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New Approach for Targeted Treatment of Mild COVID-19 by Honeysuckle through Network Pharmacology Analysis.

Authors :
Li H
Li Y
Luo C
Liang X
Liu Z
Liu Y
Ling Y
Source :
Computational and mathematical methods in medicine [Comput Math Methods Med] 2022 Feb 21; Vol. 2022, pp. 9604456. Date of Electronic Publication: 2022 Feb 21 (Print Publication: 2022).
Publication Year :
2022

Abstract

Objective: To investigate the potential pharmacological value of extracts from honeysuckle on patients with mild coronavirus disease 2019 (COVID-19) infection.<br />Methods: The active components and targets of honeysuckle were screened by Traditional Chinese Medicine Database and Analysis Platform (TCMSP). SwissADME and pkCSM databases predict pharmacokinetics of ingredients. The Gene Expression Omnibus (GEO) database collected transcriptome data for mild COVID-19. Data quality control, differentially expressed gene (DEG) identification, enrichment analysis, and correlation analysis were implemented by R toolkit. CIBERSORT evaluated the infiltration of 22 immune cells.<br />Results: The seven active ingredients of honeysuckle had good oral absorption and medicinal properties. Both the active ingredient targets of honeysuckle and differentially expressed genes of mild COVID-19 were significantly enriched in immune signaling pathways. There were five overlapping immunosignature genes, among which RELA and MAP3K7 expressions were statistically significant ( P < 0.05). Finally, immune cell infiltration and correlation analysis showed that RELA, MAP3K7, and natural killer (NK) cell are with highly positive correlation and highly negatively correlated with hematopoietic stem cells.<br />Conclusion: Our analysis suggested that honeysuckle extract had a safe and effective protective effect against mild COVID-19 by regulating a complex molecular network. The main mechanism was related to the proportion of infiltration between NK cells and hematopoietic stem cells.<br />Competing Interests: The authors declare that they have no conflicts of interest.<br /> (Copyright © 2022 Huijuan Li et al.)

Details

Language :
English
ISSN :
1748-6718
Volume :
2022
Database :
MEDLINE
Journal :
Computational and mathematical methods in medicine
Publication Type :
Academic Journal
Accession number :
35237344
Full Text :
https://doi.org/10.1155/2022/9604456