVID-19, MAPK8-MAPK10-BAD, 6MNA-Rofecoxib-Indomethacin, RAS signaling pathway, Network pharmacology ","lastPublishedDoi":"10.21203/rs.3.rs-111615/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-111615/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) \u003cem\u003eshowed promising clinical efficacy toward COVID-19 patients as painkillers and anti-inflammatory agents. However, \u003c/em\u003ethe prospective anti-COVID-19 mechanisms of NSAIDs\u003cem\u003e are not evidently exposed. Therefore, we intended to decipher the most potent NSAIDs candidate(s) and its novel mechanism(s) against COVID-19 by network pharmacology.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMethod:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eFDA (U.S. Food \u0026amp; Drug Administration) approved twenty NSAIDs were used for this study.\u003cem\u003e Genes related to selected NSAIDs and COVID-19 related genes were identified by the \u003c/em\u003eSimilarity Ensemble Approach, Swiss Target Prediction, and PubChem databases\u003cem\u003e. Venn diagram identified overlapping genes between NSAIDs and COVID-19 related genes. The interactive networking between NSAIDs and overlapping genes was analyzed by STRING. \u003c/em\u003eRStudio plotted the bubble chart of KEGG pathway enrichment analysis of overlapping genes\u003cem\u003e. Finally, the binding affinity of NSAIDs against target genes was determined through molecular docking analysis.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eResults:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e Geneset enrichment analysis exhibited 26 signaling pathways against COVID-19. Inhibition of proinflammatory stimuli of tissues and/or cells by inactivating RAS signaling pathway was identified as the key anti-COVID-19 mechanism of NSAIDs. Besides, \u003c/em\u003eMAPK8, MAPK10, and BAD genes were explored as the associated genes of the RAS. Among twenty NSAIDs, 6MNA, rofecoxib, and indomethacin revealed promising binding affinity with the highest docking score against three identified genes, respectively.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Overall, our proposed three NSAIDs (6MNA, rofecoxib, and indomethacin) might block the RAS by inactivating its associated genes, thus may alleviate excessive inflammation induced by SARS-CoV-2. \u003c/p\u003e","manuscriptTitle":"SARS-CoV-2 intervened by NSAIDs: A network pharmacology approach to decipher signaling pathway and interactive genes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-11-30 23:27:19","doi":"10.21203/rs.3.rs-111615/v1","editorialEvents":[{"type":"communityComments","content":5},{"type":"decision","content":"Major revision","date":"2021-03-01T08:18:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-01-25T12:50:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4e2f10b2-f91e-4ceb-8e8a-2e33c4dbe6ff","date":"2021-01-23T20:41:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"b0bb0c22-fbe9-4aa1-ba99-d2d701a38bdf","date":"2021-01-08T15:26:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-12-14T10:59:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-11-25T16:47:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-11-25T16:34:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-11-25T16:31:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2020-11-19T08:11:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"178da546-a690-4724-9dcf-f1de736fc59b","owner":[],"postedDate":"November 30th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":1232605,"name":"Health Policy"},{"id":1232606,"name":"Clinical Pharmacology"}],"tags":[],"updatedAt":"2021-04-12T05:44:14+00:00","versionOfRecord":[],"versionCreatedAt":"2020-11-30 23:27:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-111615","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-111615","identity":"rs-111615","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}