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LitCovid-PubTator

LitCovid-PMC-OGER-BB

{"project":"LitCovid-PMC-OGER-BB","denotations":[{"id":"T567","span":{"begin":19,"end":23},"obj":"CHEBI:23888;CHEBI:23888"},{"id":"T568","span":{"begin":53,"end":61},"obj":"SP_7"},{"id":"T569","span":{"begin":209,"end":217},"obj":"SP_7"},{"id":"T570","span":{"begin":328,"end":336},"obj":"SP_7"},{"id":"T578","span":{"begin":700,"end":708},"obj":"SP_7"},{"id":"T579","span":{"begin":744,"end":748},"obj":"CHEBI:23888;CHEBI:23888"},{"id":"T580","span":{"begin":871,"end":875},"obj":"CHEBI:23888;CHEBI:23888"},{"id":"T581","span":{"begin":1331,"end":1340},"obj":"SP_7"},{"id":"T582","span":{"begin":2224,"end":2232},"obj":"SP_7"},{"id":"T583","span":{"begin":2384,"end":2388},"obj":"CHEBI:23888;CHEBI:23888"},{"id":"T584","span":{"begin":2405,"end":2410},"obj":"PR:000005188"},{"id":"T585","span":{"begin":2412,"end":2416},"obj":"PR:000009030"},{"id":"T586","span":{"begin":2418,"end":2422},"obj":"PR:000000017"},{"id":"T587","span":{"begin":2424,"end":2428},"obj":"PR:000001471"},{"id":"T588","span":{"begin":2435,"end":2441},"obj":"PR:000001548"},{"id":"T589","span":{"begin":2443,"end":2447},"obj":"PR:000001944"},{"id":"T590","span":{"begin":2449,"end":2452},"obj":"PR:000000134"},{"id":"T591","span":{"begin":2462,"end":2466},"obj":"CHEBI:23888;CHEBI:23888"},{"id":"T592","span":{"begin":2489,"end":2497},"obj":"SP_7"},{"id":"T593","span":{"begin":2610,"end":2628},"obj":"UBERON:0000160"},{"id":"T594","span":{"begin":2638,"end":2656},"obj":"GO:0007259"},{"id":"T596","span":{"begin":2704,"end":2712},"obj":"SP_7"}],"text":"3.8 Validation of drug positioning for QFPD against COVID-19 via the robustness of disease network\nFirstly, the robustness of whole networks against formula attack was assessed to evaluate QFPD attack on the COVID-19 disease network. Interestingly, Table 4 and Fig. 11 showed that MSXG, SGMH, XCH, WLS and Others attack on the COVID-19 network were characterized by greater disturbance score than negative control (BXTM), and increasing dependence on hub nodes, indicating greater fragility under formula attack. In addition, SGMH, MSXG, and Others exerted higher disturbance score than the positive control (YDBF) Table 5 .\nFig. 11 Evaluation of the effect of QFPD on the robustness disturbance of COVID-19 network. Blue normal distribution: drug attack on random networks as a null distribution for the permutation test. Red vertical line: the disturbance rate of the drug to the real disease network. Fist row: MXSG, second row: SGMH, third row: XCH, fourth row: WLS, fifth row: Others. Fist column: average connectivity, second row: average length of shortest path, third row: connection centrality, fourth row: closeness centrality. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nTable 5 Docking score between common ingredients of QFPD and 2019-nCov proteins.\nMolecule MS1 MX16 MX17 MX8 MXO1 SO1 SX1 WO1 XO1\nMain Protease −7.6 −7 −7.8 −7.8 −7.8 −7.2 −7.1 −7.4 −7.4\nPapain-like protease −8 −8.2 −8.1 −8.1 −8.2 −8.2 −9.2 −8.7 −8.3\nRdRp with RNA −8.6 −8 −7.9 −7.9 −8 −8.4 −8.2 −8.8 −9.5\nRdRp without RNA −7.1 −6.8 −6.8 −6.8 −7 −7.1 −6.9 −7.5 −7.1\nHelicase ADP site −6.2 −6.5 −6.3 −6.1 −6.2 −6.4 −6.8 −6.2 −6.8\nHelicase NCB site −7.4 −7.1 −7.2 −7.2 −7.5 −7.5 −7.4 −7.6 −7.5\nNsp14(ExoN) −7.2 −6.6 −6.6 −6.7 −6.9 −7 −6.9 −7.1 −7.1\nNsp14(N7-MTase) −8.6 −8.3 −8.4 −8.3 −8.6 −8.3 −9.4 −8.7 −8.7\nNsp15(endoribonuclease) −6.2 −6.8 −6.4 −6.4 −6.3 −6.5 −6.8 −6.4 −6.6\nNsp16(2′-O-MTase) −8.1 −7.4 −7.6 −7.8 −7.8 −8.3 −7.7 −8.4 −8.2\nN protein NCB site −8.1 −7.9 −8 −8 −7.6 −7.8 −7.5 −7.7 −7.9\nE protein(ion channel) −6.4 −6.9 −7.2 −7.2 −6.9 −6.9 −7.9 −6.8 −6.8\nM: MXSG, S: SGMH, X: XCH, O: Others.\nNext, to illustrate the mechanism of QFPD against COVID-19, a formula-attacked target-KEGG pathway network was constructed (Fig. 12 ). This network showed that MSXG, SGMH, XCH, WLS and Others interacted with 8 drug-attacked nodes (Cdc20, Ido1, Ifng, Il10, Il6, Ptger4, Spi1, Tnf), and 24 drug-attacked nodes in the COVID-19 network were related to Graft-versus-host disease, cytokine-cytokine receptor interaction, asthma, influenza A, inflammatory bowel disease, JAK-STAT signaling, etc.\nFig. 12 Disturbance analysis of QFPD for COVID-19 network. A: Venn diagram of the five formulae’ attacked targets. B: Formula-attacked target-KEGG pathway network; green square: formula, yellow diamond: attacked target, red circle: KEGG pathways. The bigger the size of the nodes is, the higher the degree is. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)"}

LitCovid-PD-FMA-UBERON

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T147","span":{"begin":1341,"end":1349},"obj":"Body_part"},{"id":"T148","span":{"begin":1530,"end":1533},"obj":"Body_part"},{"id":"T149","span":{"begin":1588,"end":1591},"obj":"Body_part"},{"id":"T150","span":{"begin":1767,"end":1771},"obj":"Body_part"},{"id":"T151","span":{"begin":2011,"end":2018},"obj":"Body_part"},{"id":"T152","span":{"begin":2071,"end":2078},"obj":"Body_part"},{"id":"T153","span":{"begin":2549,"end":2557},"obj":"Body_part"},{"id":"T154","span":{"begin":2558,"end":2566},"obj":"Body_part"},{"id":"T155","span":{"begin":2623,"end":2628},"obj":"Body_part"}],"attributes":[{"id":"A147","pred":"fma_id","subj":"T147","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A148","pred":"fma_id","subj":"T148","obj":"http://purl.org/sig/ont/fma/fma67095"},{"id":"A149","pred":"fma_id","subj":"T149","obj":"http://purl.org/sig/ont/fma/fma67095"},{"id":"A150","pred":"fma_id","subj":"T150","obj":"http://purl.org/sig/ont/fma/fma84120"},{"id":"A151","pred":"fma_id","subj":"T151","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A152","pred":"fma_id","subj":"T152","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A153","pred":"fma_id","subj":"T153","obj":"http://purl.org/sig/ont/fma/fma84050"},{"id":"A154","pred":"fma_id","subj":"T154","obj":"http://purl.org/sig/ont/fma/fma84050"},{"id":"A155","pred":"fma_id","subj":"T155","obj":"http://purl.org/sig/ont/fma/fma7199"}],"text":"3.8 Validation of drug positioning for QFPD against COVID-19 via the robustness of disease network\nFirstly, the robustness of whole networks against formula attack was assessed to evaluate QFPD attack on the COVID-19 disease network. Interestingly, Table 4 and Fig. 11 showed that MSXG, SGMH, XCH, WLS and Others attack on the COVID-19 network were characterized by greater disturbance score than negative control (BXTM), and increasing dependence on hub nodes, indicating greater fragility under formula attack. In addition, SGMH, MSXG, and Others exerted higher disturbance score than the positive control (YDBF) Table 5 .\nFig. 11 Evaluation of the effect of QFPD on the robustness disturbance of COVID-19 network. Blue normal distribution: drug attack on random networks as a null distribution for the permutation test. Red vertical line: the disturbance rate of the drug to the real disease network. Fist row: MXSG, second row: SGMH, third row: XCH, fourth row: WLS, fifth row: Others. Fist column: average connectivity, second row: average length of shortest path, third row: connection centrality, fourth row: closeness centrality. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nTable 5 Docking score between common ingredients of QFPD and 2019-nCov proteins.\nMolecule MS1 MX16 MX17 MX8 MXO1 SO1 SX1 WO1 XO1\nMain Protease −7.6 −7 −7.8 −7.8 −7.8 −7.2 −7.1 −7.4 −7.4\nPapain-like protease −8 −8.2 −8.1 −8.1 −8.2 −8.2 −9.2 −8.7 −8.3\nRdRp with RNA −8.6 −8 −7.9 −7.9 −8 −8.4 −8.2 −8.8 −9.5\nRdRp without RNA −7.1 −6.8 −6.8 −6.8 −7 −7.1 −6.9 −7.5 −7.1\nHelicase ADP site −6.2 −6.5 −6.3 −6.1 −6.2 −6.4 −6.8 −6.2 −6.8\nHelicase NCB site −7.4 −7.1 −7.2 −7.2 −7.5 −7.5 −7.4 −7.6 −7.5\nNsp14(ExoN) −7.2 −6.6 −6.6 −6.7 −6.9 −7 −6.9 −7.1 −7.1\nNsp14(N7-MTase) −8.6 −8.3 −8.4 −8.3 −8.6 −8.3 −9.4 −8.7 −8.7\nNsp15(endoribonuclease) −6.2 −6.8 −6.4 −6.4 −6.3 −6.5 −6.8 −6.4 −6.6\nNsp16(2′-O-MTase) −8.1 −7.4 −7.6 −7.8 −7.8 −8.3 −7.7 −8.4 −8.2\nN protein NCB site −8.1 −7.9 −8 −8 −7.6 −7.8 −7.5 −7.7 −7.9\nE protein(ion channel) −6.4 −6.9 −7.2 −7.2 −6.9 −6.9 −7.9 −6.8 −6.8\nM: MXSG, S: SGMH, X: XCH, O: Others.\nNext, to illustrate the mechanism of QFPD against COVID-19, a formula-attacked target-KEGG pathway network was constructed (Fig. 12 ). This network showed that MSXG, SGMH, XCH, WLS and Others interacted with 8 drug-attacked nodes (Cdc20, Ido1, Ifng, Il10, Il6, Ptger4, Spi1, Tnf), and 24 drug-attacked nodes in the COVID-19 network were related to Graft-versus-host disease, cytokine-cytokine receptor interaction, asthma, influenza A, inflammatory bowel disease, JAK-STAT signaling, etc.\nFig. 12 Disturbance analysis of QFPD for COVID-19 network. A: Venn diagram of the five formulae’ attacked targets. B: Formula-attacked target-KEGG pathway network; green square: formula, yellow diamond: attacked target, red circle: KEGG pathways. The bigger the size of the nodes is, the higher the degree is. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)"}

LitCovid-PD-MONDO

LitCovid-PD-CLO

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T325","span":{"begin":267,"end":269},"obj":"http://purl.obolibrary.org/obo/CLO_0053733"},{"id":"T326","span":{"begin":631,"end":633},"obj":"http://purl.obolibrary.org/obo/CLO_0053733"},{"id":"T327","span":{"begin":778,"end":779},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T328","span":{"begin":818,"end":822},"obj":"http://purl.obolibrary.org/obo/UBERON_0000473"},{"id":"T329","span":{"begin":1360,"end":1363},"obj":"http://purl.obolibrary.org/obo/CLO_0007875"},{"id":"T330","span":{"begin":1360,"end":1363},"obj":"http://purl.obolibrary.org/obo/CLO_0052410"},{"id":"T331","span":{"begin":2234,"end":2235},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T332","span":{"begin":2607,"end":2608},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T333","span":{"begin":2647,"end":2656},"obj":"http://purl.obolibrary.org/obo/SO_0000418"},{"id":"T334","span":{"begin":2722,"end":2723},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T335","span":{"begin":2778,"end":2779},"obj":"http://purl.obolibrary.org/obo/CLO_0001021"}],"text":"3.8 Validation of drug positioning for QFPD against COVID-19 via the robustness of disease network\nFirstly, the robustness of whole networks against formula attack was assessed to evaluate QFPD attack on the COVID-19 disease network. Interestingly, Table 4 and Fig. 11 showed that MSXG, SGMH, XCH, WLS and Others attack on the COVID-19 network were characterized by greater disturbance score than negative control (BXTM), and increasing dependence on hub nodes, indicating greater fragility under formula attack. In addition, SGMH, MSXG, and Others exerted higher disturbance score than the positive control (YDBF) Table 5 .\nFig. 11 Evaluation of the effect of QFPD on the robustness disturbance of COVID-19 network. Blue normal distribution: drug attack on random networks as a null distribution for the permutation test. Red vertical line: the disturbance rate of the drug to the real disease network. Fist row: MXSG, second row: SGMH, third row: XCH, fourth row: WLS, fifth row: Others. Fist column: average connectivity, second row: average length of shortest path, third row: connection centrality, fourth row: closeness centrality. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nTable 5 Docking score between common ingredients of QFPD and 2019-nCov proteins.\nMolecule MS1 MX16 MX17 MX8 MXO1 SO1 SX1 WO1 XO1\nMain Protease −7.6 −7 −7.8 −7.8 −7.8 −7.2 −7.1 −7.4 −7.4\nPapain-like protease −8 −8.2 −8.1 −8.1 −8.2 −8.2 −9.2 −8.7 −8.3\nRdRp with RNA −8.6 −8 −7.9 −7.9 −8 −8.4 −8.2 −8.8 −9.5\nRdRp without RNA −7.1 −6.8 −6.8 −6.8 −7 −7.1 −6.9 −7.5 −7.1\nHelicase ADP site −6.2 −6.5 −6.3 −6.1 −6.2 −6.4 −6.8 −6.2 −6.8\nHelicase NCB site −7.4 −7.1 −7.2 −7.2 −7.5 −7.5 −7.4 −7.6 −7.5\nNsp14(ExoN) −7.2 −6.6 −6.6 −6.7 −6.9 −7 −6.9 −7.1 −7.1\nNsp14(N7-MTase) −8.6 −8.3 −8.4 −8.3 −8.6 −8.3 −9.4 −8.7 −8.7\nNsp15(endoribonuclease) −6.2 −6.8 −6.4 −6.4 −6.3 −6.5 −6.8 −6.4 −6.6\nNsp16(2′-O-MTase) −8.1 −7.4 −7.6 −7.8 −7.8 −8.3 −7.7 −8.4 −8.2\nN protein NCB site −8.1 −7.9 −8 −8 −7.6 −7.8 −7.5 −7.7 −7.9\nE protein(ion channel) −6.4 −6.9 −7.2 −7.2 −6.9 −6.9 −7.9 −6.8 −6.8\nM: MXSG, S: SGMH, X: XCH, O: Others.\nNext, to illustrate the mechanism of QFPD against COVID-19, a formula-attacked target-KEGG pathway network was constructed (Fig. 12 ). This network showed that MSXG, SGMH, XCH, WLS and Others interacted with 8 drug-attacked nodes (Cdc20, Ido1, Ifng, Il10, Il6, Ptger4, Spi1, Tnf), and 24 drug-attacked nodes in the COVID-19 network were related to Graft-versus-host disease, cytokine-cytokine receptor interaction, asthma, influenza A, inflammatory bowel disease, JAK-STAT signaling, etc.\nFig. 12 Disturbance analysis of QFPD for COVID-19 network. A: Venn diagram of the five formulae’ attacked targets. B: Formula-attacked target-KEGG pathway network; green square: formula, yellow diamond: attacked target, red circle: KEGG pathways. The bigger the size of the nodes is, the higher the degree is. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)"}

LitCovid-PD-CHEBI

LitCovid-PD-HP

{"project":"LitCovid-PD-HP","denotations":[{"id":"T20","span":{"begin":2589,"end":2595},"obj":"Phenotype"},{"id":"T21","span":{"begin":2610,"end":2636},"obj":"Phenotype"}],"attributes":[{"id":"A20","pred":"hp_id","subj":"T20","obj":"http://purl.obolibrary.org/obo/HP_0002099"},{"id":"A21","pred":"hp_id","subj":"T21","obj":"http://purl.obolibrary.org/obo/HP_0002037"}],"text":"3.8 Validation of drug positioning for QFPD against COVID-19 via the robustness of disease network\nFirstly, the robustness of whole networks against formula attack was assessed to evaluate QFPD attack on the COVID-19 disease network. Interestingly, Table 4 and Fig. 11 showed that MSXG, SGMH, XCH, WLS and Others attack on the COVID-19 network were characterized by greater disturbance score than negative control (BXTM), and increasing dependence on hub nodes, indicating greater fragility under formula attack. In addition, SGMH, MSXG, and Others exerted higher disturbance score than the positive control (YDBF) Table 5 .\nFig. 11 Evaluation of the effect of QFPD on the robustness disturbance of COVID-19 network. Blue normal distribution: drug attack on random networks as a null distribution for the permutation test. Red vertical line: the disturbance rate of the drug to the real disease network. Fist row: MXSG, second row: SGMH, third row: XCH, fourth row: WLS, fifth row: Others. Fist column: average connectivity, second row: average length of shortest path, third row: connection centrality, fourth row: closeness centrality. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nTable 5 Docking score between common ingredients of QFPD and 2019-nCov proteins.\nMolecule MS1 MX16 MX17 MX8 MXO1 SO1 SX1 WO1 XO1\nMain Protease −7.6 −7 −7.8 −7.8 −7.8 −7.2 −7.1 −7.4 −7.4\nPapain-like protease −8 −8.2 −8.1 −8.1 −8.2 −8.2 −9.2 −8.7 −8.3\nRdRp with RNA −8.6 −8 −7.9 −7.9 −8 −8.4 −8.2 −8.8 −9.5\nRdRp without RNA −7.1 −6.8 −6.8 −6.8 −7 −7.1 −6.9 −7.5 −7.1\nHelicase ADP site −6.2 −6.5 −6.3 −6.1 −6.2 −6.4 −6.8 −6.2 −6.8\nHelicase NCB site −7.4 −7.1 −7.2 −7.2 −7.5 −7.5 −7.4 −7.6 −7.5\nNsp14(ExoN) −7.2 −6.6 −6.6 −6.7 −6.9 −7 −6.9 −7.1 −7.1\nNsp14(N7-MTase) −8.6 −8.3 −8.4 −8.3 −8.6 −8.3 −9.4 −8.7 −8.7\nNsp15(endoribonuclease) −6.2 −6.8 −6.4 −6.4 −6.3 −6.5 −6.8 −6.4 −6.6\nNsp16(2′-O-MTase) −8.1 −7.4 −7.6 −7.8 −7.8 −8.3 −7.7 −8.4 −8.2\nN protein NCB site −8.1 −7.9 −8 −8 −7.6 −7.8 −7.5 −7.7 −7.9\nE protein(ion channel) −6.4 −6.9 −7.2 −7.2 −6.9 −6.9 −7.9 −6.8 −6.8\nM: MXSG, S: SGMH, X: XCH, O: Others.\nNext, to illustrate the mechanism of QFPD against COVID-19, a formula-attacked target-KEGG pathway network was constructed (Fig. 12 ). This network showed that MSXG, SGMH, XCH, WLS and Others interacted with 8 drug-attacked nodes (Cdc20, Ido1, Ifng, Il10, Il6, Ptger4, Spi1, Tnf), and 24 drug-attacked nodes in the COVID-19 network were related to Graft-versus-host disease, cytokine-cytokine receptor interaction, asthma, influenza A, inflammatory bowel disease, JAK-STAT signaling, etc.\nFig. 12 Disturbance analysis of QFPD for COVID-19 network. A: Venn diagram of the five formulae’ attacked targets. B: Formula-attacked target-KEGG pathway network; green square: formula, yellow diamond: attacked target, red circle: KEGG pathways. The bigger the size of the nodes is, the higher the degree is. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)"}

LitCovid-PD-GO-BP

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T103","span":{"begin":2079,"end":2090},"obj":"http://purl.obolibrary.org/obo/GO_0022831"},{"id":"T104","span":{"begin":2647,"end":2656},"obj":"http://purl.obolibrary.org/obo/GO_0023052"}],"text":"3.8 Validation of drug positioning for QFPD against COVID-19 via the robustness of disease network\nFirstly, the robustness of whole networks against formula attack was assessed to evaluate QFPD attack on the COVID-19 disease network. Interestingly, Table 4 and Fig. 11 showed that MSXG, SGMH, XCH, WLS and Others attack on the COVID-19 network were characterized by greater disturbance score than negative control (BXTM), and increasing dependence on hub nodes, indicating greater fragility under formula attack. In addition, SGMH, MSXG, and Others exerted higher disturbance score than the positive control (YDBF) Table 5 .\nFig. 11 Evaluation of the effect of QFPD on the robustness disturbance of COVID-19 network. Blue normal distribution: drug attack on random networks as a null distribution for the permutation test. Red vertical line: the disturbance rate of the drug to the real disease network. Fist row: MXSG, second row: SGMH, third row: XCH, fourth row: WLS, fifth row: Others. Fist column: average connectivity, second row: average length of shortest path, third row: connection centrality, fourth row: closeness centrality. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nTable 5 Docking score between common ingredients of QFPD and 2019-nCov proteins.\nMolecule MS1 MX16 MX17 MX8 MXO1 SO1 SX1 WO1 XO1\nMain Protease −7.6 −7 −7.8 −7.8 −7.8 −7.2 −7.1 −7.4 −7.4\nPapain-like protease −8 −8.2 −8.1 −8.1 −8.2 −8.2 −9.2 −8.7 −8.3\nRdRp with RNA −8.6 −8 −7.9 −7.9 −8 −8.4 −8.2 −8.8 −9.5\nRdRp without RNA −7.1 −6.8 −6.8 −6.8 −7 −7.1 −6.9 −7.5 −7.1\nHelicase ADP site −6.2 −6.5 −6.3 −6.1 −6.2 −6.4 −6.8 −6.2 −6.8\nHelicase NCB site −7.4 −7.1 −7.2 −7.2 −7.5 −7.5 −7.4 −7.6 −7.5\nNsp14(ExoN) −7.2 −6.6 −6.6 −6.7 −6.9 −7 −6.9 −7.1 −7.1\nNsp14(N7-MTase) −8.6 −8.3 −8.4 −8.3 −8.6 −8.3 −9.4 −8.7 −8.7\nNsp15(endoribonuclease) −6.2 −6.8 −6.4 −6.4 −6.3 −6.5 −6.8 −6.4 −6.6\nNsp16(2′-O-MTase) −8.1 −7.4 −7.6 −7.8 −7.8 −8.3 −7.7 −8.4 −8.2\nN protein NCB site −8.1 −7.9 −8 −8 −7.6 −7.8 −7.5 −7.7 −7.9\nE protein(ion channel) −6.4 −6.9 −7.2 −7.2 −6.9 −6.9 −7.9 −6.8 −6.8\nM: MXSG, S: SGMH, X: XCH, O: Others.\nNext, to illustrate the mechanism of QFPD against COVID-19, a formula-attacked target-KEGG pathway network was constructed (Fig. 12 ). This network showed that MSXG, SGMH, XCH, WLS and Others interacted with 8 drug-attacked nodes (Cdc20, Ido1, Ifng, Il10, Il6, Ptger4, Spi1, Tnf), and 24 drug-attacked nodes in the COVID-19 network were related to Graft-versus-host disease, cytokine-cytokine receptor interaction, asthma, influenza A, inflammatory bowel disease, JAK-STAT signaling, etc.\nFig. 12 Disturbance analysis of QFPD for COVID-19 network. A: Venn diagram of the five formulae’ attacked targets. B: Formula-attacked target-KEGG pathway network; green square: formula, yellow diamond: attacked target, red circle: KEGG pathways. The bigger the size of the nodes is, the higher the degree is. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)"}

LitCovid-sentences

LitCovid-PD-GlycoEpitope

{"project":"LitCovid-PD-GlycoEpitope","denotations":[{"id":"T8","span":{"begin":1391,"end":1394},"obj":"GlycoEpitope"}],"attributes":[{"id":"A8","pred":"glyco_epitope_db_id","subj":"T8","obj":"http://www.glycoepitope.jp/epitopes/AN0690"}],"text":"3.8 Validation of drug positioning for QFPD against COVID-19 via the robustness of disease network\nFirstly, the robustness of whole networks against formula attack was assessed to evaluate QFPD attack on the COVID-19 disease network. Interestingly, Table 4 and Fig. 11 showed that MSXG, SGMH, XCH, WLS and Others attack on the COVID-19 network were characterized by greater disturbance score than negative control (BXTM), and increasing dependence on hub nodes, indicating greater fragility under formula attack. In addition, SGMH, MSXG, and Others exerted higher disturbance score than the positive control (YDBF) Table 5 .\nFig. 11 Evaluation of the effect of QFPD on the robustness disturbance of COVID-19 network. Blue normal distribution: drug attack on random networks as a null distribution for the permutation test. Red vertical line: the disturbance rate of the drug to the real disease network. Fist row: MXSG, second row: SGMH, third row: XCH, fourth row: WLS, fifth row: Others. Fist column: average connectivity, second row: average length of shortest path, third row: connection centrality, fourth row: closeness centrality. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nTable 5 Docking score between common ingredients of QFPD and 2019-nCov proteins.\nMolecule MS1 MX16 MX17 MX8 MXO1 SO1 SX1 WO1 XO1\nMain Protease −7.6 −7 −7.8 −7.8 −7.8 −7.2 −7.1 −7.4 −7.4\nPapain-like protease −8 −8.2 −8.1 −8.1 −8.2 −8.2 −9.2 −8.7 −8.3\nRdRp with RNA −8.6 −8 −7.9 −7.9 −8 −8.4 −8.2 −8.8 −9.5\nRdRp without RNA −7.1 −6.8 −6.8 −6.8 −7 −7.1 −6.9 −7.5 −7.1\nHelicase ADP site −6.2 −6.5 −6.3 −6.1 −6.2 −6.4 −6.8 −6.2 −6.8\nHelicase NCB site −7.4 −7.1 −7.2 −7.2 −7.5 −7.5 −7.4 −7.6 −7.5\nNsp14(ExoN) −7.2 −6.6 −6.6 −6.7 −6.9 −7 −6.9 −7.1 −7.1\nNsp14(N7-MTase) −8.6 −8.3 −8.4 −8.3 −8.6 −8.3 −9.4 −8.7 −8.7\nNsp15(endoribonuclease) −6.2 −6.8 −6.4 −6.4 −6.3 −6.5 −6.8 −6.4 −6.6\nNsp16(2′-O-MTase) −8.1 −7.4 −7.6 −7.8 −7.8 −8.3 −7.7 −8.4 −8.2\nN protein NCB site −8.1 −7.9 −8 −8 −7.6 −7.8 −7.5 −7.7 −7.9\nE protein(ion channel) −6.4 −6.9 −7.2 −7.2 −6.9 −6.9 −7.9 −6.8 −6.8\nM: MXSG, S: SGMH, X: XCH, O: Others.\nNext, to illustrate the mechanism of QFPD against COVID-19, a formula-attacked target-KEGG pathway network was constructed (Fig. 12 ). This network showed that MSXG, SGMH, XCH, WLS and Others interacted with 8 drug-attacked nodes (Cdc20, Ido1, Ifng, Il10, Il6, Ptger4, Spi1, Tnf), and 24 drug-attacked nodes in the COVID-19 network were related to Graft-versus-host disease, cytokine-cytokine receptor interaction, asthma, influenza A, inflammatory bowel disease, JAK-STAT signaling, etc.\nFig. 12 Disturbance analysis of QFPD for COVID-19 network. A: Venn diagram of the five formulae’ attacked targets. B: Formula-attacked target-KEGG pathway network; green square: formula, yellow diamond: attacked target, red circle: KEGG pathways. The bigger the size of the nodes is, the higher the degree is. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)"}

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