Evidence map›Paper›PMID 35990823›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2022

Potential Mechanisms of Biejiajian Pill in the Treatment of Diabetic Atherosclerosis Based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

Rong Zhu, Bingzhao Du, Jiayao Yuan, Shuxun Yan, Mingyi Shao, Feng Sang, Qian Bi, Zhongrui Wang, Qian Zhen, Yu Fu

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Rong ZhuSchool of the First Clinical, Henan University of Chinese Medicine, Zhengzhou 450000, China.ORCID https://orcid.org/0000-0001-5148-9860
Bingzhao DuDepartment of Science Research, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, China.
Jiayao YuanSchool of the First Clinical, Henan University of Chinese Medicine, Zhengzhou 450000, China.ORCID https://orcid.org/0000-0002-5437-8944
Shuxun YanDepartment of Endocrinology, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, China.
Mingyi ShaoDepartment of Gastroenterology, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, China.
Feng SangDepartment of Key Laboratory of Viral Diseases Prevention and Treatment of Traditional Chinese Medicine of Henan Province, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, China.
Qian BiDepartment of Science Research, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, China.
Zhongrui WangSchool of the First Clinical, Henan University of Chinese Medicine, Zhengzhou 450000, China.
Qian ZhenSchool of the First Clinical, Henan University of Chinese Medicine, Zhengzhou 450000, China.
Yu FuDepartment of Science Research, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, China.ORCID https://orcid.org/0000-0001-9849-7841
First Affiliated Hospital of Henan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Biejiajian pill (BJJP), a classical traditional Chinese formula, has been reported that it has an effective treatment for diabetic atherosclerosis in recent years, but its underlying mechanisms remain elusive. The study aimed to explore the potential mechanisms of BJJP on diabetic atherosclerosis by integrating network pharmacology, molecular docking, and molecular dynamics simulation. Methods: The active components of BJJP were collected by TCMSP and TCMID, and then the potential targets were obtained from the SwissTargetPrediction database. The targets related to diabetic atherosclerosis were identified from the GeneCards and OMIM databases. The intersection of the potential targets regulated by active components of BJJP and the targets of diabetic atherosclerosis were common targets, which were visualized by the Venn diagram. The common targets were imported into the STRING database to construct a protein-protein interaction (PPI) network. The network of "Medicine-Compound-Target" was constructed with Cytoscape 3.7.1 software. GO functional enrichment analysis and KEGG pathway enrichment analysis were performed using the DAVID database and visualized through bioinformatics. The intersecting targets were input into Cytoscape 3.7.1 software, and the Network Analyzer tool was employed to screen out the key targets. Then molecular docking was used to verify the binding affinity between the active compounds and the key targets, and molecular dynamics simulation was used to investigate the stability of the binding models. Results: A total of 81 active components, 186 targets of BJJP, and 4041 targets of diabetic atherosclerosis were obtained. Furthermore, 121 overlapping targets were identified. GO functional enrichment analysis revealed that these targets were correlated with the oxidation-reduction process, negative regulation of apoptotic process, inflammatory response, and other biological processes. The results of the KEGG pathway enrichment analysis showed that the common targets mainly participated in proteoglycans in cancer, PPAR signaling pathway, adherens junction, insulin resistance, HIF-1 signaling pathway, PI3K-Akt signaling pathway, etc. The results of molecular docking confirmed that the core active components in BJJP could bind well to the key targets. Results from molecular dynamics simulation showed that the binding energies of AKT1-Luteolin, MMP9-quercetin, and MMP9-luteolin complexes were -28.93 kJ·mol Conclusion: The study revealed that BJJP is characterized as multicomponent, multitarget, and multipathway to treat diabetic atherosclerosis, which is helpful to provide ideas and a basis for pharmacological research and clinical application in the future.

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PMID35990823
PMCPMC9391107
OpenAlexW4290964038

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.