Prediction of Treatment Mechanisms of Scutellariae Radix on Viral Pneumonia Through Network Pharmacology: Focus on Hypoxic State Regulation Through HIF-1<i>α</i> and HSP90

Jee-won Shon; Do Kyung Han; Youn Sook Kim; Won Gun An; Shon, Jee-won; Han, Do Kyung; Kim, Youn Sook; An, Won Gun

doi:10.13048/jkm.24024

JKM > Volume 45(2); 2024 > Article

Shon, Han, Kim, and An: Prediction of Treatment Mechanisms of Scutellariae Radix on Viral Pneumonia Through Network Pharmacology: Focus on Hypoxic State Regulation Through HIF-1α and HSP90

Original Article

The Journal of Korean Medicine 2024; 45(2): 55-73.

Published online: June 01, 2024

DOI: https://doi.org/10.13048/jkm.24024

Prediction of Treatment Mechanisms of Scutellariae Radix on Viral Pneumonia Through Network Pharmacology: Focus on Hypoxic State Regulation Through HIF-1α and HSP90

Jee-won Shon¹^{, §}

, Do Kyung Han¹^{, §}

, Youn Sook Kim²^{, *}

, Won Gun An¹^{, *}

¹Department of Korean Medicine, School of Korean Medicine, Pusan National University

²Research Institute for Longevity and Well-Being, Pusan National University

Correspondence to: Won Gun An, Department of Korean Medicine, School of Korean Medicine, Pusan National University, Tel: +82-51-510-8455, E-mail: wgan@pusan.ac.kr

Correspondence to: Youn Sook Kim, Research Institute for Longevity and Well-Being, Pusan National University, Tel: +82-51-510-8455, E-mail: younskim@pusan.ac.kr

§ These authors contributed equally to this work.

Received April 15, 2024 Revised May 14, 2024 Accepted May 14, 2024

Abstract

Objectives

In this study, we used network-based systems pharmacology analysis and molecular docking methods to predict the therapeutic mechanism of Scutellariae Radix on viral pneumonia.

Methods

We screened active components of Scutellariae Radix and its’ genes by TCMSP. Also, we extracted viral pneumonia related target genes through Gene Cards, CTD and DisGeNet. To construct Protein-protein Interaction, STRING database was used. For functional enrichment, using SRplot platform, genes were classified by 3 categories: cellular component (CC), molecular function (MF) and biological process (BP). Molecular docking was conducted by AutoDockTools (version 4.2.6).

Results

32 Network-based systematic pharmacology analysis identified 37 target genes associated with baicalein. Based on the network and gene ontology analysis of the active ingredient's target genes and disease target genes, we identified nine core genes (AKT1, BAX, BCL2, CASP3, HIF1A, PTGS2, RELA, TP53, VEGFA) and HSP90 as involved. Notably, HIF1A showed the highest relevance, overlapping with two or more utilized programs. Hypoxia-inducible factor 1-alpha (HIF-1α) has been implicated in the expression of inflammatory cytokines, the induction of hypoxia, and the triggering of cytokine storms. Baicalein, a major component of SR, binds to both HIF-1α and HSP90, suggesting that it may be a possible targeted treatment for viral pneumonia.

Conclusions

Baicalein may bind to HIF-1α to control inflammation caused by viral infectious diseases and may also regulate hypoxic conditions to prevent impairment of lung function caused by an overactive immune system. These findings suggest further research into the molecular mechanisms involved in hypoxia and provide a scientific basis for improving the treatment of viral infectious diseases.

Keywords: Baicalein, COVID-19, HIF-1α, Molecular docking, Scutellariae Radix

Fig. 1

Investigating overlaps between genes derived by applying four keywords related to viral pneumonia to three databases: GeneCards (G), DisGeNET (D), and CTD (C), and Baicalein's target genes.

(A) The keyword is 'Viral Pneumonia’. (B) The keyword is 'Pneumonia Influenza’. (C) The keyword is 'SARS’. (D) The keyword is 'Coronavirus Infection’. The number of genes overlapping between disease-related genes and Baicalein's target genes is represented by black circles.

Fig. 2

Nine Key Genes Common in Four Keywords.

Fig. 3

Protein-Protein Interaction of 26 Key Duplicated Genes Overlapping in Two or More Disease keywords. PPI enrichment p-value: < 1.0e-16.

Fig. 4

Protein-Protein Interaction (PPI) Involving 9 Key Duplicated Genes and HSP90, as Represented in STRING.

(A) 10 nodes connected by 36 edges, averaging 7.2 nodes interacting. PPI enrichment p-value: 0.00267. (B) Genes associated with lung tissue (green nodes). (C) Genes involved in host-virus interaction (blue nodes) and apoptosis (red nodes).

Fig. 5

Ten Compounds and Targets with a High Degree of Association Among the Compounds of Scutellariae Radix and Target genes.

Fig. 6

Gene Ontology Analysis of Scutellariae Radix and Baicalein.

The results for three ontologies, namely Biological Process (BP), Cellular Component (CC), and Molecular Function (MF), for both (A) Scutellariae Radix and (B) Baicalein.

Fig. 7

Predictive model of the binding of baicalein to HSP90 and HIF1A

(A) Gray: protein, HSP90 (PDB ID: 1YET), pink: ligand, baicalein, affinity: −6.7 kcal/mol. (B) Light green: van der waals, Green: conventional hydrogen bond, Pink: Pi-alkyl, Yellow: Pi-sulfur, Purple: Pi-sigma. (C) 3D structure of the intermolecular docking of baicalein and HSP90. (D) Gray: protein, HIF1A (PDB ID: 8HE3), Pink: ligand, baicalein, affinity: −6.6 kcal/mol. (E) Light green: van der waals, Green: conventional hydrogen bond, Pink: Pi-alkyl, Yellow: Pi-anion. (F) 3D detailed structure of the intermolecular docking of baicalein and HIF1A.

Table 1

Active Compounds of Scutellariae Radix

Molecule ID	Molecule Name	OB (%)	Caco-2	DL
MOL000073	ent-Epicatechin	48.96	0.02	0.24
MOL000173	wogonin	30.68	0.79	0.23
MOL000228	(2R)-7-hydroxy-5-methoxy-2-p henylchroman-4-one	55.23	0.87	0.2
MOL000358	beta-sitosterol	36.91	1.32	0.75
MOL000449	Stigmasterol	43.83	1.44	0.76
MOL000525	Norwogonin	39.4	0.6	0.21
MOL000552	5,2'-Dihydroxy-6,7,8-trimethox yflavone	31.71	0.93	0.35
MOL001458	coptisine	30.67	1.21	0.86
MOL001490	bis[(2S)-2-ethylhexyl] benzene-1,2-dicarboxylate	43.59	0.98	0.35
MOL001506	Supraene	33.55	2.08	0.42
MOL001689	acacetin	34.97	0.67	0.24
MOL002714	Baicalein	33.52	0.63	0.21
MOL002879	Diop	43.59	0.79	0.39
MOL002897	epiberberine	43.09	1.17	0.78
MOL002908	5,8,2'-Trihydroxy-7-methoxyfl avone	37.01	0.76	0.27
MOL002909	5,7,2,5-tetrahydroxy-8,6-dimet hoxyflavone	33.82	0.35	0.45
MOL002910	Carthamidin	41.15	0.16	0.24
MOL002914	Eriodyctiol (flavanone)	41.35	0.05	0.24
MOL002915	Salvigenin	49.07	0.86	0.33
MOL002917	5,2',6'-Trihydroxy-7,8-dimetho xyflavone	45.05	0.48	0.33
MOL002925	5,7,2',6'-Tetrahydroxyflavone	37.01	0.18	0.24
MOL002926	dihydrooroxylin A	38.72	0.71	0.23
MOL002927	Skullcapflavone II	69.51	0.68	0.44
MOL002928	oroxylin a	41.37	0.76	0.23
MOL002932	Panicolin	76.26	0.84	0.29
MOL002933	5,7,4'-Trihydroxy-8-methoxyfl avone	36.56	0.46	0.27
MOL002934	NEOBAICALEIN	104.34	0.74	0.44
MOL008206	Moslosooflavone	44.09	1.01	0.25
MOL010415	11,13-Eicosadienoic acid, methyl ester	39.28	1.46	0.23
MOL012245	5,7,4'-trihydroxy-6-methoxyfla vanone	36.63	0.43	0.27
MOL012246	5,7,4'-trihydroxy-8-methoxyfla vanone	74.24	0.37	0.26
MOL012266	rivularin	37.94	0.65	0.37

Table 2

Targets of Baicalein

Target Proteins of Baicalein	Gene name	UniProt ID
Aryl hydrocarbon receptor	AHR	P35869
RAC-alpha serine/threonine-protein kinase	AKT1	P31749
Arachidonate 12-lipoxygenase, 12S-type	ALOX12	P18054
Apolipoprotein D	APOD	P05090
Androgen receptor	AR	P10275
Apoptosis regulator BAX	BAX	Q07812
Apoptosis regulator Bcl-2	BCL2	P10415
Calmodulin	CALM1	P0DP23
Caspase-3	CASP3	P42574
G2/mitotic-specific cyclin-B1	CCNB1	P14635
Cell division control protein 2 homolog	CDK1	P06493
Cytochrome c	CYCS	P99999
Dipeptidyl peptidase IV	DPP4	P27487
Egl nine homolog 1	EGLN1	Q9GZT9
Fatty acid-binding protein, epidermal	FABP5	Q01469
Proto-oncogene c-Fos	FOS	P01100
Fos-related antigen 1	FOSL1	P15407
Fos-related antigen 2	FOSL2	P15408
Hypoxia-inducible factor 1-alpha	HIF1A	Q16665
Heat shock protein HSP 90	HSP90AB1	P08238
Insulin-like growth factor II	IGF2	P01344
Matrix metalloproteinase-9	MMP9	P14780
Myeloperoxidase	MPO	P05164
Nuclear receptor coactivator 1	NCOA1	Q15788
Nuclear receptor coactivator 2	NCOA2	Q15596
Nuclear factor of activated T-cells, cytoplasmic 1	NFATC1	O95644
NADPH oxidase 5	NOX5	Q96PH1
CGMP-inhibited 3',5'-cyclic phosphodiesterase A	PDE3A	Q14432
Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit, gamma isoform	PIK3CG	P48736
mRNA of PKA Catalytic Subunit C-alpha	PRKACA	P17612
Trypsin-1	PRSS1	P07477
Prostaglandin G/H synthase 1	PTGS1	P23219
Prostaglandin G/H synthase 2	PTGS2	P35354
Transcription factor p65	RELA	Q04206
Tudor domain-containing protein 7	TDRD7	Q8NHU6
Cellular tumor antigen p53	TP53	P04637
Vascular endothelial growth factor A	VEGFA	P15692

Table 3

Common Genes between Baicalein Target Genes between Each Diseases Keyword.

Viral Pneumonia	Pneumonia Influenza	SARS	Coronavirus Infection
AHR	AHR	CASP3	DPP4
AKT1	AKT1	AKT1	AHR
APOD	BAX	APOD	AKT1
AR	BCL2	AR	APOD
BAX	CASP3	BAX	AR
BCL2	DPP4	BCL2	BAX
CASP3	FABP5	CCNB1	BCL2
CDK1	FOSL1	CYCS	CALM1
CYCS	HIF1A	FOS	CASP3
EGLN1	MMP9	FOSL1	CCNB1
FABP5	MPO	HIF1A	CDK1
FOS	PIK3CG	MMP9	FABP5
FOSL1	PRSS1	MPO	FOS
FOSL2	PTGS1	NFATC1	HIF1A
HIF1A	PTGS2	PTGS2	HSP90AB1
IGF2	RELA	RELA	PIK3CG
MMP9	TP53	TP53	PRKACA
MPO	VEGFA	VEGFA	PRSS1
NFATC1			PTGS2
NOX5			RELA
PDE3A			TP53
PIK3CG			VEGFA
PRKACA
PRSS1
PTGS1
PTGS2
RELA
TP53
VEGFA

Table 4

26 Genes Duplicated Two or More Times in Four Disease Names

Duplicated 4 times	Duplicated 3 times	Duplicated 2 times
AKT1	AHR	CDK1
BAX	FABP5	PRKACA
BCL2	PIK3CG	PTGS1
CASP3	PRSS1	DPP4
HIF1A	FOSL1	CYCS
PTGS2	MMP9	NFATC1
RELA	MPO	CCNB1
TP53	APOD
VEGFA	AR
	FOS

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