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PMC:7247521 JSONTXT 19 Projects

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Id Subject Object Predicate Lexical cue
T1 0-130 Sentence denotes Protection against COVID-19 injury by qingfei paidu decoction via anti-viral, anti-inflammatory activity and metabolic programming
T2 132-150 Sentence denotes Graphical abstract
T3 152-162 Sentence denotes Highlights
T4 163-205 Sentence denotes • A novel FUNP analysis on QFPD function.
T5 206-290 Sentence denotes • QFPD act on COVID-19 via anti-viral, anti-inflammatory and metabolic programming.
T6 291-366 Sentence denotes • 9 QFPD ingredients presented good molecular docking score for 2019-nCov.
T7 367-437 Sentence denotes • SGMH, MXSG and Others are the top 3 efficient formula for COVID-19.
T8 439-447 Sentence denotes Abstract
T9 448-562 Sentence denotes Qingfei Paidu decoction (QFPD), a multi-component herbal formula, has been widely used to treat COVID-19 in China.
T10 563-636 Sentence denotes However, its active compounds and mechanisms of action are still unknown.
T11 637-765 Sentence denotes Firstly, we divided QFPD into five functional units (FUs) according to the compatibility theory of traditional Chinese medicine.
T12 766-1184 Sentence denotes The corresponding common targets of the five FUs were all significantly enriched in Go Ontology (oxidoreductase activity, lipid metabolic process, homeostatic process, etc.), KEGG pathways (steroid biosynthesis, PPAR signaling pathway, adipocytokine signaling pathway, etc.), TTD diseases (chronic inflammatory diseases, asthma, chronic obstructive pulmonary Disease, etc.), miRNA (MIR183), kinase (CDK7) and TF (LXR).
T13 1185-1284 Sentence denotes QFPD contained 257 specific targets in addition to HCoV, pneumonia and ACE2 co-expression proteins.
T14 1285-1402 Sentence denotes Then, network topology analysis of the five components-target-pathway-disease networks yielded 67 active ingredients.
T15 1403-1617 Sentence denotes In addition, ADMET estimations showed that 20 compounds passed the stringent lead-like criteria and in silico drug-likeness test with high gastrointestinal absorption and the median lethal dose (LD50 > 1600 mg/kg).
T16 1618-1824 Sentence denotes Moreover, 4 specific ingredients (M3, S1, X2 and O2) and 5 common ingredients (MS1, MX16, SX1, WO1 and XO1) of QFPD presented good molecular docking score for 2019-nCov structure and non-structure proteins.
T17 1825-2100 Sentence denotes Finally, drug perturbation of COVID-19 network robustness showed that all five FUs may protect COVID-19 independently, and target 8 specifically expressed drug-attacked nodes which were related to the bacterial and viral responses, immune system, signaling transduction, etc.
T18 2101-2258 Sentence denotes In conclusion, our new FUNP analysis showed that QFPD had a protection effect on COVID-19 by regulating a complex molecular network with safety and efficacy.
T19 2259-2384 Sentence denotes Part of the mechanism was associated with the regulation of anti-viral, anti-inflammatory activity and metabolic programming.
T20 2386-2401 Sentence denotes 1 Introduction
T21 2402-2515 Sentence denotes 2019-novel coronavirus (2019-nCov) outbreak took place in December 2019 and continues to spread around the world.
T22 2516-2629 Sentence denotes By April 3, 2020, more than 1 million patients have been diagnosed with corona virus disease 2019 (COVID-19) [1].
T23 2630-2845 Sentence denotes The virus has a long incubation period, is highly contagious, and is generally susceptible to all types of people, which has a huge negative impact on people's health, economic development, and social stability [2].
T24 2846-2937 Sentence denotes However, there is still a lack of effective clinical drugs or vaccine to control the virus.
T25 2938-3071 Sentence denotes Traditional Chinese medicine has a good effect on viral infectious pneumonia and has shown a certain effect in the treatment of SARS.
T26 3072-3763 Sentence denotes On February 7, 2020, the China Health Commission and the Administration of Traditional Chinese Medicine jointly issued a notice recommending formula Qingfei Paidu decoction (QFPD, Herba Ephedrae, Radix Glycyrrhizae, Semen Armeniacae Amarum, Gypsum Fibrosum, Ramulus Cinnamomi, Rhizoma Alismatis, Polyporus Umbellatus, Rhizoma Atractylodis Macrocephalae, Poria, Radix Bupleuri, Radix Scutellariae, Rhizome Pinelliae Preparata, Rhizoma Zingiberis Recens, Radix Asteris, Flos Farfarae, Rhizoma Belamcandae, Herba Asari, Rhizoma Dioscoreae, Fructus Aurantii Immaturus, Pericarpium Citri Reticulatae, Herba Pogostemonis) for the treatment of COVID-19 according to clinical treatment and efficacy.
T27 3764-4020 Sentence denotes QFPD is a compound prescription in TCM including Ma Xing Shi Gan decoction (MSXG), She Gan Ma Huang decoction (SGMH), Xiao Chai Hu (XCH), and Wu Ling San (WLS), which was first discovered in the classic Treatise on Exogenous Febrile Disease (Shanghan Lun).
T28 4021-4267 Sentence denotes MXSG (Herba Ephedrae, Radix Glycyrrhizae, Semen Armeniacae Amarum, Gypsum Fibrosum) has been used for the treatment of the common cold, fever, and influenza virus infections via damaging the viral surface structure and inhibiting viral entry [3].
T29 4268-4532 Sentence denotes SGMH (Herba Ephedrae, Rhizome Pinelliae Preparata, Rhizoma Zingiberis Recens, Radix Asteris, Flos Farfarae, Rhizoma Belamcandae, Herba Asari) is a classical prescription for the treatment of flu-like symptoms, asthma, inflammation, tonsillitis and sore throat [4].
T30 4533-4718 Sentence denotes XCH (Radix Glycyrrhizae, Radix Bupleuri, Radix Scutellariae, Rhizome Pinelliae Preparata, Rhizoma Zingiberis Recens) possesses antiviral [5] and various anticarcinogenic properties [6].
T31 4719-4958 Sentence denotes WLS (Ramulus Cinnamomi, Rhizoma Alismatis, Polyporus Umbellatus, Rhizoma Atractylodis Macrocephalae, Poria), a famous Chinese prescription for nephritic syndrome, can improve kidney excretion function and inhibit inflammatory response [7].
T32 4959-5054 Sentence denotes These researches indicate that MXSG, SGMH, XCH and WLS may be functional units of formula QFPD.
T33 5055-5174 Sentence denotes Previous studies have focused on the mechanism of compound prescription based on a single traditional Chinese medicine.
T34 5175-5270 Sentence denotes However, it may not reflect functional compatibility mechanism of traditional Chinese medicine.
T35 5271-5448 Sentence denotes Therefore, it is worthy of comparing the similarities and differences of different QFPD functional units in the treatment of COVID-19, including MXSG, SGMH, XCH, WLS and Others.
T36 5449-5683 Sentence denotes QFPD contains a total of 21 traditional Chinese medicines, and it is difficult to elucidate the complex mechanism of QFPD on COVID-19 by traditional pharmacological methods due to the multi-components and multi-targets of the formula.
T37 5684-5841 Sentence denotes Network pharmacology, a new method in recent years, can integrate interactions of drugs, targets, pathways and diseases into a biological network system [8].
T38 5842-6113 Sentence denotes Therefore, more and more TCM researchers have begun to use network pharmacology to explore the material basis of TCM, and to reveal the overall comprehensive effects of multi-path, multi-component and multi-target of TCM prescription and its treatment of diseases [9,10].
T39 6114-6283 Sentence denotes More importantly, previous study reported that disease conditions can be more fragile than health systems against various perturbations for the un-optimized system [11].
T40 6284-6439 Sentence denotes So the formula may be more effective for COVID-19 disease via the stronger effects on the reduction of the robustness of the COVID-19 disease network [12].
T41 6440-6660 Sentence denotes In our study, since MSXG, SGMH, XCH and WLS have been independently used for the treatment of viral infectious pneumonia, this study firstly screened out major effective compounds from five functional units respectively.
T42 6661-6979 Sentence denotes Then we offered a new understanding of the functional units mechanism of QFPD against COVID-19 by a novel functional units of network pharmacology (FUNP) approach and formula perturbation analysis, and provided a combination strategy to explore mechanisms of inter-ingredients interactions from a holistic perspective.
T43 6981-7005 Sentence denotes 2 Materials and methods
T44 7007-7028 Sentence denotes 2.1 Data preparation
T45 7029-7221 Sentence denotes Compounds of the main herb in formula MSXG, SGMH, XCH, WLS and Others were searched in TCMSP [13], and screened based on drug-likeness (DL) ≥0.18 [14] and oral bioavailability (OB) ≥30 % [15].
T46 7222-7322 Sentence denotes Then, the corresponding Pubchem CIDs of the compounds were retrieved from the Pubchem database [16].
T47 7323-7518 Sentence denotes Finally, BATMAN-TCM [17], an bioinformatics analysis tool for studying TCM’s molecular mechanisms, was used to identify potential target genes of the active components (uploaded by Pubchem CIDs).
T48 7519-7599 Sentence denotes To make the results more credible, we set the cutoff score ≥ 30 as the standard.
T49 7600-7790 Sentence denotes Finally, to discovery the co-differentially presented targets in the five formulae, we conducted pan-formula analysis using Venn diagrams (http://bioinformatics.psb.ugent.be/webtools/Venn/).
T50 7792-7855 Sentence denotes 2.2 Functional and pathway enrichment analyses of QFPD targets
T51 7856-8133 Sentence denotes To better understand the functional involvements of MSXG, SGMH, XCH, WLS and Others targets, bioinformatics analyses of multiple formulae targets were first performed, including Gene Ontology (GO) function term, KEGG biological pathway and OMIM/TTD disease enrichment analyses.
T52 8134-8432 Sentence denotes Then, kinase, microRNA and transcriptional factor (TF) enrichment analyses of the five formulae targets were conducted using the tool WebGestalt (http://bioinfo.vanderbilt.edu/webgestalt) [18] and the bubble and chord plot map were drawn with the R language ggplot2 and GOplot installation package.
T53 8433-8510 Sentence denotes P-values were adjusted for multiple testing by Benjamini-Hochberg adjustment.
T54 8512-8571 Sentence denotes 2.3 Construction of PPI network and MCODE modules analysis
T55 8572-8715 Sentence denotes To further explore the pharmacological mechanisms, five PPI networks were built including: MSXG, SGMH, XCH, WLS and Others targets PPI network.
T56 8716-8870 Sentence denotes Specifically, the five kinds of target proteins were respectively uploaded to Metascape to build PPI networks, with the species limited to “Homo sapiens”.
T57 8871-9030 Sentence denotes Next, MCODE analysis [19], a method for finding densely connected modules in PPI networks, was carried out by Cytoscape 3.2.1 (http://www.cytoscape.org/) [20].
T58 9031-9254 Sentence denotes Finally, KEGG (Kyoto Encyclopedia of Genes and Genomes) signaling pathway enrichment analysis was further conducted on the identified functional modules of MSXG, SGMH, XCH, WLS and Others targets PPI networks, respectively.
T59 9256-9281 Sentence denotes 2.4 Network construction
T60 9282-9445 Sentence denotes Based on the five formulae’s active components, BATMAN-TCM was used to set up five networks of components-target-pathway-disease (MSXG, SGMH, XCH, WLS and Others).
T61 9446-9686 Sentence denotes To emphasize the important elements of the five networks, we only exhibited the hub targets according to the default criteria (targets with no fewer than 6, 5, 8, 7 and 4 linking compounds for MSXG, SGMH, XCH, WLS and Others, respectively).
T62 9687-9809 Sentence denotes Finally, these important linking compounds of MSXG, SGMH, XCH, WLS and Others networks were obtained for further analysis.
T63 9811-9866 Sentence denotes 2.5 ADMET evaluation of the predicted active compounds
T64 9867-10100 Sentence denotes Based on the SwissADME database [21], the physicochemical properties of the active components was predicted, including molecular weight (MW), rotatable bonds count, H-bond acceptors and donors count, TPSA and leadlikeness violations.
T65 10101-10597 Sentence denotes Second, pharmacokinetic properties was predicted through pkCSM database [22], which contained the absorption (Caco-2 cell permeability, HIA and skin permeability), distribution (VDss, unbound fraction, blood-brain barrier and central nervous system permeability), excretion (total clearance and renal OCT2 substrate) and toxicity (AMES toxicity, maximum tolerated dose, hERG I inhibitor, hERG II inhibitor, oral rat acute toxicity (LD50), hepatotoxicity, skin sensitisation, and minnow toxicity).
T66 10599-10621 Sentence denotes 2.6 Molecular docking
T67 10622-10838 Sentence denotes To facilitate drug discovery against COVID-19, we used COVID-19 Docking Server (https://ncov.schanglab.org.cn/index.php) [23] to predict the binding modes between 12 COVID-19 targets and the 20 lead-likeness of QFPD.
T68 10839-11383 Sentence denotes Specifically, the 10 nonstructural and 2 structural proteins of 2019-nCov were collected (Mpro, PLpro, nsp12 [RdRp with RNA], nsp12 [RdRp without RNA], nsp13 [Helicase ADP site], nsp13 [Helicase NCB site], nsp14 [ExoN], nsp14 [N7-MTase], nsp15 [endoribonuclease], nsp16 [2′-O-MTase], N protein NCB site and E protein [ion channel]); and the corresponding Protein Data Bank (PDB)codes were 6LU7, 4OW0, 3H5Y (with RNA), 3H5Y (without RNA), 6JYT (ADP site), 6JYT (NCB site), 5C8S (ExoN),5C8S (N7-MTase), 2RHB, 2XYR, 4KYJ, and 5 × 29, respectively.
T69 11384-11509 Sentence denotes Finally, Discovery Studio software elucidated the 14 best docking results between compounds and the COVID-19 target proteins.
T70 11511-11580 Sentence denotes 2.7 ACE2 and CD147 expression across tissues and co-expression genes
T71 11581-11732 Sentence denotes To understand the expression and distribution of ACE2 and CD147 across tissues, a radar plot including 53 tissues was performed through COXPRESdb [24].
T72 11733-11827 Sentence denotes And the top 200 co-expression genes of ACE2 and CD147 (P < 1E-16) were obtained, respectively.
T73 11828-11967 Sentence denotes Then, text mining method from the literature was used to screen for pneumonia-associated genes through COREMINE (http://www.coremine.com/).
T74 11968-12111 Sentence denotes In addition, co-expression genes of ACE2 in colonic epithelial cells [25] and HCoV-associated host proteins with references [26] were obtained.
T75 12112-12238 Sentence denotes Finally, we performed UpsetView analysis (http://www.ehbio.com/ImageGP/) between these five sets of proteins and QFPD targets.
T76 12240-12339 Sentence denotes 2.8 Validation of drug positioning for QFPD against COVID-19 via the robustness of disease network
T77 12340-12581 Sentence denotes Since QFPD effects on COVID-19 via multi-component and multi-target, we evaluate the potential efficacy of QFPD through TCMATCOV platform, which uses the quantitative evaluation algorithm of multi-target drugs to disturb the disease network.
T78 12582-12686 Sentence denotes Specifically, the disturbing effect of drugs on diseases is simulated by deleting disease network nodes.
T79 12687-12899 Sentence denotes The disturbance rate of drugs is calculated by comparing the changes of network topology characteristics before and after drug intervention, which is used to evaluate the intervention effect of drugs on diseases.
T80 12900-13069 Sentence denotes Firstly, COVID-19 disease network was constructed based on specific cytokines of COVID-19 [27] and differentially expressed genes of SARS (GSE36969, GSE51387, GSE68820).
T81 13070-13312 Sentence denotes Then, this platform uses four kinds of network topology characteristics to evaluate the robustness of COVID-19 network, including network average connectivity, network average shortest path, connectivity centrality and compactness centrality.
T82 13313-13463 Sentence denotes And the five formulae (MSXG, SGMH, XCH, WLS and Others) disturbance scores are calculated according to the changes before and after drug intervention.
T83 13464-13719 Sentence denotes Finally, the disturbance effect of the five formulae on the COVID-19 network was compared with null models with the total score of the disturbance, and the higher the value is, the higher the damage degree of drugs to the stability of the network is [12].
T84 13720-13867 Sentence denotes We take Banxia tianma baizhu decoction (BXTM) as negative control; and another efficient formula Yi du bi fei decoction (YDBF) as positive control.
T85 13869-13878 Sentence denotes 3 Result
T86 13880-13946 Sentence denotes 3.1 Prediction of active components and potential targets of QFPD
T87 13947-14084 Sentence denotes Firstly, the DL ≥ 0.18 and OB ≥ 30 %.s were set as the standard to screen the chemical components obtained through online database TCMSP.
T88 14085-14304 Sentence denotes Specifically, a total of 175 effective components of QFPD were screened from the TCM database, including 82 species of MSXG, 35 species of SGMH, 105 species of XCH, 21 species of WLS and 32 species of Others (Table 1 ).
T89 14305-14527 Sentence denotes Among these effective components, 89 (50.86 %) components exited in more than two formulae; CID5280343 and CID5280794 were owned by MXSG, Others, SGMH and XCH; CID12303645 was owned by MXSG, Others, WLS and XCH (Fig. 1 A).
T90 14528-14728 Sentence denotes Secondly, a total of 300 targets of QFPD were screened from the BATMAN-TCM database, including 192 targets of MSXG, 201 targets of SGMH, 221 targets of XCH, 96 targets of WLS and 99 targets of Others.
T91 14729-14801 Sentence denotes Among these proteins, 21 (7%) targets exited in five formulae (Fig. 1B).
T92 14802-14839 Sentence denotes Table 1 Effective components of QFPD.
T93 14840-14861 Sentence denotes Formula N PubChem_Cid
T94 14862-15757 Sentence denotes MSXG 82 CID10090416,CID10542808,CID10881804,CID11267805,CID114829,CID11558452,CID11602329,CID11975273,CID120074,CID12303645,CID124049,CID124052,CID13965473,CID14604077,CID14604078,CID14604081,CID15228663,CID15380912,CID162412,CID177149,CID193679,CID197678,CID23724664,CID25015742,CID268208,CID336327,CID354368,CID3764,CID439246,CID440833,CID442411,CID44257530,CID480774,CID480780,CID480787,CID480859,CID480873,CID49856081,CID503731,CID503737,CID5280343,CID5280378,CID5280448,CID5280544,CID5280794,CID5280863,CID5281619,CID5281654,CID5281789,CID5282768,CID5282805,CID5312521,CID5316900,CID5317300,CID5317478,CID5317479,CID5317480,CID5317652,CID5317768,CID5317777,CID5318437,CID5318585,CID5318679,CID5318869,CID5318998,CID5318999,CID5319013,CID5320083,CID5460988,CID5481234,CID5481948,CID5481949,CID5997,CID636883,CID637112,CID64971,CID6918970,CID73205,CID928837,CID9927807,CID15840593,CID15228662
T95 15758-16244 Sentence denotes SGMH 35 CID1135,CID1174,CID3026,CID5789,CID6782,CID6998,CID8437,CID8679,CID13625,CID117158,CID159225,CID185,CID10019512,CID11438306,CID11869417,CID11870462,CID12315507,CID162350,CID16726037,CID222284,CID389888,CID3902,CID440833,CID5280343,CID5280445,CID5280544,CID5280794,CID5280863,CID5281331,CID5281605,CID5281616,CID5281628,CID5281654,CID5281779,CID5282768,CID5315890,CID5316876,CID5320945,CID5484202,CID5488781,CID5491637,CID64959,CID64982,CID676152,CID71307581,CID72307,CID13688752
T96 16245-17385 Sentence denotes XCH 105 CID10090416,CID10542808,CID10881804,CID11267805,CID11438306,CID114829,CID11558452,CID11602329,CID117443,CID12303645,CID124049,CID124052,CID124211,CID13965473,CID14135323,CID14604077,CID14604078,CID14604081,CID15228662,CID15228663,CID15380912,CID156992,CID158311,CID15840593,CID159029,CID161271,CID162412,CID177149,CID185034,CID193679,CID197678,CID222284,CID23724664,CID25015742,CID25721350,CID268208,CID336327,CID354368,CID373261,CID3764,CID389001,CID389888,CID439246,CID442411,CID44257530,CID44258628,CID480774,CID480780,CID480787,CID480859,CID480873,CID49856081,CID503731,CID503737,CID5280343,CID5280378,CID5280442,CID5280448,CID5280794,CID5280863,CID5281605,CID5281619,CID5281654,CID5281674,CID5281703,CID5281789,CID5282768,CID5312521,CID5316900,CID5317300,CID5317478,CID5317479,CID5317480,CID5317652,CID5317768,CID5317777,CID5318437,CID5318585,CID5318679,CID5318869,CID5318998,CID5318999,CID5319013,CID5319042,CID5319252,CID5320083,CID5320315,CID5320399,CID5321865,CID5322059,CID5322078,CID5460988,CID5481234,CID5481948,CID5481949,CID5484202,CID636883,CID637112,CID64959,CID64971,CID64982,CID73205,CID821279,CID928837,CID9927807
T97 17386-17626 Sentence denotes WLS 21 CID10181133,CID10743008,CID12303645,CID14036811,CID15225964,CID15226717,CID15976101,CID182232,CID222284,CID44575602,CID5283628,CID5471851,CID5471852,CID56668247,CID6436630,CID712316,CID73402,CID9064,CID9805290,CID14448075,CID14236575
T98 17627-17971 Sentence denotes Others 32 CID10212,CID11824478,CID122159,CID12303645,CID14057197,CID145659,CID17897,CID33934,CID373261,CID40429858,CID42607889,CID439246,CID442834,CID443024,CID5280343,CID5280445,CID5280794,CID5281326,CID5281617,CID5281781,CID5319406,CID5320621,CID5495928,CID5997,CID631170,CID632135,CID676152,CID712316,CID72344,CID79730,CID1149877,CID45359875
T99 17972-18043 Sentence denotes Fig. 1 Venn diagram of the five formulae’ active compounds and targets.
T100 18044-18069 Sentence denotes A: compounds, B: targets.
T101 18071-18134 Sentence denotes 3.2 Functional and pathway enrichment analyses of QFPD targets
T102 18135-18407 Sentence denotes As shown in Fig. 2 , the 11 enriched GO terms of the targets in all five formulae were found, such as oxidoreductase activity, lipid metabolic process, lipid binding, small molecule metabolic process, homeostatic process, signal transducer activity and cell proliferation.
T103 18408-18778 Sentence denotes Furthermore, the results of pathway enrichment analysis showed that the 7 KEGG pathways were significantly related to more than 4 formula groups, including dteroid biosynthesis, adipocytokine signaling pathway, neuroactive ligand-receptor interaction, steroid hormone biosynthesis, PPAR signaling pathway, arginine and proline metabolism and ABC transporters (Fig. 3 A).
T104 18779-19009 Sentence denotes In addition, TTD analysis showed that the 8 diseases were significantly association with more than 3 formula groups, such as acne, Behcet'S disease, benign prostate hyperplasia, intrahepatic cholestasis and brain injury (Fig. 3B).
T105 19010-19119 Sentence denotes However, the five formulae contained their specific (MSXG, SGMH, XCH, WLS and Others) GO, KEGG and TTD terms.
T106 19120-19513 Sentence denotes For example, neurological system process and beta-Alanine metabolism terms were specific for MXSG; membrane organization and parasitic infections of the eye terms for SGMH; circadian rhythm and hypertension terms for XCH; nucleic acid binding transcription factor activity, ovarian steroidogenesis and chronic inflammatory diseases terms for WLS; fat digestion and absorption terms for Others.
T107 19514-19582 Sentence denotes Fig. 2 Bubble plot of the GO analysis of the five formulae’ targets.
T108 19583-19657 Sentence denotes Fig. 3 Bubble plot of the KEGG/TTD analysis of the five formulae’ targets.
T109 19658-19674 Sentence denotes A: KEGG, B: TTD.
T110 19675-19880 Sentence denotes In the prediction of miRNAs in QFPD targets, MIR-183 and MIR-130A/B/301 were the highest linking terms to bind the five formulae targets and formulae Others was the highest group to bind miRNAs (Fig. 4 A).
T111 19881-20008 Sentence denotes In addition, kinase prediction revealed CDK7 were significantly enriched in formulae MSXG, SGMH, XCH, WLS and Others (Fig. 4B).
T112 20009-20168 Sentence denotes Finally, TF analysis showed that LXR was the highest linking TF to bind the four formulae targets and formulae WLS was the highest group to bind TFs (Fig. 4C).
T113 20169-20254 Sentence denotes Fig. 4 The miRNA, kinase and TF analysis of the five formulae’ targets by WebGestalt.
T114 20255-20364 Sentence denotes Chord plot showing the five formulae’ targets present in the represented enriched miRNA, kinase and TF terms.
T115 20365-20470 Sentence denotes Outer ring shows miRNA/kinase/TF term and log2 enrichment ratio (left) or five formulae grouping (right).
T116 20471-20528 Sentence denotes Chords connect miRNA/kinase/TF term with formulae groups.
T117 20529-20556 Sentence denotes A: miRNA, B: kinase, C: TF.
T118 20558-20617 Sentence denotes 3.3 Construction of PPI network and MCODE modules analysis
T119 20618-20783 Sentence denotes To further explore the functional relationship among five formulae, PPI networks were constructed through Metascape, and visual composition carried out by Cytoscape.
T120 20784-20989 Sentence denotes Firstly, the potential 192 target genes of MXSG were analyzed by PPI network, and the results showed that there were 144 nodes and 510 edges, which represented the interaction between protein and function.
T121 20990-21134 Sentence denotes The MXSG PPI network function module was confirmed by the MCODE plug-in and a list of the corresponding meaningful modules presented (Fig. 5 A).
T122 21135-21163 Sentence denotes 3 modules scores were > 2.5.
T123 21164-21180 Sentence denotes Module 1 (score:
T124 21181-21256 Sentence denotes 5.769) consisted of 13 nodes and the seed gene was COX7A1; Module 2 (score:
T125 21257-21333 Sentence denotes 4.429) consisted of 14 nodes and the seed gene was ALDH1A1; module 3 (score:
T126 21334-21388 Sentence denotes 5.0) consisted of 11 nodes and the seed gene was CNR2.
T127 21389-21588 Sentence denotes KEGG pathway enrichment analysis showed that MXSG modules were enriched in neuroactive ligand-receptor interaction, calcium signaling pathway, inflammatory mediator regulation of TRP channels, et.al.
T128 21589-21627 Sentence denotes Fig. 5 KEGG analysis of MCODE modules.
T129 21628-21770 Sentence denotes MCODE analysis was performed after the construction of the five formulae’ targets PPI; then, KEGG analysis was conducted on the MCODE modules.
T130 21771-21782 Sentence denotes A: MXSG, B:
T131 21783-21815 Sentence denotes Others, C: WLS, D: SGMH, E: XCH.
T132 21816-21958 Sentence denotes Secondly, the potential 99 target genes of Others were analyzed by PPI network, and the results showed that there were 77 nodes and 194 edges.
T133 21959-22000 Sentence denotes Only 1 module score were > 2.5 (Fig. 5B).
T134 22001-22017 Sentence denotes Module 1 (score:
T135 22018-22076 Sentence denotes 5.769) consisted of 13 nodes and the seed gene was COX7A1.
T136 22077-22237 Sentence denotes KEGG pathway enrichment analysis showed that Others modules were enriched in huntington's disease, glycolysis / gluconeogenesis, Notch signaling pathway, et.al.
T137 22238-22376 Sentence denotes Thirdly, the potential 96 target genes of WLS were analyzed by PPI network, and the results showed that there were 60 nodes and 143 edges.
T138 22377-22419 Sentence denotes Only 1 modules score were > 2.5 (Fig. 5C).
T139 22420-22436 Sentence denotes Module 1 (score:
T140 22437-22493 Sentence denotes 2.706) consisted of 17 nodes and the seed gene was CNR2.
T141 22494-22683 Sentence denotes KEGG pathway enrichment analysis showed that WLS modules were enriched in thyroid hormone signaling pathway, adipocytokine signaling pathway, neuroactive ligand-receptor interaction, et.al.
T142 22684-22826 Sentence denotes Fourthly, the potential 201 target genes of SGMH were analyzed by PPI network, and the results showed that there were 153 nodes and 505 edges.
T143 22827-22865 Sentence denotes 3 modules scores were > 2.5 (Fig. 5D).
T144 22866-22882 Sentence denotes Module 1 (score:
T145 22883-22957 Sentence denotes 3.529) consisted of 17 nodes and the seed gene was ACSS1; Module 2 (score:
T146 22958-23028 Sentence denotes 4.5) consisted of 7 nodes and the seed gene was CNR2; module 3 (score:
T147 23029-23083 Sentence denotes 3.5) consisted of 8 nodes and the seed gene was PRKCG.
T148 23084-23245 Sentence denotes KEGG pathway enrichment analysis showed that SGMH modules were enriched in insulin resistance, adipocytokine signaling pathway, Th17 cell differentiation, et.al.
T149 23246-23386 Sentence denotes At last, the potential 221 target genes of XCH were analyzed by PPI network, and the results showed that there were 166 nodes and 643 edges.
T150 23387-23425 Sentence denotes 5 modules scores were > 2.5 (Fig. 5E).
T151 23426-23442 Sentence denotes Module 1 (score:
T152 23443-23518 Sentence denotes 5.769) consisted of 13 nodes and the seed gene was COX7A1; Module 2 (score:
T153 23519-23592 Sentence denotes 2.769) consisted of 13 nodes and the seed gene was RRM1; module 3 (score:
T154 23593-23664 Sentence denotes 5.5) consisted of 12 nodes and the seed gene was CNR2; module 4 (score:
T155 23665-23739 Sentence denotes 2.909) consisted of 11 nodes and the seed gene was ACSS1; module 5 (score:
T156 23740-23794 Sentence denotes 3.0) consisted of 7 nodes and the seed gene was FFAR1.
T157 23795-23971 Sentence denotes KEGG pathway enrichment analysis showed that XCH modules were enriched in calcium signaling pathway, cGMP-PKG signaling pathway, neuroactive ligand-receptor interaction, et.al.
T158 23973-23998 Sentence denotes 3.4 Network construction
T159 23999-24134 Sentence denotes After using the BATMAN-TCM, we constructed five ingredients-target-pathway-disease networks, including MSXG, SGMH, XCH, WLS and Others.
T160 24135-24351 Sentence denotes In order to emphasize the important network elements, we showed the networks that exhibit those targets with larger than 6, 5, 8, 7 and 4 linking compounds for MSXG, SGMH, XCH, WLS and Others, respectively (Fig. 6 ).
T161 24352-24702 Sentence denotes MSXG network contained 31 key components, 50 proteins and 17 pathways; SGMH network contained 15 key components, 20 proteins and 8 pathways; WLS network contained 18 key components, 9 proteins and 4 pathways; XCH network contained 32 key components, 15 proteins and 12 pathways; Others network contained 10 key components, 13 proteins and 3 pathways.
T162 24703-24820 Sentence denotes To find the potential drugs of formulae QFPD for COVID-19, a total of 67 hub components were used for ADMET analysis.
T163 24821-24873 Sentence denotes Fig. 6 The component-target-pathway-disease network.
T164 24874-24890 Sentence denotes Purple polygons:
T165 24891-24993 Sentence denotes PubChem ID of QFPD compounds; blue pentagrams: QFPD targets; yellow circles: KEGG pathway; red square:
T166 24994-25055 Sentence denotes Therapeutic Target Database (TTD) disease term, green square:
T167 25056-25112 Sentence denotes Online Mendelian Inheritance in Man (OMIN) disease term.
T168 25113-25149 Sentence denotes A: MXSG, B: SGMH, C: WLS, D: XCH, E:
T169 25150-25288 Sentence denotes Others. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
T170 25290-25335 Sentence denotes 3.5 ADMET evaluation of the 67 key compounds
T171 25336-25491 Sentence denotes Since in silico ADMET prediction can help early drug design and evaluation, ADMET properties of the 67 key compounds were predicted by SwissADME and pkCSM.
T172 25492-25686 Sentence denotes Chemical properties including molecular weight (MW), rotatable bonds count, H-bond acceptors and donors count, TPSA and leadlikeness violations were calculated by SwissADME and shown as Fig. 8A.
T173 25687-25906 Sentence denotes It is worth mentioning that 21 (31.34 %) compounds passed the stringent lead-like criteria (250 g/mol ≤ MW ≤ 350 g/mol, XLOGP ≤ 3.5 and rotatable bonds ≤ 7), which are excellent candidates for drug discovery (Fig. 7 A).
T174 25907-26032 Sentence denotes And these lead-likeness compounds were further predicted by pkCSM, with the exception of S3 (low gastrointestinal absorption)
T175 26033-26105 Sentence denotes Fig. 7 Chemical properties statistics of hub components in the formulae.
T176 26106-26108 Sentence denotes A:
T177 26109-26409 Sentence denotes Molecular weight, B: rotatable bond count, C: H-bond acceptors count, D: H-bond donors count, E: topological polar surface area (TPSA), F: leadlikeness violations, G: pharmacokinetic and toxicity evaluated parameters of 20 leadlikeness compounds by pkCSM; green = good, yellow = tolerable, red = bad.
T178 26410-26416 Sentence denotes Caco2:
T179 26417-26441 Sentence denotes Caco-2 Permeability,HIA:
T180 26442-26478 Sentence denotes Intestinal Absorption (Human), Skin:
T181 26479-26531 Sentence denotes Skin Permeability, VDss: volume of distribution, FU:
T182 26532-26562 Sentence denotes Fraction Unbound (Human), BBB:
T183 26563-26601 Sentence denotes Blood Brain Barrier permeability, CNS:
T184 26602-26641 Sentence denotes Central Nervous System permeability,TC:
T185 26642-26664 Sentence denotes Total Clearance, OCT2:
T186 26665-26727 Sentence denotes Renal Organic Cation Transporter 2, AMES: AMES toxicity, MTDD:
T187 26728-26802 Sentence denotes Maximum Tolerated Dose (Human), hERG I/II: hERG I and II Inhibitors, LD50:
T188 26803-26838 Sentence denotes Oral Rat Acute Toxicity (LD50), HT:
T189 26839-26858 Sentence denotes Hepatotoxicity, SS:
T190 26859-26882 Sentence denotes Skin Sensitisation, MT:
T191 26883-27030 Sentence denotes Minnow toxicity. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
T192 27031-27158 Sentence denotes Fig. 8 Schematic (3D and 2D) representation that molecular model of specific compounds of each formulae with COVID-19 proteins.
T193 27159-27316 Sentence denotes A: M3 and E protein [ion channel], B: M3 and nsp13 [Helicase NCB site], C: S1 and nsp13 [Helicase ADP site], D: S1 and PLpro, E: X2 and Mpro, F: O2 and Mpro.
T194 27317-27345 Sentence denotes M: MXSG, S: SGMH, X: XCH, O:
T195 27346-27353 Sentence denotes Others.
T196 27354-27533 Sentence denotes Regarding the absorption parameters, all 20 compounds (Table 2 ) presented a promising oral availability including the optimal Caco-2 cell permeability, HIA and skin permeability.
T197 27534-27765 Sentence denotes The drug distribution results showed that most of the compounds distributed in tissue (VDss> 0.45: tissue, VDss <−0.15: plasma) with good unbound fraction scores, thus becoming available to interact with the pharmacological target.
T198 27766-27888 Sentence denotes Only compound W5 and W11 were entirely unable to penetrate the blood-brain barrier (BBB) and central nervous system (CNS).
T199 27889-28023 Sentence denotes In addition, 15 compounds presented a good renal elimination and were not substrates of the renal organic cation transporter 2 (OCT2).
T200 28024-28279 Sentence denotes Finally, 14 compounds did not present any particular toxicity problems including AMES toxicity, maximum tolerated dose, hERG I inhibitor, hERG II inhibitor, oral rat acute toxicity (LD50), hepatotoxicity, skin sensitisation, and minnow toxicity (Fig. 7B).
T201 28280-28328 Sentence denotes Table 2 20 potential active compounds from QFPD.
T202 28329-28394 Sentence denotes Pubchem Molecular Name Structure Pubchem Molecular Name Structure
T203 28395-28455 Sentence denotes CID6918970 M3 ZINC5356864 CID10019512 S5 3-O-Methylviolanone
T204 28456-28501 Sentence denotes CID336327 M5 Medicarpin CID9064 W5 Cianidanol
T205 28502-28548 Sentence denotes CID14057197 O1 – CID182232 W11 (+)-Epicatechin
T206 28549-28605 Sentence denotes CID42607889 O2 Alysifolinone CID25721350 X1 ZINC13130930
T207 28606-28663 Sentence denotes CID3902 S1 letrozole CID14135323 X2 (2S)-dihydrobaicalein
T208 28664-28713 Sentence denotes CID821279 X4 ZINC338038 CID439246 MXO1 naringenin
T209 28714-28773 Sentence denotes CID440833 MS1 Leucocyanidol CID676152 SO1 SR-01,000,767,148
T210 28774-28836 Sentence denotes CID177149 MX16 (+)-Vestitol CID11438306 SX1 cyclo(L-Tyr-l-Phe)
T211 28837-28894 Sentence denotes CID114829 MX17 Liquiritigenin CID712316 WO1 (-)-taxifolin
T212 28895-28957 Sentence denotes CID928837 MX8 ZINC519174 CID373261 XO1 Eriodyctiol (flavanone)
T213 28958-28986 Sentence denotes M: MXSG, S: SGMH, X: XCH, O:
T214 28987-28994 Sentence denotes Others.
T215 28996-29018 Sentence denotes 3.6 Molecular docking
T216 29019-29544 Sentence denotes The application of COVID-19 docking server and Discovery Studio software elucidated the interactions between the 20 lead-likeness compounds (S1, W5, MX17, MX16, W11, M5, XO1, MXO1, SO1, WO1, X4, MX8, M3, S5, SX1, O1, X2, X1, O2, MS1) and the 10 nonstructural and 2 structural proteins (Mpro, PLpro, nsp12 [RdRp with RNA], nsp12 [RdRp without RNA], nsp13 [Helicase ADP site], nsp13 [Helicase NCB site], nsp14 [ExoN], nsp14 [N7-MTase], nsp15 [endoribonuclease], nsp16 [2′-O-MTase], N protein NCB site, E protein [ion channel]).
T217 29545-29599 Sentence denotes The docking scores were depicted in Table 3, Table 4 .
T218 29600-29744 Sentence denotes The smaller of docking score, the lower of energy would be required, which means the binding between the compounds and the targets are stronger.
T219 29745-29822 Sentence denotes There are 9 compounds presenting better bonding ability than other compounds.
T220 29823-29905 Sentence denotes Table 3 Docking score between specific ingredients of QFPD and 2019-nCov proteins.
T221 29906-29948 Sentence denotes Molecule M3 M5 S1 S5 W11 W5 X1 X2 X4 O1 O2
T222 29949-30017 Sentence denotes Main Protease −7.7 −7.3 −6.8 −6.9 −7.2 −7.5 −7.1 −7.9 −7.3 −7.1 −7.4
T223 30018-30089 Sentence denotes Papain-like protease −8.7 −8.5 −9.9 −7.7 −8 −8 −8.4 −8.7 −8.2 −8.6 −8.2
T224 30090-30158 Sentence denotes RdRp with RNA −8.4 −8.5 −8.5 −8.3 −9.1 −9.1 −8.4 −8.2 −8.2 −8.3 −8.6
T225 30159-30230 Sentence denotes RdRp without RNA −6.8 −6.8 −6.9 −6.8 −6.7 −6.9 −7.1 −7.2 −6.5 −7.3 −7.1
T226 30231-30299 Sentence denotes Helicase ADP site −6.3 −6.3 −7.3 −6.5 −6 −6 −6.3 −6.5 −6.2 −6.1 −6.5
T227 30300-30372 Sentence denotes Helicase NCB site −7.9 −6.9 −7.2 −7.1 −7.2 −7.2 −7.4 −7.5 −7.3 −7.4 −7.4
T228 30373-30439 Sentence denotes Nsp14(ExoN) −6.8 −6.6 −6.3 −6.4 −6.9 −6.8 −6.7 −6.9 −6.4 −6.6 −6.9
T229 30440-30508 Sentence denotes Nsp14(N7-MTase) −8.8 −8.1 −8.5 −7.5 −8.4 −8.4 −8.3 −8.5 −8 −8.3 −8.5
T230 30509-30587 Sentence denotes Nsp15(endoribonuclease) −6.6 −6.3 −6.3 −5.9 −6.2 −6.2 −6.2 −6.3 −6.2 −6.4 −6.4
T231 30588-30660 Sentence denotes Nsp16(2′-O-MTase) −7.5 −7.4 −7.5 −7.2 −8.2 −8.2 −7.7 −7.9 −7.7 −7.9 −8.4
T232 30661-30730 Sentence denotes N protein NCB site −7.6 −7.5 −7.8 −7.6 −7.6 −7.6 −8 −8 −7.5 −7.6 −7.6
T233 30731-30806 Sentence denotes E protein(ion channel) −8.1 −7 −7.8 −6.7 −6.4 −6.4 −7.2 −7.3 −7.2 −7.1 −6.8
T234 30807-30835 Sentence denotes M: MXSG, S: SGMH, X: XCH, O:
T235 30836-30843 Sentence denotes Others.
T236 30844-30935 Sentence denotes Table 4 Evaluation of the effect of QFPD on the robustness disturbance of COVID-19 network.
T237 30936-30979 Sentence denotes Topology MXSG SGMH XCH WLS Others BXTM YDBF
T238 30980-31025 Sentence denotes DTS 25.66 26.71 21.02 17.64 23.16 14.52 22.71
T239 31026-31070 Sentence denotes AC −4.63 −5.21 −3.02 −3.49 −5.38 −2.32 −3.78
T240 31071-31113 Sentence denotes APL 13.35 13.40 9.96 6.49 10.66 4.59 11.17
T241 31114-31159 Sentence denotes CoC −1.44 −1.64 −1.59 −1.30 −1.23 −1.15 −1.25
T242 31160-31205 Sentence denotes ClC −6.24 −6.46 −6.45 −6.36 −5.88 −6.46 −6.52
T243 31206-31391 Sentence denotes Average connectivity (AC), Connection centrality (CoC), Closeness centrality (ClC): the larger the quotient is, the more stable the network and, the less the influence made by the drug.
T244 31392-31567 Sentence denotes Disturbance total score (DTS), Average length of shortest path (APL), : the larger the quotient is, the less stable the network and, the larger the influence made by the drug.
T245 31568-31599 Sentence denotes Negative control formula: BXTM.
T246 31600-31631 Sentence denotes Positive control formula: YDBF.
T247 31632-32047 Sentence denotes M3 (Fig. 8A), a specific compound in formulae MXSG, showed eight interactions with E protein [ion channel] including Pi-sigma, Pi-alkyl and Alkyl, which were connected with TYR 57, ALA 32, ILE 46 and PRO 54, etc.; additionally, M3 (Fig. 8B) showed five interactions with nsp13 [Helicase NCB site] including Unfavorable Donor-Donor, Pi-alkyl and Alkyl, which were connected with ASN 559, ARG 409, LEU 42 and PRO 406.
T248 32048-32496 Sentence denotes S1 (Fig. 8C), a specific compound in formulae SGMH, showed seven interactions with nsp13 [Helicase ADP site] including H-bond interactions, van der waals, Amide-Pi stacked and Pi-alkyl, which were connected with ALA 313, ASP 374, GLN 537 and SER 289, etc.; additionally, S1 (Fig. 8D) showed five interactions with PLpro including Pi-anion, Pi-Pi stacked, Pi-Pi T-shaped and Pi-alkyl, which were connected with TYR 264, ASP 164, TYR 268 and PRO 248.
T249 32497-32721 Sentence denotes X2 (Fig. 8E), a specific compound in formulae XCH, showed seven interactions with Mpro including H-bond interactions, Pi-Donor hydrogen bond and Pi-alkyl, which were connected with MET 165, GLU 166, LEU 141 and CYS 145, etc.
T250 32722-32967 Sentence denotes O2 (Fig. 8F), a specific compound in formulae Others, showed seven interactions with Mpro including H-bond interactions, Carbon hydrogen bond, Pi-anion, Pi-sulfur and Pi-alkyl, which were connected with MET 131, GLY 71, LEU 100 and CYS 115, etc.
T251 32968-33421 Sentence denotes MS1 (Fig. 9 A), a compound in formulae MXSG and SGMH, showed eleven interactions with N protein NCB site including H-bond interactions, Pi-Donor hydrogen bond, Pi-sigma, Pi-Pi stacked and Pi-alkyl, which were connected with SER 51, THR 109, ALA 50 and PRO 42, etc.; additionally, MS1 (Fig. 9B) showed five interactions with nsp14 [ExoN] including H-bond interactions and Pi-Pi stacked, which were connected with GLU 92, PHE 190, ASP 273 and VAL 91, etc.
T252 33422-33651 Sentence denotes MX16 (Fig. 9C), a compound in formulae MXSG and XCH, showed seven interactions with nsp15 [endoribonuclease] including H-bond interactions, Alkyl and Pi-alkyl, which were connected with PRO 343, VAL 275, LYS 344 and SER 293, etc.
T253 33652-34021 Sentence denotes SX1 (Fig. 9D), a compound in formulae SGMH and XCH, showed two interactions with nsp14 [N7-MTase] including Pi-Pi stacked and Pi-alkyl, which were connected with PHE 426; additionally, SX1 (Fig. 9E) showed five interactions with nsp15 [endoribonuclease] including H-bond interactions, Alkyl and Pi-alkyl, which were connected with LYS 344, LYS 289, VAL 291 and PRO 343.
T254 34022-34542 Sentence denotes WO1 (Fig. 9F), a compound in formulae WLS and Others, showed seven interactions with nsp16 [2′-O-MTase] including H-bond interactions, Carbon hydrogen bond, Pi-Pi T-shaped, Pi-alkyl and Pi-anion, which were connected with PHE 149, CYS 115, ASP 99 and SER 74, etc.; additionally, WO1 (Fig. 9G) showed seven interactions with nsp12 [RdRp without RNA] including H-bond interactions, Carbon hydrogen bond, Unfavorable Donor-Donor, Pi-cation and Pi-anion, which were connected with THR 556, ARG 553, ASP 623 and SER 682, etc.
T255 34543-34801 Sentence denotes XO1 (Fig. 9H), a compound in formulae XCH and Others, showed ten interactions with nsp12 [RdRp with RNA] including H-bond interactions, Pi-Donor hydrogen bond, Pi-Pi T-shaped and Pi-alkyl, which were connected with CYS 813, GLY 590, LYS 593 and ASP 865, etc.
T256 34802-34931 Sentence denotes Fig. 9 Schematic (3D and 2D) representation that molecular model of common compounds of the five formulae with COVID-19 proteins.
T257 34932-35193 Sentence denotes A: MS1 and N protein NCB site, B: MS1 and nsp14 [ExoN], C: MX16 and nsp15 [endoribonuclease], D: SX1 and nsp14 [N7-MTase], E: SX1 and nsp15 [endoribonuclease], F: WO1 and nsp16 [2′-O-MTase], G: WO1 and nsp12 [RdRp without RNA], H: XO1 and nsp12 [RdRp with RNA].
T258 35194-35288 Sentence denotes MS: MXSG and SGMH, MX: MXSG and XCH, SX: SGMH and XCH, WO: WLS and Others, XO: XCH and Others.
T259 35290-35359 Sentence denotes 3.7 ACE2 and CD147 expression across tissues and co-expression genes
T260 35360-35531 Sentence denotes Since 2019-nCov may enter other tissues and organs through ACE2 and CD147 binding, we firstly explored the expression and distribution of ACE2 and CD147 across 53 tissues.
T261 35532-35715 Sentence denotes Fig. 10 A showed that the 5 top expression tissues of ACE2 were terminal ileum, testis, visceral (omentum), left ventricle and kidney cortex, which are 3 fold change higher than lung.
T262 35716-35859 Sentence denotes And the 5 top expression tissues of CD147 were testis, visceral (omentum), left ventricle, aorta, atrial appendage and transformed fibroblasts.
T263 35860-36151 Sentence denotes Then, to further understand whether QFPD only targets pneumonia or 2019-nCov, we obtained 200 co-expression genes of ACE2, 200 co-expression genes of CD147, 470 pneumonia-associated proteins, 119 HCoV-associated host proteins, and 476 co-expression genes of ACE2 in colonic epithelial cells.
T264 36152-36382 Sentence denotes Fig. 10B displayed that QFPD had some common targets with these five sets, while specific 254 targets for QFPD, indicating other mechanisms of QFPD on COVID-19 in addition to 2019-nCov, pneumonia, ACE2 and CD147 related functions.
T265 36383-36456 Sentence denotes Fig. 10 ACE2 and CD147 expression across tissues and co-expression genes.
T266 36457-36459 Sentence denotes A:
T267 36460-36518 Sentence denotes Radar plot of ACE2 and CD147 expression across 53 tissues.
T268 36519-36576 Sentence denotes The expression values were converted to base-2 logarithm.
T269 36577-36635 Sentence denotes Red triangle and square mean the top 5 expression tissues.
T270 36636-36638 Sentence denotes B:
T271 36639-36864 Sentence denotes UpSet plot of proteins among QFPD, HCoV (Host_protein), pneumonia, ACE2 co-expression genes (ACE2_database), CD147 co-expression genes (CD147_database), and ACE2 co-expression genes in colonic epithelial cells (ACE2_colonic).
T272 36865-36963 Sentence denotes The horizontal bar graph at the bottom left shows the total number of proteins for each group set.
T273 36964-37053 Sentence denotes Circles and vertical lines in the x-axis mark the corresponding data sets being compared.
T274 37054-37273 Sentence denotes The vertical bar graph at the top quantitates the number of proteins in the comparisons. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
T275 37275-37374 Sentence denotes 3.8 Validation of drug positioning for QFPD against COVID-19 via the robustness of disease network
T276 37375-37509 Sentence denotes Firstly, the robustness of whole networks against formula attack was assessed to evaluate QFPD attack on the COVID-19 disease network.
T277 37510-37788 Sentence denotes 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.
T278 37789-37900 Sentence denotes In addition, SGMH, MSXG, and Others exerted higher disturbance score than the positive control (YDBF) Table 5 .
T279 37901-37992 Sentence denotes Fig. 11 Evaluation of the effect of QFPD on the robustness disturbance of COVID-19 network.
T280 37993-38098 Sentence denotes Blue normal distribution: drug attack on random networks as a null distribution for the permutation test.
T281 38099-38179 Sentence denotes Red vertical line: the disturbance rate of the drug to the real disease network.
T282 38180-38257 Sentence denotes Fist row: MXSG, second row: SGMH, third row: XCH, fourth row: WLS, fifth row:
T283 38258-38265 Sentence denotes Others.
T284 38266-38544 Sentence denotes 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.)
T285 38545-38625 Sentence denotes Table 5 Docking score between common ingredients of QFPD and 2019-nCov proteins.
T286 38626-38673 Sentence denotes Molecule MS1 MX16 MX17 MX8 MXO1 SO1 SX1 WO1 XO1
T287 38674-38730 Sentence denotes Main Protease −7.6 −7 −7.8 −7.8 −7.8 −7.2 −7.1 −7.4 −7.4
T288 38731-38794 Sentence denotes Papain-like protease −8 −8.2 −8.1 −8.1 −8.2 −8.2 −9.2 −8.7 −8.3
T289 38795-38849 Sentence denotes RdRp with RNA −8.6 −8 −7.9 −7.9 −8 −8.4 −8.2 −8.8 −9.5
T290 38850-38909 Sentence denotes RdRp without RNA −7.1 −6.8 −6.8 −6.8 −7 −7.1 −6.9 −7.5 −7.1
T291 38910-38972 Sentence denotes Helicase ADP site −6.2 −6.5 −6.3 −6.1 −6.2 −6.4 −6.8 −6.2 −6.8
T292 38973-39035 Sentence denotes Helicase NCB site −7.4 −7.1 −7.2 −7.2 −7.5 −7.5 −7.4 −7.6 −7.5
T293 39036-39090 Sentence denotes Nsp14(ExoN) −7.2 −6.6 −6.6 −6.7 −6.9 −7 −6.9 −7.1 −7.1
T294 39091-39151 Sentence denotes Nsp14(N7-MTase) −8.6 −8.3 −8.4 −8.3 −8.6 −8.3 −9.4 −8.7 −8.7
T295 39152-39220 Sentence denotes Nsp15(endoribonuclease) −6.2 −6.8 −6.4 −6.4 −6.3 −6.5 −6.8 −6.4 −6.6
T296 39221-39283 Sentence denotes Nsp16(2′-O-MTase) −8.1 −7.4 −7.6 −7.8 −7.8 −8.3 −7.7 −8.4 −8.2
T297 39284-39343 Sentence denotes N protein NCB site −8.1 −7.9 −8 −8 −7.6 −7.8 −7.5 −7.7 −7.9
T298 39344-39411 Sentence denotes E protein(ion channel) −6.4 −6.9 −7.2 −7.2 −6.9 −6.9 −7.9 −6.8 −6.8
T299 39412-39440 Sentence denotes M: MXSG, S: SGMH, X: XCH, O:
T300 39441-39448 Sentence denotes Others.
T301 39449-39583 Sentence denotes Next, to illustrate the mechanism of QFPD against COVID-19, a formula-attacked target-KEGG pathway network was constructed (Fig. 12 ).
T302 39584-39937 Sentence denotes 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.
T303 39938-39996 Sentence denotes Fig. 12 Disturbance analysis of QFPD for COVID-19 network.
T304 39997-39999 Sentence denotes A:
T305 40000-40052 Sentence denotes Venn diagram of the five formulae’ attacked targets.
T306 40053-40055 Sentence denotes B:
T307 40056-40184 Sentence denotes Formula-attacked target-KEGG pathway network; green square: formula, yellow diamond: attacked target, red circle: KEGG pathways.
T308 40185-40378 Sentence denotes 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.)
T309 40380-40393 Sentence denotes 4 Discussion
T310 40394-40484 Sentence denotes Novel coronavirus (2019-nCov) infection is characterized by lung and immune system damage.
T311 40485-40606 Sentence denotes Severe infection can lead to acute respiratory distress syndrome (ARDS) and septicemia, and eventually lead to death [2].
T312 40607-40691 Sentence denotes In addition, a number of patients presented multi-organ damage and dysfunction [28].
T313 40692-40774 Sentence denotes However, there are no specific drugs or vaccine for the treatment of the COVID-19.
T314 40775-40897 Sentence denotes This reason may partly be that a single targeted drug cannot cure a complex disease with complex biological networks [29].
T315 40898-41119 Sentence denotes Despite the lack of strong evidence-based medicine, TCM has a good potential to complement the medical service for COVID-19, including reverting radiological changes, and shortening fever duration and hospital stay. [30].
T316 41120-41265 Sentence denotes It is observed that the total effective rate of QFPD in the treatment of pneumonia patients infected by novel coronavirus is more than 90 % [31].
T317 41266-41457 Sentence denotes Therefore, we explored the mechanism of QFPD against COVID-19 by systems pharmacology, and provided a combination strategy to explore the functional units in QFPD from a holistic perspective.
T318 41458-41576 Sentence denotes To our knowledge, this is the first study to explore the mechanisms of QFPD for COVID based on intra-functional units.
T319 41577-41921 Sentence denotes In this study, GO enrichment analysis showed that the common GO terms of MSXG, SGMH, XCH, WLS and Others targets were significant enriched in oxidoreductase activity, lipid metabolic process, lipid binding, small molecule metabolic process, and homeostatic process etc., suggesting QFPD may exert anti-viral activity through metabolic function.
T320 41922-42138 Sentence denotes In agreement with these results, a recent research has found that lipid metabolic reprograming plays an important role in virus replication, which may be an appealing and applicable target for antiviral therapy [32].
T321 42139-42371 Sentence denotes KEGG analysis showed that in addition to lipid metabolism-related pathways, endocrine system pathways were also significantly enriched in more than four formulae, including PPAR signaling pathway and adipocytokine signaling pathway.
T322 42372-42604 Sentence denotes A recent study has showed that the host can exert anti-inflammatory functions to inhibit excessive inflammatory damage through PPAR signaling pathway after H1N1 infection, thus keeping homeostasis of metabolism and development [33].
T323 42605-42910 Sentence denotes In addition, other common terms were significant enriched in more than two formulae, such as immune system process, endoplasmic reticulum, cell-cell signaling, calcium signaling pathway, vascular smooth muscle contraction, inflammatory mediator regulation of TRP channels, cardiac muscle contraction, etc.
T324 42911-43113 Sentence denotes Therefore, the multi-pathway and multi-target results of our intra functional unit of QFPD not only showed a new useful method for studying TCM, but may demonstrate the rationality of TCM compatibility.
T325 43114-43177 Sentence denotes Moreover, TCMATCOV platform was used to validate these results.
T326 43178-43580 Sentence denotes Interestingly, all the five FUs of QFPD showed higher disturbance score than negative control (BXTM), indicating that MSXG, SGMH, XCH, WLS and Others may protect COVID-19 independently, and target 8 specifically expressed drug-attacked nodes (Cdc20, Ido1, Ifng, Il10, Il6, Ptger4, Spi1, Tnf) which were related to the bacterial and viral responses, cytokine, immune system, signaling transduction, etc.
T327 43581-43835 Sentence denotes Currently, a number of studies have showed that 2019-nCov can cause multiple organs dysfunction, including liver [34], pancreas [35], kidney [36], throat and rectum [37], which may be the reason that a wide distribution of ACE2 across these tissues [38].
T328 43836-44107 Sentence denotes In agreement with these results, we found that ACE2 was highly expressed in terminal ileum, testis, adipose visceral omentum, heart left ventricle, kidney cortex and thyroid, etc., and QFPD has only 15.33 % common targets with 2019-nCov, pneumonia and ACE2 related genes.
T329 44108-44217 Sentence denotes These results indicate that the effective treatment of QFPD for COVID-19 may be through a holistic treatment.
T330 44218-44500 Sentence denotes Moreover, TTD analysis further displayed that QFPD targets were significantly enriched in many COVID-19 related disease, such as chronic inflammatory diseases, asthma, inflammatory bowel disease, chronic obstructive pulmonary disease, intrahepatic cholestasis, chronic ileitis, etc.
T331 44501-44651 Sentence denotes It is known that ADMETox prediction is an important part in evaluating if a drug can be toxic or can be absorbed during drug development process [39].
T332 44652-44891 Sentence denotes In our study, ADMETox evaluation shows that 20 compounds passed the stringent lead-like criteria (250 ≤ MW≤350 & XLOGP ≤ 3.5 & Number of rotatable bonds≤7) [40] and in silico drug-likeness test, and showed high gastrointestinal absorption.
T333 44892-45069 Sentence denotes Moreover, predicted toxicity evaluation showed that the median lethal dose (LD50) of all these ingredients was above 1600 mg/kg, thus may suggesting safety and efficacy of QFPD.
T334 45070-45404 Sentence denotes Combined with molecular docking results, 4 specific ingredients (M3, S1, X2 and O2) and 5 common ingredients (MS1, MX16, SX1, WO1 and XO1) of QFPD might be promising leading compounds with good molecular docking score for 2019-nCov structure and non-structure proteins, revealing that QFPD treated COVID-19 by multi-component synergy.
T335 45405-45479 Sentence denotes However, these newly monomer components should provide a further research.
T336 45480-45594 Sentence denotes It has been reported that host cellular microRNAs (miRNAs) are involved in the regulation of virus infection [41].
T337 45595-45726 Sentence denotes A previous study discovered that significantly up-regulated MIR301 and down-regulated MIR183/130B were found in H1N1 patients [42].
T338 45727-45916 Sentence denotes Consistent with these results, we found that MIR183 and MIR130A/B/301 are related to four functional units of QFPD, indicating these microRNAs may exert anti−COVID-19 activity through QFPD.
T339 45917-46126 Sentence denotes In addition, CDKs have played a role in the efficient replication of various viruses, including human HIV-1, papillomaviruses, human cytomegalovirus (HCMV), herpes simplex virus (HSV) type 1 and HSV-2 [43,44].
T340 46127-46358 Sentence denotes In agreement with these results, we found that CDK7 was predicted to enriched in the five formulae, suggesting that QFPD may regulate replication of COVID-19 viruses via CDK7 mediated cell cycle and RNA polymerase II transcription.
T341 46359-46537 Sentence denotes Recently, a previous study showed that LXR known to regulate cholesterol homeostasis during inflammation were differentially regulated during H1N1 influenza virus infection [45].
T342 46538-46732 Sentence denotes Based on our results that LXR was associated with MSXG, SGMH, XCH, WLS targets, we speculated that QFPD can regulate metabolic and pro-inflammatory processes to counter COVID-19 virus infection.
T343 46733-46792 Sentence denotes In summary, QFPD is effective in the treatment of COVID-19.
T344 46793-46970 Sentence denotes However, some shortcomings in our study include lack of an in-depth study of predictive monomers and key targets and pathways, thus need further validation in vivo and in vitro.
T345 46971-47237 Sentence denotes And the TCMATCOV platform uses SARS disease network, which is different from the COVID-19 disease network, and COVID-19-related cytokines are related to severe COVID-19 disease, so the results of platform analysis more reflect the potential efficacy of severe stage.
T346 47238-47393 Sentence denotes Nevertheless, this study confirms that network pharmacology can help explore the mechanism of QFPD on the treatment of COVID-19 with time- and cost-saving.
T347 47394-47586 Sentence denotes Moreover, based on our new FUNP analysis, we reveal that QFPD treat COVID-19 by a holistic treatment and multi-component synergy, and are further demonstrated by formula perturbation analysis.
T348 47587-47738 Sentence denotes In addition, this study provides possible candidate monomers of QFPD and related miRNAs, kinases and TFs with potential therapeutic effect on COVID-19.
T349 47739-47856 Sentence denotes This will hopefully provide evidence and new insights for further researches on the treatment of COVID-19 using QFPD.
T350 47858-47878 Sentence denotes Author contributions
T351 47879-48315 Sentence denotes Conceiving the research, Jian Chen and Yong-bing Cao; Data curation, Jian Chen, Wen-jie Sun, and Zhi-qiang Liang; Funding acquisition, Jian Chen, Zhi-qiang Liang, Bing-yong Cao and Ye-min Cao; Investigation, Ling-San Hu, Jian-ru Wang, and Bing-yong Cao; Methodology, Yong-kui Wang, Jiang-wei Yang and Ye-min Cao; Resources, Ling-San Hu and Yong-kui Wang; Visualization, Jian-ru Wang, Jiang-wei Yang; Writing – original draft, Jian Chen.
T352 48317-48350 Sentence denotes Declaration of Competing Interest
T353 48351-48395 Sentence denotes The authors declare no conflict of interest.
T354 48397-48412 Sentence denotes Acknowledgement
T355 48413-49052 Sentence denotes This work was supported by the 10.13039/100007219Shanghai Natural Science Foundation (17ZR1427600), National Science and Technology Major Projects for "Major New Drugs Innovation and Development" (2018ZX09201008-002-091 and 2018ZX09201008-002-092), Three-year Action Plan of "strong and excellent Chinese Medicine" in Hongkou District (HGY-MGB-2018-01-01), Shanghai Science and Technology Support Project in Biomedicine Field (18401932900), Budgetary Projects of Shanghai University of Traditional Chinese Medicine (2019LK046), Special Clinical Research Project of Health Profession of Shanghai Municipal Commission of Health (20194Y0081).