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. 2022 Oct 7;7(41):36598–36610. doi: 10.1021/acsomega.2c04589

Dissection of the Active Ingredients and Potential Mechanism of Han-Shi-Yu-Fei-Decoction in Treating COVID-19 Based on In Vivo Substances Profiling and Clinical Symptom-Guided Network Pharmacology

Guangyang Jiao †, Xiangcheng Fan ‡,§, Yejian Wang ∥, Nan Weng ‡,⊥, Luolan Ouyang #, Haoqian Wang #, Sihan Pan #, Doudou Huang †, Jun Han , Feng Zhang ‡,§,∥,*, Wansheng Chen †,‡,§,*
PMCID: PMC9578366  PMID: 36268464

Abstract

graphic file with name ao2c04589_0007.jpg

This work was aimed to elucidate the mechanism of action of Han-Shi-Yu-Fei-decoction (HSYFD) for treating patients with mild coronavirus disease 2019 (COVID-19) based on clinical symptom-guided network pharmacology. Experimentally, an ultra-high performance liquid chromatography technique coupled with quadrupole time-of-flight mass spectrometry method was used to profile the chemical components and the absorbed prototype constituents in rat serum after its oral administration, and 11 out of 108 compounds were identified. Calculatingly, the disease targets of Han-Shi-Yu-Fei symptoms of COVID-19 were constructed through the TCMIP V2.0 database. The subsequent network pharmacology and molecular docking analysis explored the molecular mechanism of the absorbed prototype constituents in the treatment of COVID-19. A total of 42 HSYFD targets oriented by COVID-19 clinical symptom were obtained, with EGFR, TP53, TNF, JAK2, NR3C1, TH, COMT, and DRD2 as the core targets. Enriched pathway analysis yielded multiple COVID-19-related signaling pathways, such as the PI3K/AKT signaling pathway and JAK-STAT pathway. Molecular docking showed that the key compounds, such as 6-gingerol, 10-gingerol, and scopoletin, had high binding activity to the core targets like COMT, JAK2, and NR3C1. Our work also verified the feasibility of clinical symptom-guided network pharmacology analysis of chemical compounds, and provided a possible agreement between the points of views of traditional Chinese medicine and western medicine on the disease.

1. Introduction

Since the outbreak of COVID-19 in 2019, it has stayed a global public health concern that has not yet been effectively resolved, posing a serious threat to human health and economic development.1 Traditional Chinese medicine (TCM) has played a vital role in COVID-19 prevention and treatment. It has been listed in the “Diagnosis and Treatment Plan for COVID-19 Infection”, version 3, issued by the National Health Commission of the People’s Republic of China.2 Significantly, the combination of TCM and western medicine has led to significant achievements in the battle against COVID-19.3

It is well accepted that COVID-19 may evolve in four (overlapping) phases, from mild to moderate to severe to critical, which is staged by the clinical symptoms. Treatment of patients in mild and moderate stages is of utmost importance because about 14% of patients can progress to severe stage in only 1 week.4 Of note, both TCM and western medicine systems have a general agreement on this point.5 The typical clinical symptoms, including fever, cough, abnormality of the pharynx, fatigue, anergy, dyspnea, abnormality of the stomach, nausea, vomiting, diarrhea, abnormality of the tongue, and abnormality of the vasculature, were interpreted as “Han” and “Shi” that were blocked in the lung, according to the theory of TCM. Therefore, the typical recommended TCM recipe was “Han-Shi-Yu-Fei decoction (HSYFD)”. It consists of Atractylodis rhizoma [AR; Atractylodes lancea (Thunb.) DC.], Citri reticulatae pericarpium (CRP; Citrus reticulata Blanco), Magnoliae officinalis cortex (MOC; Magnolia officinalis Rehd. et Wils.), Pogostemonis Herba [PH; Pogostemon cablin (Blanco) Benth.], Tsaoko Fructus (TF; Amomum tsao-ko Crevost et Lemaire), Ephedrae Herba (EH; Ephedra sinica Stapf), Notopterygii rhizoma et Radix (NRR; Notopterygium incisum Ting ex H.T. Chang), Arecae semen (AS; Areca catechu L.), and Zingiberis rhizoma Recens (ZRR; Zingiber officinale Rosc.).6 However, its active compounds and therapeutic mechanisms have not been studied yet.

According to the current network of pharmacology research and a few in vitro experiments, the mechanism of TCM in COVID-19 is a multi-component, multi-target, and multi-pathway, which exhibits the functions of combating viral infections, immune regulation, amelioration of lung injury and fibrosis, and protection of target organs.7,8 However, most of the network pharmacology research studies were guided by the disease targets.9 As the COVID-19 patients were staged by the clinical symptoms, which were associated with the progression from mild to moderate COVID-19 illness to severe or critical status, it is an effective way to force mechanism study by the disease symptom-guided network pharmacology.

In this study, an ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC–Q-TOF-MS) method was used to identify the chemical components of HSYFD in vitro and then discriminate the blood-absorbing constituents, which were involved in the subsequent network pharmacology analysis and molecular docking techniques (Figure 1).10,11 This strategy, based on a UHPLC–Q-TOF-MS method combined with network pharmacology, can decrease false-positive results for the TCM which should be orally administered and could be widely applied to discover phytochemical or biomolecular evidence with distinct potential functional basis. Our work provides meaningful data for further pharmacological study of HSYFD in the treatment of COVID-19.

Figure 1.

Figure 1

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Whole framework of this study.

2. Results

2.1. Optimization of UHPLC–Q-TOF-MS Conditions

The separation of the chemical constituents was performed on a Waters ACQUITY UPLC BEH C18 column (2.1 × 100 mm, 1.7 μm) by gradient elution with a mobile phase (phase A: 0.1% aqueous formic acid solution and phase B: acetonitrile solution).12,13 The chromatographic peaks were well separated and distributed in the total ion chromatogram (TIC) when the elution time was set at 30 min.

2.2. Identification of Compounds in HSYFD

The TICs of HSYFD in both positive and negative modes are shown in Figure 2. This was the first step to construct an in-house compound database 1.0 (HSYFD) by combining the compound information. The available information including the chemical name, formula, and accurate molecular weight, by searching the reference databases (such as PubMed, SciFinder, Web of Science, and CNKI), and generated the two-dimensional data (m/z-compounds) for the chemical compounds from all the herbs from HSYFD. Second, compounds were characterized by the systematically matched information in Agilent MassHunter Qualitative Analysis 10.0 software by the function “find by formula”. An average mass error of adduct and isotopes 10 ppm was set in the criterion. After automatic identification, the MS FINDER 3.5.2 software, HMDB 5.0, and MassBank databases were used to confirm the characterized chemical components by checking the fragment structures. Detailed compound information is summarized in Table 1. A total of 108 chromatographic peaks were identified, of which 65 compositions were found in the positive mode, 37 compositions were detected in the negative mode, and 6 compositions were found in both the positive and negative modes.

Figure 2.

Figure 2

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Extract ion chromatograms of HSYFD. (A) Positive mode and (B) negative mode.

Table 1. Identification of Compounds in HSYFD by UHPLC–Q-TOF-MSb.

no. RT (min) mode average m/z adduct type MS/MS spectrum error (ppm) formula compound category source
1 0.868 ESI– 154.0616 [M – H]− 137.0343 –3.50 C6H9N3O2 histidine amino acids AS
2 0.868 ESI– 173.1042 [M – H]− 131.0798 –2.18 C6H14N4O2 arginine amino acids AS
3 0.936 ESI– 245.0435 [M – H]− 215.0329 –4.47 C13H10O5 isopimpinellin coumarins NRR
4 1.059 ESI+ 118.0862 [M + H]+ 100.0450 –0.26 C5H11NO2 valine amino acids AS
5 1.286 ESI+ 182.0826 [M + H]+ 165.0619, 136.0723, 123.0544 8.54 C9H11NO3 tyrosine amino acids AS
6 1.434 ESI+ 132.102 [M + H]+ 115.0422 1.04 C6H13NO2 leucine amino acids AS
7 1.582 ESI+ 166.1229 [M + H]+ 152.108, 132.1013, 117.0748 1.30 C10H15NO pseudoephedrine alkaloids EH
8 2.188 ESI- 164.0714 [M – H]− 164.0174, 147.0510 –1.88 C9H11NO2 l-phenylalanine amino acids AR
9 2.416 ESI– 167.0348 [M – H]− 123.0487 –1.60 C8H8O4 vanillic acid phenols NRR, PH, MOC, AS, AR, CRP, TF
10 2.906 ESI– 153.0191 [M – H]− 109.0302 –1.89 C7H6O4 gentisic acid phenols TF
11 3.449 ESI+ 152.1073 [M + H]+ 134.0970, 117.0701 2.05 C9H13NO norephedrine alkaloids EH
12 4.169 ESI– 203.0832 [M – H]− 142.0698, 116.0506 2.45 C11H12N2O2 D-tryptophan amino acids AR
13 5.202 ESI+ 180.1389 [M + H]+ 162.1280, 117.0721 3.12 C11H17NO methylephedrine alkaloids EH
14 5.214 ESI+ 135.0808 [M + H]+ 119.0816 1.06 C9H10O chavicol phenols MOC
15 5.365 ESI– 188.0354 [M – H]− 144.0439, 131.0366 –0.84 C10H7NO3 kynurenic acid amino acids EH
16 5.373 ESI+ 166.1227 [M + H]+ 166.1226, 148.1117 0.20 C10H15NO ephedrine alkaloids EH
17 5.612 ESI+ 192.1023 [M + H]+ 146.0515, 133.1011, 105.0667 1.43 C11H13NO2 ephedroxane alkaloids EH
18 5.817 ESI+ 139.0392 [M + H]+ 139.0386, 121.0506 1.45 C7H6O3 4-hydroxybenzoic acid phenols AS, TF
19 5.840 ESI+ 195.0655 [M + H]+ 177.0546,145.0513 3.08 C10H10O4 ferulic acid phenylpropanoids AS, EH
20 5.977 ESI+ 233.1535 [M + H]+ 233.1535, 215.142, 187.1429 0.17 C15H20O2 atractylenolide II sesquiterpenoids AR
21 6.227 ESI+ 355.1021 [M + H]+ 193.087, 163.038 –0.59 C16H18O9 chlorogenic acid caffeoylquinic acids NRR, EH, MOC
22 6.617 ESI– 179.0348 [M – H]− 135.0446 –1.26 C9H8O4 caffeic acid phenylpropanoids MOC, EH, CRP
23 7.015 ESI– 369.0827 [M – H]− 207.0209 0.06 C16H18O10 fraxin coumarins NRR
24 7.539 ESI– 153.0193 [M – H]− 135.0438, 109.0305 –0.35 C7H6O4 protocatechuic acid hydroxybenzoic acid derivatives TF, AS
25 7.653 ESI– 289.0716 [M – H]− 151.0384, 137.0238, 121.0239, 109.0290 –0.40 C15H14O6 epicatechin flavonoids EH, AS, TF
  7.718 ESI+ 291.0868 [M + H]+ 123.1151 2.65 C15H14O6 epicatechin    
26 7.866 ESI+ 149.0606 [M + H]+ 131.0482, 103.0549 4.83 C9H8O2 cinnamic acid phenylpropanoids EH
27 8.017 ESI– 163.04 [M – H]− 163.0405, 145.0258, 119.0363 –1.47 C9H8O3 p-coumaric acid phenols MOC, CRP, NRR
28 8.049 ESI+ 223.0603 [M + H]+ 177.0563, 163.0385, 151.0368, 121.0507 1.02 C11H10O5 isofraxidin coumarins NRR
29 8.071 ESI+ 595.1652 [M + H]+ 287.1398, 255.0938 –0.85 C27H30O15 lonicerin flavonoids CRP
30 8.120 ESI– 151.0399 [M – H]− 151.0399, 135.0448, 119.0384 –1.03 C8H8O3 vanillin phenols EH
31 8.174 ESI+ 342.1712 [M]+ 342.171, 297.1169 3.20 C20H23NO4+ magnoflorine alkaloids MOC
32 8.584 ESI+ 137.1323 [M + H]+ 109.0993 –1.70 C10H16 camphene monoterpenoids PH
33 8.652 ESI+ 765.2214 [M + Na]+ 581.1885, 435.1274 –0.09 C33H42O19 narirutin-4′-glucoside flavonoid-7-o-glycosides CRP
34 8.709 ESI+ 330.1704 [M + H]+ 330.1706, 192.113 1.29 C19H23NO4 reticuline alkaloids MOC
35 8.860 ESI– 623.1987 [M – H]− 461.1522, 135.0454 0.65 C29H36O15 acteoside steroids MOC, PH
36 9.235 ESI– 191.0349 [M – H]− 175.0375, 161.0275, 147.0442 0.43 C10H8O4 scopoletin coumarins NRR
  9.301 ESI+ 193.0501 [M + H]+ 163.0572, 149.0595 3.10 C10H8O4 scopoletin    
37 9.608 ESI+ 197.117 [M + H]+ 179.1049, 133.1011 0.88 C11H16O3 loliolide benzofurans PH
38 9.608 ESI+ 153.1271 [M + H]+ 153.1273, 135.117, 121.051, 107.0855 –0.75 C10H16O citral monoterpenoids CRP
39 9.645 ESI– 609.1458 [M – H]− 301.0360 0.34 C27H30O16 rutin flavonoids TF, CRP
40 9.656 ESI– 577.1563 [M – H]− 431.0955, 269.0382 0.11 C27H30O14 rhoifolin flavonoids CRP
41 9.782 ESI– 595.1651 [M – H]− 287.0561 –2.37 C27H32O15 neoeriocitrin flavonones CRP
42 9.950 ESI+ 356.1855 [M + H]+ 325.1066 –0.57 C21H25NO4 glaucine quinolines MOC
43 10.007 ESI+ 223.1329 [M + H]+ 205.1200, 187.0773, 163.0657 0.07 C13H18O3 dehydrovomifoliol sesquiterpenoids MOC
44 10.075 ESI+ 268.134 [M + H]+ 251.1082 2.87 C17H17NO2 asimilobine alkaloids MOC
45 10.100 ESI– 447.0937 [M – H]− 285.0406 1.48 C21H20O11 isoorientin flavonoid c-glycosides CRP
46 10.510 ESI– 453.141 [M + HCOO]- 227.071 0.50 C20H24O9 nodakenin coumarins NRR
47 10.727 ESI– 463.0885 [M – H]− 300.0224, 151.0375 1.07 C21H20O12 quercetin-3-galactoside flavonoid-3-o-glycosides EH
48 10.806 ESI– 579.172 [M – H]− 459.1124, 271.0623 –0.18 C27H32O14 naringin flavonones CRP
49 10.895 ESI+ 209.0815 [M + H]+ 177.0532, 149.1006, 121.0507 3.51 C11H12O4 sinapic aldehyde phenols MOC
50a 11.501 ESI– 609.1827 [M – H]− 609.1822, 325.0666, 301.0739, 0.17 C28H34O15 hesperidin flavonones PH, EH, CRP
  11.544 ESI+ 611.1975 [M + H]+ 465.1393, 303.0863, 177.0554 0.64 C28H34O15 hesperidin    
51 12.468 ESI– 269.0464 [M – H]− 269.0464, 117.0246 2.70 C15H10O5 apigenin flavonoids PH, CRP, EH
52 12.648 ESI+ 276.0659 [M + H]+ 248.0742 1.97 C17H9NO3 liriodenine alkaloids MOC
53 12.659 ESI+ 155.1424 [M + H]+ 137.1323, 107.0852 –4.65 C10H18O α-terpineol monoterpenoids EH
54 12.730 ESI– 295.0982 [M – H]− 267.0660, 151.0406 –1.56 C18H16O4 obovatal neolignans MOC
55 12.750 ESI+ 266.1184 [M + H]+ 249.0983, 236.1679 3.04 C17H15NO2 anonaine alkaloids MOC
56 12.898 ESI+ 280.1341 [M + H]+ 249.0909 2.94 C18H17NO2 roemerine alkaloids MOC
57 13.391 ESI– 301.0355 [M – H]− 271.0246, 151.0048, 0.61 C15H10O7 quercetin flavonoids EH, AS, TF
58 13.914 ESI– 593.1874 [M – H]− 285.0774 0.34 C28H34O14 poncirin flavonones CRP
59 14.117 ESI+ 247.0974 [M + H]+ 177.0551, 147.0453 3.78 C14H14O4 columbianetin coumarins NRR
60 14.301 ESI– 491.1195 [M + HCOO]- 283.0613, 133.0309 –0.30 C22H22O10 acacetin-7-glucoside flavonoid-7-O-glycosides PH
  14.356 ESI+ 447.1304 [M + H]+ 285.0746 3.82 C22H22O10 acacetin-7-glucoside    
61 14.857 ESI+ 151.1117 [M + H]+ 151.1116, 133.1028, 107.0849 1.05 C10H14O 2-(4-methylphenyl)propan-2-ol phenylpropanes MOC
62 14.893 ESI– 726.3825 [M – H]− 708.3709, 696.3708 –1.45 C36H53N7O9 citrusin III alkaloids CRP
63 15.759 ESI– 329.0666 [M – H]− 313.0718, 283.0612, 253.0486 –0.49 C17H14O7 ombuin flavonoids PH
64 16.578 ESI– 359.0771 [M – H]− 283.0635 –0.53 C16H12O6 diosmetin flavonoids NRR
65 16.951 ESI+ 353.2293 [M + Na]+ 261.1767 –2.11 C18H34O5 tianshic acid fatty acids PH
66 17.031 ESI+ 251.1983 [M + Na]+ 229.1246, 209.1115, 121.0512 1.49 C14H28O2 myristic acid fatty acids AS
67 17.691 ESI+ 231.1022 [M + H]+ 175.0391, 147.1164 2.80 C14H14O3 osthenol 7-hydroxycoumarins NRR
68 17.762 ESI– 279.1029 [M – H]− 239.0726, 133.0188 0.91 C18H16O3 magnaldehyde B neolignans MOC
69 17.794 ESI+ 343.1185 [M + H]+ 287.0955, 163.0733 1.97 C19H18O6 4′,5,7,8-tetramethoxyflavone flavonoids CRP
70 17.808 ESI– 283.0618 [M – H]− 283.0619, 268.0355 1.80 C16H12O5 wogonin flavonoids AR
71 17.999 ESI+ 205.1956 [M + H]+ 177.0919, 163.0751,149.1320 2.44 C15H24 α-bulnesene sesquiterpenoids PH
72 18.092 ESI– 300.0878 [M – H]− 270.0464 1.13 C16H15NO5 citpressine I acridones CRP
73 18.195 ESI– 285.0772 [M – H]− 201.0217 1.73 C16H14O5 (R)-pabulenol psoralens NRR
  18.386 ESI+ 287.092 [M + H]+ 215.0699, 203.0333 2.37 C16H14O5 (R)-pabulenol    
74 18.434 ESI– 343.0831 [M – H]− 283.0617 1.72 C18H16O7 pachypodol flavonoids PH
75 18.640 ESI+ 425.121 [M + Na]+ 403.1399, 375.1068, 287.0838 3.76 C21H22O8 nobiletin flavonoids CRP
76 18.867 ESI– 311.129 [M + HCOO]- 249.0932, 223.0723 0.97 C18H18O2 honokiol lignans MOC
77 18.898 ESI+ 221.1901 [M + H]+ 203.0343, 177.0913, 163.0734, 107.0848 0.53 C15H24O (−)-caryophyllene oxide sesquiterpenoids MOC
78 18.955 ESI+ 312.2175 [M + NH4]+ 259.1674, 163.0732, 137.0595 3.34 C17H26O4 6-gingerol gingerols ZRR
79a 18.960 ESI+ 277.181 [M + H]+ 119.0849, 107.0847 4.53 C17H24O3 6-shogaol phenylacetaldehydes ZRR
80 19.126 ESI+ 315.0872 [M + H]+ 300.2190, 163.1471 3.20 C17H14O6 kumatakenin flavonoids PH
81 19.319 ESI+ 274.2744 [M + NH4]+ 211.0343 1.48 C16H32O2 palmitic acid fatty acids AR
82 19.661 ESI+ 299.1652 [M + H]+ 217.0758, 163.0728 2.74 C19H22O3 ostruthin coumarins NRR
83 19.706 ESI+ 395.1111 [M + Na]+ 343.0986 4.04 C20H20O7 tangeretin flavonoids CRP
84 20.036 ESI+ 287.0925 [M + H]+ 203.0346 3.94 C16H14O5 pabulenol psoralens NRR
85a 20.720 ESI– 353.1397 [M – H]− 201.0195 0.41 C21H22O5 notopterol coumarins NRR
86 20.754 ESI+ 203.0346 [M + H]+ 159.0803, 147.0402, 133.0973 3.42 C11H6O4 xanthotoxol 8-hydroxypsoralens NRR
87 20.754 ESI+ 255.0658 [M + H]+ 255.0659, 121.0512 2.62 C15H10O4 chrysophanol anthraquinones AS
88 21.596 ESI+ 229.0865 [M + H]+ 135.0478, 119.0823 2.62 C14H12O3 trans-resveratrol phenols AS
89 21.642 ESI+ 137.0597 [M + H]+ 137.0597, 109.0648 0.78 C8H8O2 4-methoxybenzaldehyde benzoyl derivatives TF
90 21.667 ESI– 201.0195 [M – H]− 177.0194, 133.024, 117.029 0.10 C11H6O4 bergaptol 5-hydroxypsoralens NRR
91 21.667 ESI– 269.0819 [M – H]− 201.0194 –0.3 C16H14O4 imperatorin psoralens NRR
  21.710 ESI+ 293.0792 [M + Na]+ 203.0349, 175.0397 3.70 C16H14O4 imperatorin    
92 21.824 ESI+ 137.1324 [M + H]+ 137.0567, 121.0509, 109.0652 –1.05 C10H16 terpinolene monoterpenes EH
93 22.214 ESI– 315.2539 [M + HCOO]- 269.0765, 251.1129, 225.0919 –0.87 C17H34O2 heptadecanoic acid fatty acids AS
94 22.632 ESI+ 249.149 [M + H]+ 231.1382, 203.1778 2.46 C15H20O3 atractylenolide III sesquiterpenoids AR
95 22.678 ESI+ 245.1903 [M + Na]+ 209.1785, 195.1726, 8.99 C15H26O hinesol sesquiterpenoids AR
96 22.769 ESI+ 285.0767 [M + H]+ 239.1099, 135.0434 2.66 C16H12O5 physcion anthraquinones AS
97 22.837 ESI+ 293.2107 [M + H]+ 275.1944, 137.0578 –2.04 C18H28O3 7-paradol paradols ZRR
98 23.224 ESI+ 231.1387 [M + H]+ 231.1387, 213.1356, 185.1325, 105.064 3.44 C15H18O2 atractylenolide I sesquiterpenoids AR
99 23.258 ESI+ 279.2324 [M + H]+ 261.1824, 233.0831 1.70 C18H30O2 linolenic acid fatty acids AS
100 23.725 ESI+ 203.1799 [M + H]+ 161.1316, 119.0852, 105.0696 2.05 C15H22 curcumene sesquiterpenoids AR
101 23.896 ESI+ 351.2527 [M + H]+ 177.0906, 145.0663, 137.0601 –0.91 C21H34O4 10-gingerol gingerols ZRR
102 23.930 ESI+ 305.2112 [M + H]+ 137.0598 0.09 C19H28O3 8-shogaol shogaols ZRR
103 25.934 ESI+ 329.1751 [M + H]+ 193.0497, 163.0758 1.22 C20H24O4 5-geranyloxy-7-methoxycoumarin terpene lactones NRR
104 26.935 ESI+ 305.2463 [M + Na]+ 135.1154, 121.0524, 107.0824 6.91 C18H34O2 oleic acid fatty acids AS
105 28.065 ESI– 487.3214 [M – H]− 279.0956 –1.11 C33H44O3 eudesmagnolol neolignans MOC
106 28.689 ESI+ 527.3136 [M + Na]+ 135.1176 1.98 C33H44O4 eudesobovatol A neolignans MOC
107 28.689 ESI+ 205.1952 [M + H]+ 205.1955, 149.133, 123.1162, 109.1006 0.47 C15H24 farnesene sesquiterpenoids EH
108 28.928 ESI+ 379.2845 [M + H]+ 343.2225, 137.0608 0.97 C23H38O4 12-gingerol gingerols ZRR
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a

The results were identified by the standards.

b

MOC: Magnoliae Officinalis Cortex; EH: Ephedrae Herba; TF: Tsaoko Fructus; AR: Atractylodis Rhizoma; PH: Pogostemonis Herba; ZRR: Zingiberis Rhizoma Recens; CRP: Citri Reticulatae Pericarpium; AS: Arecae Semen; NRR: Notopterygii Rhizoma et Radix.

The structural types of these compounds were mainly flavonoids, sesquiterpenoids, amino acids, and phenylpropanoids. Among the constituents, 9 compounds were from AR, 13 compounds were from CRP, 17 compounds were from MOC, 2 compounds were from TF, 12 compounds were from EH, 16 compounds were from NRR, 6 compounds were from ZRR, 12 compounds were from AS, and 8 compounds were from PH. 13 compounds were common compositions of multiple medicinal materials, such as both AS and EH contain ferulic acid.

2.3. Analysis of Prototype Constituents of HSYFD in Rat Serum

As 108 compounds were found from database 1.0, the retention times of those compounds were added in the library list, and therefore generated the three-dimensional data set (retention time-m/z-compounds) in Personal Compound Database Library (PCDL), which certainly was the database 2.0.14−16 Normally, the method criterion for retention time was 0.25 min, and the average mass error of adduct and isotopes was 10 ppm. The rat serum was analyzed by the same UHPLC–Q-TOF-MS method, and therefore the absorbed prototype compounds were screened out by quick-matching the peaks in the database 2.0 using the Agilent MassHunter Qualitative Analysis 10.0 software.

Eleven chromatographic peaks were identified (Table 2, Figure 3). Among the constituents, hinesol was from AR, 10-gingerol and 6-gingerol were from ZRR, scopoletin was from NRR, anonaine was from MOC, loliolide and kumatakenin were from PH, norephedrine was from EH, histidine was from AS, p-coumaric acid was from MOC, CRP, and NRR, and 4-hydroxybenzoic acid was from TF and AS.

Table 2. Identification of Prototype Constituents of HSYFD in Rat Serum by UHPLC–Q-TOF-MSa.

no. tR (min) identification average m/z error (ppm) adduct type formula source
1 0.759 histidine 154.0606 –0.21 [M-H]- C6H9N3O2 AS
2 3.658 norephedrine 152.1059 –6.3 [M + H]+ C9H13NO EH
3 6.058 4-hydroxybenzoic acid 139.0398 1.54 [M + H]+ C7H6O3 TF, AS
4 8.114 p-coumaric acid 209.0454 –5.94 [M-H]- C9H8O3 MOC, CRP, NRR
5 9.211 scopoletin 193.0507 3.10 [M + H]+ C10H8O4 NRR
6 9.574 loliolide 197.1171 –0.98 [M + H]+ C11H16O3 PH
7 12.660 anonaine 266.1179 0.55 [M + H]+ C17H15NO2 MOC
8 18.813 6-gingerol 293.1740 0.57 [M-H]- C17H26O4 ZRR
9 19.024 kumatakenin 315.0854 –3.48 [M + H]+ C17H14O6 PH
10 22.532 hinesol 223.2051 3.04 [M + H]+ C15H26O AR
11 24.013 10-gingerol 373.2312 –2.81 [M + Na]+ C21H34O4 ZRR
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a

MOC: Magnoliae officinalis cortex; EH: Ephedrae Herba; TF: Tsaoko fructus; AR: Atractylodis rhizoma; PH: Pogostemonis Herba; ZRR: Zingiberis rhizoma Recens; CRP: Citri reticulatae pericarpium; AS: Arecae semen; NRR: Notopterygii rhizoma et Radix.

Figure 3.

Figure 3

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Extract ion chromatograms of HSYFD in the serum of rats. (A) Positive mode and (B) negative mode.

2.4. Network Pharmacology Analysis

2.4.1. Potential Targets of the Active Ingredient of HSYFD

A total of 422 putative targets of the 11 identified prototype constituents of HSYFD were obtained from the databases, and 704 potential targets were obtained by searching the genes related to Han-Shi-Yu-Fei symptoms of COVID-19 in the TCMIP V2.0. There were 48 overlapping targets from the compound-related targets and Han-Shi-Yu-Fei-related targets (Figure 4A). By constructing a protein–protein interaction (PPI) network for the abovementioned targets, it was found that a total of 42 targets interacted, forming a complex interlaced network. Among them, the betweenness centrality, closeness centrality, and degree of EGFR, TP53, TNF, JAK2, NR3C1, TH, COMT, and DRD2 were all higher than the average and were considered to be the core targets (Figure 4B, Table 3). To establish the relationship of herbs, compounds, and targets, we constructed a network of them. As shown in Figure 4C, the network consisted of 61 nodes and 84 edges, and the active ingredients of HSYFD correspond to multiple targets, and one target also corresponds to multiple active compounds; among them, 10-gingerol corresponds to 17 targets, 6-gingerol corresponds to 15 targets, both kumatakenin and anonaine correspond to 10 targets, they were the components with the most associated targets.

Figure 4.

Figure 4

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Therapeutic network of HSYFD. (A) Analysis of predicted active ingredients–disease target genes among herbs from HSYFD and COVID-19. (B) Protein–protein network of core target genes. (C) The herb–constituent–target network diagram of HSYFD in the treatment of COVID-19. The central circles represent the herbs, green represents the absorbed constituent, and the outer yellow circles represent the targets. (D) GO function analysis of targets of HSYFD against COVID-19. Blue represents the biological process, orange represents the molecular function, and green represents the cellular component.

Table 3. Core Targets in the PPI Network.
gene name protein name degree value betweenness centrality closeness centrality
EGFR epidermal growth factor receptor 19 0.110916 0.569444
TP53 cellular tumor antigen p53 19 0.112516 0.525641
TNF tumor necrosis factor 17 0.161021 0.539474
JAK2 tyrosine–protein kinase JAK2 16 0.057006 0.488095
NR3C1 glucocorticoid receptor 14 0.267501 0.569444
TH tyrosine 3-monooxygenase 10 0.115960 0.506173
COMT catechol O-methyltransferase 10 0.098256 0.427083
DRD2 D(2) dopamine receptor 8 0.041807 0.460674
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2.4.2. GO and KEGG Analyses of Potential Targets of the Active Ingredient of HSYFD

To probe the mechanisms of HSYFD in the treatment of mild stage of COVID-19, 42 targets were enriched by GO functional enrichment and KEGG pathway enrichment analyses. A total of 988 GO teams with a p-value < 0.001 were enriched, including 851 biological processes, 64 molecular functions, and 73 cellular components (Figure 4D). In detail, the biological process category mainly involved cellular process, biological regulation, and response to stimuli. Molecular function enrichment results primarily included binding, catalytic activity, and molecular transducer activity. In the cellular component category, targets were considered to be enriched in cell, cell part, and membrane. Multisteps were reported in the SARS-CoV-2 entry process. Specifically, in the steps that fusion between viral and cellular membranes, the viral RNA was released into the host cell cytoplasm for uncoating and replication.17 GO analysis suggested that the therapeutic effect of HSYFD on COVID-19 may be attributed to its disruption of the interaction between viral and host cellular membranes.

Similarly, KEGG signaling pathways (P < 0.01) included multiple pathways that had been shown to be associated with COVID-19 (Table 4). For instance, both MAPK and PI3K/AKT signaling pathways contain multiple core targets (TNF, TP53, EGFR, and JAK2). It was reported that the MAPK pathway could regulate many cellular processes and were essential for immune cell function,18 and the PI3K/AKT signaling pathway was associated with the activation of both CD147 and furin, which was also involved in the endocytosis of SARS-CoV-2.19 Additionally, the process of virus invading cells was reported to cause changes in erbB, HIF-1, and mTOR pathways by the integrative proteo-transcriptomics analysis of Huh7 cells infected with SARS-CoV-2.20 Moreover, SARS-CoV-2 could trigger inflammation through the JAK-STAT pathway, leading to the development of cytokine storms in cells such as lung cells and endothelial cells, causing lung injury.21

Table 4. 20 Signaling Pathways Related to COVID-19.
pathway KEGG_class genes P value
MAPK signaling pathway signal transduction INSR, BRAF, KIT, TNF, MET, TP53, PRKACA, EGFR 0.000097200
Rap1 signaling pathway signal transduction INSR, DRD2, BRAF, KIT, MET, EGFR, PIK3CA 0.000102320
PI3K-Akt signaling pathway signal transduction INSR, TLR4, JAK2, KIT, JAK3, MET, TP53, EGFR, PIK3CA 0.000251609
HIF-1 signaling pathway signal transduction INSR, TLR4, EGFR, STAT3, PIK3CA 0.000296533
taste transduction sensory system HTR1A, PRKACA, HTR3A, HTR1D 0.000644398
cAMP signaling pathway signal transduction DRD2, BRAF, HTR1A, PRKACA, PIK3CA, HTR1D 0.000714311
ErbB signaling pathway signal transduction ABL1, BRAF, EGFR, PIK3CA 0.000880997
Necroptosis cell growth and death TLR4, JAK2, TNF, JAK3, STAT3 0.001287180
Jak-STAT signaling pathway signal transduction JAK2, JAK3, EGFR, STAT3, PIK3CA 0.001430151
neuroactive ligand–receptor interaction signaling molecules and interaction AVPR2, DRD2, OPRM1, NR3C1, HTR1A, OPRD1, HTR1D 0.001489206
AGE-RAGE signaling pathway in diabetic complications endocrine and metabolic diseases JAK2, TNF, STAT3, PIK3CA 0.001583736
type II diabetes mellitus endocrine and metabolic diseases INSR, TNF, PIK3CA 0.001859059
Th17 cell differentiation immune system JAK2, JAK3, STAT3, LCK 0.002226016
insulin resistance endocrine and metabolic diseases INSR, TNF, STAT3, PIK3CA 0.002298795
sphingolipid signaling pathway signal transduction TNF, TP53, PIK3CA, OPRD1 0.003210978
phenylalanine metabolism amino acid metabolism DDC, MIF 0.003455026
inflammatory bowel disease (IBD) immune diseases TLR4, TNF, STAT3 0.004849935
insulin signaling pathway endocrine system INSR, BRAF, PRKACA, PIK3CA 0.005453038
Parkinson disease neurodegenerative diseases SLC18A2, DRD2, TH, PRKACA 0.006891435
mTOR signaling pathway signal transduction INSR, BRAF, TNF, PIK3CA 0.008208998
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2.5. Molecular Docking Results

The binding activities of these core targets and the core compounds were preliminarily verified by molecular docking technology.22 Results showed that the binding energies of almost all core targets to the molecules less than −5.0 kcal/mol (Figure 5). For example, the binding energies of COMT, JAK2, NR3C1, and TP53 to 6-gingerol were −5.8, −6.6, −6.7, and −5.8 kcal/mol, indicating that they displayed good binding activities, which was largely consistent with the previous compound-target result by network pharmacology analysis.

Figure 5.

Figure 5

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Molecular docking results. (A) COMT with scopoletin; (B) COMT with 6-gingerol; (C) DRD2 with anonaine; (D) DRD2 with norephedrine; (E) EGFR with kumatakenin; (F) JAK2 with 10-gingerol; (G) JAK2 with 6-gingerol; (H) NR3C1 with 6-gingerol; (I) NR3C1 with 10-gingerol; (J) NR3C1 with hinesol; (K) TNF with 10-gingerol; (L) TP53 with 6-gingerol.

3. Discussion

For orally administrated TCM recipe, systematic identification of the blood-absorbing compounds is critical to understanding its pharmacodynamic material basis and the therapeutic mechanism.23 Therefore, first, a total of 108 components were identified from HSYFD by the UHPLC–Q-TOF-MS technique. The qualitative analysis characterization compounds mainly consisted of flavonoids, sesquiterpenoids, amino acids, and phenylpropanoids. Next, a total of 11 prototype components were identified from the rat serum after oral administration of HSYFD, which could be recognized as the potential material basis for the efficacy of HSYFD. In particular, kumatakenin from PH showed good inhibitory activity against SARS-CoV-2 replication in Vero E6 and Calu-3 cells, whose inhibitory effects were even better than those of lopinavir/ritonavir and chloroquine.24 In addition, 10-gingerol and 6-gingerol, two key compounds based on degree ranking in herb–constituent–target network analysis, showed anti-inflammatory, immune regulation, and anti-nausea activities.25 In some situations, the elevated inflammatory markers were also identified as risk factors for psychoticism symptoms, which could induce depression in COVID-19 patients.26,27 Moreover, scopoletin from NRR promotes glutamatergic modulating effects and could regulate depression by increasing synaptic plasticity in prefrontal regions.28

Although COVID-19 was diagnosed based on reverse transcription polymerase chain reaction, the patients were classified as mild, moderate, severe, or critical depending on the clinical severity of their prominent clinical symptoms. In the initial viral phase, about 80% of patients usually have mild or asymptomatic disease. In the second phase, host–virus interactions take place which dictate the outcome for the subsequent phases of the disease, which corresponded to a hyper-responsiveness of the immune system. Given this characterization, the typical clinical manifestations were the representatives of the targets of COVID-19. Thus, it is worth noting that the disease targets were obtained by the clinical symptom-guided searching, and, interestingly, the commonly used known related targets for COVID-19 such as NR3C1,29 JAK2,30 JAK3,31 MIF,32 and STAT333 had been overlapped.

KEGG analysis revealed many pathways associated with COVID-19, such as MAPK signaling pathway, PI3K/AKT signaling pathway, and JAK-STAT pathway. The PPI network found that EGFR, TP53, TNF, JAK2, NR3C1, TH, COMT, and DRD2 were the core targets of HSYFD in the treatment of COVID-19. The role of inflammatory mechanism had been highlighted in the pathogenesis of COVID-19. Tumor necrosis factor (TNF), another key mediator of triggering the cytokine storm, showed high levels in organs such as the lymph nodes of COVID-19 patients, which could prevent the body from producing memory B cells, thereby inhibiting the generation of a durable immune response.34 At present, the JAK inhibitor baricitinib, which could reduce inflammation by inhibiting the levels of cytokines such as IL-6, IL-1β, and TNF-α and regulate the immune environment, was approved by FDA for the treatment of hospitalized adult patients with COVID-19.35 According to the COVID-19 pathological characteristics, the overexpressed EGFR in the infected lung cells exacerbates pulmonary fibrosis as the severe consequence of cytokine storm, evidenced by the transcriptomic data of patients.36 Additionally, the lung lesions in COVID-19 patients could be alleviated by the treatment of anti-EGFR antibodies like nimotuzumab, accompanied with the reduced plasma IL-6 level.37 In addition, protective and immunomodulatory effects of TCM were observed by augmenting TNF-α and IL-6 expression in the animal model of acute lung inflammation. Recent accumulating data suggested that TP53 gene therapy may be a new treatment for COVID-19 patients,38 and it was therefore concluded that the compounds from HSYFD might augment TP53 expression. For example, 6-gingerol, which showed good binding activities to TP53, could promote the activation of TP53.39

The subsequent molecular docking computational analysis confirmed the constituent–target interactions from the network pharmacology results. Based on the description above, it was speculated that HSYFD may play a role in the treatment of COVID-19 via MAPK signaling pathway, PI3K/AKT signaling pathway, and JAK-STAT pathway.

Although 108 compounds were identified for HSYFD, only 11 prototype compounds as the absorbed constituents were characterized in the rat serum. However, those unabsorbed constituents were not considered key active constituents because of the multiple complex ingredient–body interactions. Sometimes, unabsorbed compounds such as flavonoids were metabolized by the gut microbiota to smaller metabolites, which were more bioavailable than their precursors.40 Moreover, microbiological studies showed that unabsorbed components could prompt the growth of beneficial bacteria and inhibit the growth of disease-causing bacteria, contributing to maintain the homeostasis of the digestive system and gut flora.41 Of course, the alterations of gut microbiota in COVID-19 patients consequently may lead to the development of gut dysbiosis-related diseases. Therefore, it was also recommended for the recovery of gut microbiota balance while treating COVID-19 patients.42 Many Chinese herbs and preparations have demonstrated properties of restoring intestinal barrier function and intestinal homeostasis, which may further modulate the immune function after SARS-CoV-2 infection.43,44 Understanding the role of compounds in maintaining intestinal flora balance could provide new ideas for preventing and treating COVID-19.

At present, FDA-approved anti-SARS-CoV-2 drugs such as Paxlovid, Molnupiravir, and remdesivir, mainly focus only on individual targets like 3CL protease and RdRp, and it took plenty of time and capital to discover the new drug, which is still effective on the front of continuous mutation of SARS-CoV-2.45−47 Based on a specific theory, numerous clinical data evidenced the TCM for many known infectious disease treatments. More importantly, TCM played an irreplaceable role in the prevention and treatment of unknown COVID-19 since its first epidemic, especially in the treatment of mild patients.48,49 Furthermore, current clinical trials are devoted to finding the superiority of the combination of the TCM and western medicine in the treatment of COVID-19 patients infected with Delta or Omicron variants, when compared with the western medicine treatment.50

4. Conclusions

In this work, the chemical components of HSYFD in vivo and in vitro were analyzed by a UHPLC–Q-TOF-MS method, and the mechanism for treating COVID-19 was explored by clinical symptom-guided network pharmacology technology with molecular docking. A total of 108 components were identified from HSYFD, of which 11 components were detected in the rat serum after its oral administration. MAPK signaling pathway, PI3K/AKT signaling pathway, and JAK-STAT pathway were recognized as the key pathways of HSYFD for confronting COVID-19, with COMT, DRD2, EGFR, JAK2, NR3C1, TNF, and TP53 as the key targets. Our work also verified the feasibility of clinical symptom-guided network pharmacology analysis for the chemical compounds, which provided a possible agreement between the points of view of TCM and western medicine on the disease.

5. Materials and Methods

5.1. Materials and Reagents

AR (19091207, Inner Mongolia), CRP (19090603, Zhejiang Province), MOC (19042803, Fujian Province), PH (19051410, Zhejiang Province), TF (18032901, Yunnan Province), EH (15092512, Shanxi Province), NRR (19011512, Qinghai Province), AS (19010309, Guangdong Province), and ZRR (20200308, Shanghai Province) were purchased from Wujiang District Shanghai Cai Tong de Tang Chinese herbal pieces Co., Ltd., and identified by Prof. Chen Wan-sheng from Shanghai University of Traditional Chinese Medicine. Hesperidin (P06D9F77001), 6-shogaol (P06N9L74388), and notopterol (R28m9f57295) were purchased from Shanghai Yuanye Biotechnology Co., Ltd. (purity ≥ 98%). Ultra-pure water was prepared using a Milli-Q water purification system (Bedford, France). Acetonitrile and methanol were of UPLC grade (Merck, Darmstadt, Germany). All other reagents were of analytical grade.

5.2. Preparation of the HSYFD Extract

AR (105 g), CRP (70 g), MOC (70 g), PH (70 g), TF (42 g), EH (42 g), NRR (70 g), ZRR(70 g), and AS (70 g) were co-decocted in water twice, for 1 h each time. Water added in the first round was 10 times the total weight of the herbs, and in the second round it was 8 times the total weight of the herbs. The extraction solutions were then filtered, combined, and concentrated under vacuum to yield 610 mL of a concentrated decoction (HSYFD, 0.998 g/mL). About 10 mL of the HSYFD was centrifuged at 3000 r/min for 10 min, transferred into a 1.5 mL centrifuge tube, and centrifuged again at 13,000 rpm for 15 min. 200 μL of the supernatant was then subjected to UHPLC–Q-TOF-MS analysis. The remaining decoction was freeze-dried to obtain lyophilized powder, dissolved in normal saline by ultrasound to form a solution equivalent to a crude drug concentration of 7 g/mL, and stored at 4 °C before intragastric administration.

5.3. UHPLC–Q-TOF-MS Analysis

An Agilent 1290 ultra-performance liquid chromatography system (Agilent Technologies, Santa Clara, California, USA) coupled with an Agilent 6530 Accurate Quality Q-TOF/MS system (Agilent Technologies, USA) was employed in this study. Chromatographic separation was performed on a Waters Acquity UPLC BEH C18 column (2.1 × 100 mm, 1.7 μm). The mobile phase consisted of 0.1% formic acid–water (phase A) and acetonitrile (phase B). The gradient elution procedure was set as follows: 0–3 min, 5–5% B; 3–15 min, 5–35% B; 15–29 min, 35–95% B; 29–30 min, 95% B. The flow rate was 0.3 mL/min. The column temperature was maintained at 30 °C. The injection volume was 1 μL for the HSYFD sample and 2 μL for the serum. The UV spectra were recorded at 254 and 360 nm.

Parameters for Electrospray Mass Spectrometry (ESI-MS) analysis were set as follows: scan range, mass-to-charge ratio (m/z), 100–1700; dry gas (N2) temperature, 350 °C; dry gas flow, 11.0 L/min; atomizer gas pressure, 45 psi; capillary voltage, 4000 V (positive)/3500 V (negative); divider voltage, 140 V; collision energy, 30 V. All data were obtained with reference masses at m/z 121.0509 and 922.0098 in the positive mode, and at m/z 1033.9881 in the negative mode. QC samples were injected after every five samples during the sequence analysis to evaluate the analytical performance. Agilent mass Hunter qualitative analysis B.10.00 was used for data collection and processing. MS finder 3.5.0 (http://prime.psc.riken.jp/compms/msfinder/main.html), HMDB 5.0 (https://hmdb.ca/), and Massbank (http://www.massbank.jp/) were used to further confirm the compound information.

5.4. Animals and Drug Administration

Twelve SPF grade male Sprague–Dawley rats (220 ± 20 g) were obtained from the Shanghai Institute of Planned Parenthood Research (Shanghai, China) and were housed in accordance with the Animal Ethics Committee of Shanghai University of Traditional Chinese Medicine (PZSHUTCM201113012). All rats were stored in a room with controlled temperature (22–26 °C) and humidity (40–70%), under a 12 h light–dark cycle. Animals were acclimatized to the facility for 1 week before the start of the experiment. Rats were randomly divided into two groups (n = 6 for each group) before the experiment. Rats in the HSYFD group were dosed at 70 g crude drug/kg/day for three consecutive days, while 0.9% normal saline (2 mL/day) was administered to the rats in the control group.

5.5. Serum Sample Collection and Pretreatment Method

Blood samples were collected from the infraorbital vein 1 h after the last administration of HSYFD and stored in 5 mL BD Vacutainer Plus Plastic Blood Collection Tubes. Serum was obtained by centrifugation at 3000 rpm at 4 °C for 10 min after standing for 2 h at room temperature (25 °C), and 100 μL of which was deproteinized with 400 μL of ice-cold methanol. After being vortexed for 1 min and centrifuged at 4 °C at 12,000 rpm for 15 min, the supernatant was transferred to a new centrifuge tube, lyophilized, and then reconstituted in 100 μL of methanol. The supernatant was centrifuged at 12,000 rpm for 10 min at 4 °C, and the supernatant was prepared for UHPLC–Q-TOF-MS analysis.

5.6. Target Network Analysis

The potential targets of the compounds were obtained from Swiss Target Prediction (http://www.swisstargetprediction.ch) and TCMSP (https://tcmspw.com/tcmsp.php). Based on TCMIP V2.0 (http://www.tcmip.cn), the HSYF phenotype targets were obtained by retrieving the entries of clinical symptom of mild stage of COVID-19, including fever, cough, abnormality of the pharynx, fatigue, anergy, dyspnea, abnormality of the stomach, nausea, vomiting, diarrhea, abnormality of the tongue, and abnormality of the vasculature.

The ImageGP website (http://www.ehbio.com/ImageGP/) was used to identify the common targets of HSYFD and COVID-19. The OmicShare cloud platform (https://www.omicshare.com/tools/) was used for dynamic GO enrichment analysis and KEGG pathway enrichment analysis of the abovementioned common targets, and “homo sapiens” was selected as the gene source. Significance was set at P < 0.001 for GO entries and at P < 0.01 for signal pathways. The common targets were also used to construct a PPI network model on the String website, and then input into Cytoscape 3.7.2 to obtain the PPI network, and the network analyzer function in the software was used to obtain the relevant network topology parameters. The core targets of HSYFD treatment of COVID-19 were screened with the three indices of degree of degrees, betweenness centrality, and closeness centrality, all of which exceeded the average values.51

5.7. Molecular Docking Analysis

The 3D structures of the core targets were obtained from the PDB database (http://www.rcsb.org) and AlphaFold (https://alphafold.ebi.ac.uk). PyMOL software was used to remove excess water molecules and inactive ligands. 3D structures of the compound corresponding to the core target from PubChem were converted to PDB format by openbabel 3.1.1 and saved as pdbqt format using autodock tools 1.5.7. Autodock Vina and PyMOL software were used for molecular docking and visualization.52

Acknowledgments

This project was supported by the National Natural Science Foundation of China (81830109), Jin-Zi-Ta Talent projects (0806 and 1016), and Innovative Clinical Research Funding Project (2020YLCYJ-Y25).

Author Contributions

G.-Y.J. and X.-C.F. contributed equally to this study and were co-first authors. Manuscript writing, G.-Y.J. and X.-C.F.; manuscript revision and data checking, F.Z. and D.-D.H.; rat experimental, G.-Y.J. and X.-C.F.; UHPLC–Q-TOF-MS analysis, G.-Y.J., Y.-J.W., N.W., and L.-L.O.Y.; network pharmacology, G.-Y.J., H.-Q.W., and S.-H. P.; project administration, W.-S.C.; funding acquisition, F.Z. and W.-S.C. All authors have read and approved the final version of the manuscript.

The authors declare no competing financial interest.

Notes

The animal study was reviewed and approved by the Animal Ethics Committee of Shanghai University of Traditional Chinese Medicine (PZSHUTCM201113012).

Notes

The raw data sets used and analyzed during the study are available on request to the senior author (W.-S.C., chenwansheng@smmu.edu.cn).

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