| IL-2 | elevation of are | indicators of COVID-19 (count: 2) | |
|---|---|
| In conclusion, our study shows that the comprehensive decrease of lymphocytes, and the elevation of IL-2 and IL-6 are reliable indicators of severe COVID-19.
-- Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China. medrxiv. 2020-03-16. | |
| IL-10 acts as an anti-inflammatory cytokine deriving from alternatively activated macrophages, Th2 cells, Tregs, etc 16 In conclusion, our study shows that the comprehensive decrease of lymphocytes, and the elevation of IL-2 and IL-6 are reliable indicators of severe COVID-19.
-- Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China. medrxiv. 2020-03-16. | |
| IL-6 blockade | therapy for | treatment of COVID-19 (count: 1) | |
| The pathological role of IL-6 in SARS-CoV-2 infection indicated that IL-6 blockade may provide a feasible therapy for the treatment of COVID-19.
| |
| IL-8 | may | may potential targets for immunotherapy of COVID-19 (count: 1) | |
| In this study, IL-6, TNFα and IL-8 may be potential targets for immunotherapy of COVID-19.
| |
| research team | has used IL-6 receptor antibody in | 14 COVID-19 patients (count: 1) | |
| According to the news, a research team from First Affiliated Hospital of University of Science and Technology of China has used IL-6 receptor recombinant monoclonal antibody, Tozhu monoclonal antibody, in 14 critically or severely ill COVID-19 patients [10] .
| |
| SARS-CoV-2 | of protease is | M pro (count: 1) | |
| We now know that the non-structural protein 5 (Nsp5) is the main protease (M pro ) of SARS-CoV-2 and it is a cysteine protease, which also been called "3C-like protease" (3CL pro ).
-- AI-aided design of novel targeted covalent inhibitors against SARS-CoV-2. biorxiv. 2020-03-08. | |
| Cytokine storms | are regarded as | cause of death in COVID-19 patients (count: 1) | |
| Cytokine storms, which can quickly induce organ failure and threaten the life of the patients, are regarded as an important cause of death in COVID-19 patients.
-- reference not found! | |
| IL6 | were related to | disease severity of COVID-19 patients (count: 1) | |
| Further LASSO binary logistic regression analysis of 85 clinical related parameters indicated that age, IL6, ESR, ALB and D-D were closely related to disease severity of COVID-19 patients (Figure 1B).
-- reference not found! | |
| IL-6 | be biomarker in | COVID-19 patients (count: 1) | |
| Remarkably, sharply increased IL-6 level was observed in critically ill patients, which was almost 10-folds higher than that of severe patients, moreover, all of the death cases exhibited extremely high IL-6 value(Table S1), suggesting that IL-6 might be an important biomarker of poor prognosis in COVID-19 patients.
| |
| IL-6 COVID-19 therapy | has | has used (count: 1) | |
| Notably, the IL-6 monoclonal antibody-directed COVID-19 therapy has been used in clinical trial in China (No.
| |
| increase | is in | creatine kinase level of COVID-19 patients (count: 1) | |
| And in 138 hospitalized patient there was an increase tendency towards an increase in creatine kinase level of COVID-19 patients in ICU 15 .
-- Kidney impairment is associated with in-hospital death of COVID-19 patients. medrxiv. 2020-02-20. | |
| protease inhibitors | prevent | S-protein of 2019-nCoV (count: 1) | |
| 11 Therefore, one possible way to control the infection is to seek protease inhibitors to prevent the S-protein of 2019-nCoV cleaved into S1.
-- Machine intelligence design of 2019-nCoV drugs. biorxiv. 2020-02-04. | |
| 2019-nCoV protease homology structure | has | RMSD (count: 1) | |
| Particularly, the RMSD of two crystal structures at the binding site is 0.53 Å. When we try to carry a homology modeling of 2019-nCoV protease structure from its sequence using SARS-CoV 3CL protease (PDB ID: 2gx4) as a model, the resulting 2019-nCoV protease homology structure has an RMSD of 0.9 Å (or 0.2 Å at the binding site region) with its crystal structure 6lu7.
-- Machine intelligence design of 2019-nCoV drugs. biorxiv. 2020-02-04. | |
| our 2019-nCoV training set | is built up by | 115 SARS-CoV protease inhibitors (count: 1) | |
| Therefore, our 2019-nCoV training set is built up by 115 SARS-CoV protease inhibitors.
-- Machine intelligence design of 2019-nCoV drugs. biorxiv. 2020-02-04. | |
| hydrogen bonds | promise | binding to 2019-nCoV protease binding site (count: 1) | |
| These hydrogen bonds promise a strong binding to 2019-nCoV protease binding site.
-- Machine intelligence design of 2019-nCoV drugs. biorxiv. 2020-02-04. | |
| list | synthesizability of | 319 potential inhibitors of 2019-nCoV 3CL protease including two protease drugs (count: 1) | |
| SupplementaryMaterial-1.csv: A list of SMILES strings, predicted binding affinities, logP, logS and synthesizability of 319 potential inhibitors of 2019-nCoV 3CL protease, including two anti-HIV protease drugs.
-- Machine intelligence design of 2019-nCoV drugs. biorxiv. 2020-02-04. | |
| 2019-nCoV-S | depends on | protease TMPRSS2 (count: 1) | |
| recently showed that 2019-nCoV-S uses ACE2 for entry and depends on the cellular protease TMPRSS2 for priming [10] , showing that 2019-nCoV infections also require multiple factors.
| |
| IL-6-based inflammation | play role in | development of COVID-19 (count: 1) | |
| These data suggest that CD8 + T cell exhaustion and IL-6-based inflammation might play an important role in the development of COVID-19.
| |
| IL-6 | might bridge | SARS-CoV-2 infection (count: 1) | |
| 27 Thus, IL-6 might bridge SARS-CoV-2 infection and alveolar cell injury via inducing .
| |
| IL-6 | predicted | COVID-19 progression (count: 1) | |
| Multivariate Cox regression analysis indicated that circulating IL-6 and lactate independently predicted COVID-19 progression
| |
| Inflammatory monocytes | is with | high expression of IL-6 in severe pulmonary syndrome patients of 2019-nCoV (count: 1) | |
| Inflammatory monocytes with high expression of IL-6 in severe pulmonary syndrome patients of 2019-nCoV. (a) Representative density plots showing an analysis of CD14 and CD16 expressions in gated CD45 + monocytes (Gating strategy showing in Extended Data Figure 1a) isolated from peripheral blood in in healthy controls, ICU and non-ICU patients of 2019-nCoV. (b) Representative density plots showing an analysis of GM-CSF and IL-6 expressions in gated CD45 + CD14 + monocyte cells isolated from peripheral blood in healthy controls, in ICU and non-ICU patients of 2019-nCoV. (c) Statistics calculated by the percentage of CD14 + CD16 + subsets from monocytes.
| |
| modification | led to | loss of activity against protease of 2019-nCoV (count: 1) | |
| However, compared to 11r, the structural modification led to some loss of inhibitory activity against the main protease of 2019-nCoV (IC50 = 2.39 ± 0.63 uM) as well as the 3C proteases of enteroviruses.
| |
| medRxiv preprint IL-7 | is in | serum of COVID-19 patients (count: 1) | |
| https://doi.org/10.1101/2020.02.16.20023671 doi: medRxiv preprint IL-7, IL-10, and TNF-α, in the serum of COVID-19 patients [2] .
| |
| COVID-19 patients | concentrations of | IL6 (count: 1) | |
| Our results also demonstrate that severe COVID-19 patients have higher concentrations of IL6, IL10, IL2 and IFN-γ in the serum than mild cases, suggesting that the magnitude of1 6 cytokine storm is associated with the disease severity.
| |
| IL-2 | were | up-regulated in patients with COVID-19 (count: 1) | |
| IL-2, IL-6, and IL-10 were remarkably up-regulated in patients with severe COVID-19.
-- Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China. medrxiv. 2020-03-16. | |
| serum IL-6 | were | observed in COVID-19 patients 8 (count: 1) | |
| Increased serum IL-6, IP-10, MCP-1, MIP-1A, and TNFα were observed in COVID-19 patients 8 .
-- Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China. medrxiv. 2020-03-16. | |
| serum IL-2 | assess | severity of COVID-19 (count: 1) | |
| Thus, serum IL-2, IL-6, IL-10 could be used to assess the severity of COVID-19.
-- Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China. medrxiv. 2020-03-16. | |
| higher IL-2 level | is in | COVID-19 (count: 1) | |
| The higher IL-2 level in COVID-19
-- Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China. medrxiv. 2020-03-16. | |
| COVID-19 Cytokines | severity of are | biomarkers (count: 1) | |
| IL-10, and IL-6 reflect the severity of COVID-19 Cytokines are crucial biomarkers of the progression of various inflammatory disorders including pneumonia.
-- Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China. medrxiv. 2020-03-16. | |
| Cytokine levels | is in | COVID-19 patients (count: 1) | |
| Cytokine levels in COVID-19 patients. (
-- Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China. medrxiv. 2020-03-16. | |
| FBLN5 EFEMP2 LTBP4 CFTR G6PC3 PLG GRHL2 COL5A1 SERPINA1 COX4I2 MEFV MUSK RAPSN GBA HPS1 GLI2 CBS DOCK8 SARS2 FLG STIM1 CARD11 PGM3 TYK2 NFKB2 LRBA MARS ITGA3 SMAD4 MGP PTPN11 TGFBR1 DLEC1 DLC1 RASSF1 PPP2R1B KRAS MAP3K8 NSMCE3 TSC1 TSC2 FBN1 STRA6 RARB ZEB2 ACTA2 SPINK5 NF1 IRF1 PIK3CA SOS1 HGF RIT1 PPP1CB LEP GATA6 CDSN ARPC1B PLA2G7 FAM111B PEPD AKT1 SLC34A2 RTEL1 PARN SFTPA2 BMPR2 SMAD9 CAV1 KCNK3 EIF2AK4 IGFBP7 GDF1 CREBBP GPC3 RB1 MTOR DHCR7 ELN SFTPB SFTPC ABCA3 CSF2RA CSF2RB ENG ACVRL1 RSPO2 GATA4 NKX2 TBX1 ZFPM2 GTF2H5 SCARF2 | WAS | IL21R IL13 TERC CLEC7A IRAK3 PTGER2 ALOX5 ADRB2 MUC7 PTGDR NPSR1 HLA.G CCL11 HNMT SCGB3A2 TNF CHI3L1 IL4R MS4A2 COPA TGFB1 CAPN10 CHRNA3 CHRNA5 CASP8 CYP2A6 ERCC6 FASLG IRGM MC3R SLC11A1 CCL2 CD209 SP110 TLR2 DDX41 GLUD2 ATXN2 ADH1C MAPT TBP FCGR2A HMOX1 TERT MUC5B CPS1 IFNGR1 IFNG TIRAP CISH GSDMB GSDMA ZPBP2 HLA.DRB5 HLA.DQA1 RANBP6 IL33 SLC25A46 TSLP IL1RL2 IL1RL1 SMAD3 NOTCH4 PGAP3 MIEN1 IL18R1 HLA.DRB1 ORMDL3 HHIP HTR4 CLPTM1L CHRNB4 IRF4 MC1R SLC45A2 DEF8 RALY CHEK2 MUC5AC TOLLIP DSP TP63 ADAMTS7 MUC2 GSTCD CHRM3 AGER THSD4 HLA.DOA HSD17B8 RING1 COL11A2 RXRB HLA (count: 1) | |
| WDR19 DOK7 GGT1 WNT4 WNT3 PDE4D ARHGAP31 EGFR BRAF ERBB2 PRKN ADA NR0B1 JAG1 NOTCH2 ALMS1 FOXF1 TBX21 ITCH SDCCAG8 TTC8 AFF4 MMP1 CPN1 PLD1 MAP2K2 NKX2.1 TTF1 CCDC151 KRT18 KRT8 ALG9 ZIC3 HRAS FBLN5 EFEMP2 LTBP4 CFTR G6PC3 PLG GRHL2 COL5A1 SERPINA1 COX4I2 MEFV MUSK RAPSN GBA HPS1 GLI2 CBS DOCK8 SARS2 FLG STIM1 CARD11 PGM3 TYK2 NFKB2 LRBA MARS ITGA3 SMAD4 MGP PTPN11 TGFBR1 DLEC1 DLC1 RASSF1 PPP2R1B KRAS MAP3K8 NSMCE3 TSC1 TSC2 FBN1 STRA6 RARB ZEB2 ACTA2 SPINK5 NF1 IRF1 PIK3CA SOS1 HGF RIT1 PPP1CB LEP GATA6 CDSN ARPC1B PLA2G7 FAM111B PEPD AKT1 SLC34A2 RTEL1 PARN SFTPA2 BMPR2 SMAD9 CAV1 KCNK3 EIF2AK4 IGFBP7 GDF1 CREBBP GPC3 RB1 MTOR DHCR7 ELN SFTPB SFTPC ABCA3 CSF2RA CSF2RB ENG ACVRL1 RSPO2 GATA4 NKX2.5 TBX1 ZFPM2 GTF2H5 SCARF2 WAS IL21R IL13 TERC CLEC7A IRAK3 PTGER2 ALOX5 ADRB2 MUC7 PTGDR NPSR1 HLA.G CCL11 HNMT SCGB3A2 TNF CHI3L1 IL4R MS4A2 COPA TGFB1 CAPN10 CHRNA3 CHRNA5 CASP8 CYP2A6 ERCC6 FASLG IRGM MC3R SLC11A1 CCL2 CD209 SP110 TLR2 DDX41 GLUD2 ATXN2 ADH1C MAPT TBP FCGR2A HMOX1 TERT MUC5B CPS1 IFNGR1 IFNG TIRAP CISH GSDMB GSDMA ZPBP2 HLA.DRB5 HLA.DQA1 RANBP6 IL33 SLC25A46 TSLP IL1RL2 IL1RL1 SMAD3 NOTCH4 PGAP3 MIEN1 IL18R1 HLA.DRB1 ORMDL3 HHIP HTR4 CLPTM1L CHRNB4 IRF4 MC1R SLC45A2 DEF8 RALY CHEK2 MUC5AC TOLLIP DSP TP63 ADAMTS7 MUC2 GSTCD NPNT CHRM3 AGER THSD4 HLA.DOA HSD17B8 RING1 COL11A2 RXRB HLA.
-- reference not found! | |
| we | employed ammonium chloride For | insights into 2019-nCoV-S protease choice (count: 1) | |
| For initial insights into 2019-nCoV-S protease choice, 101 we employed ammonium chloride, which elevates endosomal pH and thereby blocks CatB/L 102 activity.
| |
| IRF27 | is | candidate marker gene for SARS-CoV-2 infection (count: 1) | |
| These results suggest that IRF27 is a candidate marker gene for SARS-CoV-2 infection.
| |
| SARS-CoV-2 | is in | context of type I IFN 10 (count: 1) | |
| Examining transcriptional factor activation 9 and interferon stimulated gene (ISG) induction, SARS-CoV-2 in the context of type I IFN 10 induces phosphorylation of STAT1 and increased ISG proteins.
-- reference not found! | |
| SARS-CoV-2 | modulates | type I IFN response (count: 1) | |
| as well as further research into how SARS-CoV-2 modulates the type I IFN response early 23 during infection.
-- reference not found! | |
| We | evaluated | susceptibility of SARS-CoV-2 to IFN-I pretreatment (count: 1) | |
| We next evaluated the susceptibility of SARS-CoV-2 to IFN-I pretreatment.
-- reference not found! | |
| we | examined protein production in | 96 nucleocapsid protein production in IFN-I cells following SARS-CoV-2 infection (count: 1) | |
| Finally, we examined viral protein production finding a major deficit in 96 nucleocapsid protein production in IFN-I treated cells following SARS-CoV-2 infection (Fig.
-- reference not found! | |
| primed 99 IFN-I response | is in | SARS-CoV-2 (count: 1) | |
| Together, the results demonstrate a clear sensitivity to a primed 99 IFN-I response in SARS-CoV-2, which is not observed with SARS-CoV. 100 SARS-CoV-2 fails to attenuate STAT1 phosphorylation and ISG production.
-- reference not found! | |
| IFN-I cells | infected with | SARS-CoV-2 (count: 1) | |
| Examining Vero cell protein lysates, we found that IFN-I treated cells infected with 104 SARS-CoV-2 induced phosphorylated STAT-1 by 48 hours post infection (Fig.
-- reference not found! | |
| IFN-I treatment | results in | protein levels for 113 ISGs following SARS-CoV-2 infection (count: 1) | |
| However, IFN-I treatment results in augmented protein levels for 113 both ISGs following SARS-CoV-2 infection as compared to untreated control.
-- reference not found! | |
| differences | be | 147 drivers of SARS-CoV-2 type I IFN susceptibility (count: 1) | |
| Together, the 146 sequence homology analysis suggests that differences in NSP3, ORF3b, and/or ORF6 may be 147 key drivers of SARS-CoV-2 type I IFN susceptibility.
-- reference not found! | |
| differences | is in | 151 IFN-I sensitivity between SARS-CoV-2 (count: 1) | |
| In this report, we describe differences in 151 the IFN-I sensitivity between SARS-CoV-2 and the original SARS-CoV. While both viruses 152 maintain similar replication in untreated Vero E6 cells, SARS-CoV-2 has a significant decrease 153 in viral protein and replication following IFN-I pretreatment.
-- reference not found! | |
| SARS-CoV-2 | has | changes known as IFN-I antagonists (count: 1) | |
| Analysis of viral proteins finds SARS-CoV-2 has several changes that potentially impact its 158 capacity to modulate the type I IFN response, including loss of ORF3b and a short truncation of 159 ORF6, both known as IFN-I antagonists for SARS-CoV 30 .
-- reference not found! | |
| SARS-CoV-2 | sensitivity to | type I IFN 230 (count: 1) | |
| Overall, our results indicate that SARS-CoV-2 has a much higher sensitivity to type I IFN 230 than the previously emergent SARS-CoV. This augmented type I IFN sensitivity is likely due to 231 changes in viral proteins between the two epidemic CoV strains.
-- reference not found! | |
| SARS-CoV-2 | shows | 93 reduction following IFN-I treatment (count: 1) | |
| In contrast, SARS-CoV-2 shows a significant 93 reduction in viral replication following IFN-I treatment.
-- reference not found! | |
| STAT1 phosphorylation | is | following IFN-I pretreatment induced following SARS-CoV-2 infection (count: 1) | |
| In these studies, we have found that following IFN-I pretreatment, STAT1 191 phosphorylation is induced following SARS-CoV-2 infection.
-- reference not found! | |
| Cytokines | is in | COVID-19 patients (count: 1) | |
| Cytokines and relative T cell numbers in COVID-19 patients.
-- Reduction and Functional Exhaustion of T Cells in Patients with Coronavirus Disease 2019 (COVID-19). medrxiv. 2020-02-20. | |
| TNF-α | is in | SARS-CoV-2 infected HD patients (count: 1) | |
| In addition, the serum level of serial cytokines of IL-4, IL-6, TNF-α in SARS-CoV-2 infected HD patients remain relatively lower in comparison with non-HD patients with SARS-CoV-2 infection.
| |
| IL-4 | γ in | non HD patients with SARS-CoV-2 infection (count: 1) | |
| The proportion of these cells in HD patients with SARS-CoV-2 infection was decreased much more.(Figure 4)In addition, we observed that the serum levels of IL-4, IL-6, IL-10, TNF -α, inf -γ in non HD patients with SARS-CoV-2 infection were significantly higher than the normal level, while the serum levels of these cytokines in HD patients with SARS-CoV-2 infection or not are comparable in significantly lower than those in non HD patients with SARS-CoV-2 infection.(Figure 5) These results show that the immune system of HD patients is compromised, which may be worsened furthermore upon SARS-CoV-2 infection, and unable trigger effective immune response and cytokine release.
| |
| COVID-19 patients | is in | ChongqingIFN-γ ≥ 7.42 (count: 1) | |
| Laboratory and radiographic and findings of COVID-19 patients in ChongqingIFN-γ≥7.42 ng/ml -No./total No. (%)
| |
| SARS 3CL protease inhibitor | is | 2019-nCoV 3CL protease inhibitor (count: 1) | |
| We, therefore, hypothesize that a potent SARS 3CL protease inhibitor is also a potent 2019-nCoV 3CL protease inhibitor.
-- Potentially highly potent drugs for 2019-nCoV. biorxiv. 2020-02-13. | |
| FDA | approved drugs for | 2019-nCoV 3CL protease inhibition (count: 1) | |
| In responding to the pressing need for anti-2019-nCoV medications, we develop mathematics-based deep learning models to systematically eventuate FDA approved drugs in the DrugBank for 2019-nCoV 3CL protease inhibition.
-- Potentially highly potent drugs for 2019-nCoV. biorxiv. 2020-02-13. | |
| 2019-nCoV protease structure | can | can built (count: 1) | |
| Since the sequences are highly identical, the 2019-nCoV protease structure can be built by homology modeling with the SARS-CoV 3CL protease (PDB ID: 2A5I) [13] as a template.
-- Potentially highly potent drugs for 2019-nCoV. biorxiv. 2020-02-13. | |
| We | build | 3D 2019-nCoV 3CL protease structure (count: 1) | |
| We first build a 3D 2019-nCoV 3CL protease structure by using homology modeling.
-- Potentially highly potent drugs for 2019-nCoV. biorxiv. 2020-02-13. | |
| set | are docked to | 3D 2019-nCoV 3CL protease structure (count: 1) | |
| A set of SARS-CoV protease inhibitors are docked to the 3D 2019-nCoV 3CL protease structure using our MathPose.
-- Potentially highly potent drugs for 2019-nCoV. biorxiv. 2020-02-13. | |
| We | build | 2019-nCoV 3CL protease structure (count: 1) | |
| We build a three-dimensional (3D) 2019-nCoV 3CL protease structure using a SARS-CoV 3CL protease crystal structure as a template and collect a set of 84 SARS-CoV inhibition experimental data.
-- Potentially highly potent drugs for 2019-nCoV. biorxiv. 2020-02-13. | |
| molecules | are docked to | 3D 2019-nCoV 3CL protease structure (count: 1) | |
| The molecules of this set are docked to the 3D 2019-nCoV 3CL protease structure to form a machine learning training set.
-- Potentially highly potent drugs for 2019-nCoV. biorxiv. 2020-02-13. | |
| task | involves | 1465 2019-nCoV protease complexes (count: 1) | |
| The first task involves 1465 2019-nCoV protease complexes as the test set and 84 SARS-CoV protease inhibitors as the training set.
-- Potentially highly potent drugs for 2019-nCoV. biorxiv. 2020-02-13. | |
| understanding | validate | use of protease inhibitors against SARS-CoV-2 (count: 1) | |
| Altogether, the results presented in this work contribute to gain a deep understanding of the molecular pharmacology of SARS-CoV-2 treatment and validate the use of protease inhibitors against SARS-CoV-2.
-- reference not found! | |
| protease inhibitors | interact with | site of SARS-CoV-2 protease (count: 1) | |
| In silico data demonstrated that the different protease inhibitors, used against HIV-1, could interact with the active site of SARS-CoV-2 protease producing an interaction with a binding energy lower than -6.9 Kcal/mol.
-- reference not found! | |
| protease inhibitors | is in | patients infected with SARS-CoV-2 (count: 1) | |
| Additionally, the data obtained from prior outbreaks, the clinical results obtained by using protease inhibitors in patients infected with SARS-CoV-2, and the results shown here, support the use of protease inhibitors to treat SARS-CoV-2.
-- reference not found! | |
| compounds | showed | binding energy values to SARS-CoV-2 protease than to those (count: 1) | |
| Some compounds showed comparable binding energy values to the SARS-CoV-2 protease than to those observed for SQV, LPV and RTV.
-- reference not found! | |
| percent homology | is with | SARS-CoV-2 protease protein (count: 1) | |
| The percent homology with SARS-CoV-2 protease protein is shown for some proteins.
-- reference not found! | |
| serine protease TMPRSS2 | contributed to | S-protein priming of 2019-nCoV (count: 1) | |
| The cellular serine protease TMPRSS2 also contributed to the S-protein priming of 2019-nCoV, indicating that the TMPRSS2 inhibitor might constitute a treatment option 36 .
-- Transmission routes of 2019-nCoV and controls in dental practice. International Journal of Oral Science. 2020. | |
| docking study | modeling of | 3CL protease in SARS-CoV-2 virus (count: 1) | |
| Reviewer Expertise: Medicinal Chemistry, Drug Discovery, Chemical Biology Yu Wai Chen and co-workers presented a molecular modeling and docking study of the 3CL protease in the SARS-CoV-2 virus.
-- reference not found! | |
| SARS-CoV-2 infection | be blocked by | protease inhibitor (count: 1) | |
| Hoffmann and coworkers show that SARS-CoV-2 infection depends on the host cell factors ACE2 and TMPRSS2 and can be blocked by a clinically proven protease inhibitor.
| |
| We | investigated | protease dependence of SARS-CoV-2 entry (count: 1) | |
| The Cellular Serine Protease TMPRSS2 Primes SARS-2-S for Entry, and a Serine Protease Inhibitor Blocks SARS-CoV-2 Infection of Lung Cells We next investigated protease dependence of SARS-CoV-2 entry.
| |
| SARS-CoV-2 S proteins | forming | furin protease cleavage site (count: 1) | |
| SARS-CoV-2 S proteins have also acquired several basic residues (RRAR/S), forming a furin protease cleavage site.
-- SARS Coronavirus Redux. Trends in Immunology. 2020-03-12. | |
| SARS-CoV-2-S | depends on | protease TMPRSS2 (count: 1) | |
| recently showed that SARS-CoV-2-S uses ACE2 for entry and depends on the cellular protease TMPRSS2 for priming [5] , showing that SARS-CoV-2 infections also require multiple factors.
-- reference not found! | |
| IL-22 | seen in | SARS-CoV-2 2 (count: 1) | |
| In addition to antimicrobial peptides, IL-22 upregulates mucins, fibrinogen, anti-apoptotic proteins, serum amyloid A, and LPS binding protein 3 ; therefore, IL-22 may contribute to the formation of life-threatening edema enriched with mucins and fibrin, seen in SARS-CoV-2 2 and SARS-CoV patients 4 .
-- TH17 Responses in Cytokine Storm of COVID-19: An Emerging Target of JAK2 Inhibitor Fedratinib. Journal of Microbiology, Immunology and Infection. 2020-03-11. | |
| studies | have reported | levels of creatinine kinase in association with COVID-19 severity (count: 1) | |
| Several studies have reported elevated levels of creatinine kinase and lactate dehydrogenase or myoglobin in association with COVID-19 severity (table).
-- reference not found! | |
| baricitinib | produce | dampening of host response due to CRS including IL-6 responsible for forms during COVID-19 (count: 1) | |
| Moreover, as a selective inhibitor of JAK 1 and 2, baricitinib is also able to produce an important dampening of host inflammatory response due to CRS (including IL-6 and interferon gamma) responsible for the more severe forms of interstitial pneumonia during COVID-19 [107, 108] .
-- reference not found! | |
| reports | confirmed | elevation of IL-6 in patients with COVID-19 (count: 1) | |
| Several other reports also confirmed the elevation of IL-6 in critically ill patients with COVID-19 [6] [7] [8] .
-- reference not found! | |
| COVID-19 patients | have | level of IL 10 (count: 1) | |
| Interestingly, COVID-19 patients sometimes have a significantly elevated level of IL- 10 [2] .
-- reference not found! | |