scholarly journals GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Baixia Zhang ◽  
Shuaibing He ◽  
Chenyang Lv ◽  
Yanling Zhang ◽  
Yun Wang
Keyword(s):  
Gene Expression ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Small Molecule ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Bioactive Components ◽  
Target Proteins ◽  
Small Molecule Drugs

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

scholarly journals Rheumatoid Arthritis with Deficiency Pattern in Traditional Chinese Medicine Shows Correlation with Cold and Hot Patterns in Gene Expression Profiles

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Minzhi Wang ◽  
Gao Chen ◽  
Cheng Lu ◽  
Cheng Xiao ◽  
Li Li ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
Immune Response ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Gene Transcription ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Nucleotide Metabolism ◽  
Toll Like Receptor

In our precious study, the correlation between cold and hot patterns in traditional Chinese medicine (TCM) and gene expression profiles in rheumatoid arthritis (RA) has been explored. Based on TCM theory, deficiency pattern is another key pattern diagnosis among RA patients, which leads to a specific treatment principle in clinical management. Therefore, a further analysis was performed aiming at exploring the characteristic gene expression profile of deficiency pattern and its correlation with cold and hot patterns in RA patients by bioinformatics analysis approach based on gene expression profiles data detected with microarray technology. The TCM deficiency pattern-related genes network comprises 7 significantly, highly connected regions which are mainly involved in protein transcription processes, protein ubiquitination, toll-like receptor activated NF-κB regulated gene transcription and apoptosis, RNA clipping, NF-κB signal, nucleotide metabolism-related apoptosis, and immune response processes. Toll-like receptor activated NF-κB regulated gene transcription and apoptosis pathways are potential specific pathways related to TCM deficiency patterns in RA patients; TCM deficiency pattern is probably related to immune response. Network analysis can be used as a powerful tool for detecting the characteristic mechanism related to specific TCM pattern and the correlations between different patterns.

scholarly journals The Classification ofSiniDecoction Pattern in Traditional Chinese Medicine by Gene Expression Profiling

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Hung-Tsu Cheng ◽  
Chaang-Ray Chen ◽  
Chia-Yang Li ◽  
Chao-Ying Huang ◽  
Wun-Yi Shu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Clustering Algorithm ◽  
Mononuclear Cells ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
City Hospital ◽  
Test Results ◽  
Peripheral Blood Mononuclear

We investigated the syndromes of theSinidecoction pattern (SDP), a common ZHENG in traditional Chinese medicine (TCM). The syndromes of SDP were correlated with various severeYang deficiencyrelated symptoms. To obtain a common profile for SDP, we distributed questionnaires to 300 senior clinical TCM practitioners. According to the survey, we concluded 2 sets of symptoms for SDP: (1) pulse feels deep or faint and (2) reversal cold of the extremities. Twenty-four individuals from Taipei City Hospital, Linsen Chinese Medicine Branch, Taiwan, were recruited. We extracted the total mRNA of peripheral blood mononuclear cells from the 24 individuals for microarray experiments. Twelve individuals (including 6 SDP patients and 6 non-SDP individuals) were used as the training set to identify biomarkers for distinguishing the SDP and non-SDP groups. The remaining 12 individuals were used as the test set. The test results indicated that the gene expression profiles of the identified biomarkers could effectively distinguish the 2 groups by adopting a hierarchical clustering algorithm. Our results suggest the feasibility of using the identified biomarkers in facilitating the diagnosis of TCM ZHENGs. Furthermore, the gene expression profiles of biomarker genes could provide a molecular explanation corresponding to the ZHENG of TCM.

Design, synthesis, molecular docking and ADME studies of novel indole-thiazolidinedione derivatives and their antineoplastic activity as CDK6 inhibitors

2021 ◽  
Author(s):  
Zeynep Ates-Alagoz ◽  
Mehmet Murat Kisla ◽  
Fikriye Zengin Karadayi ◽  
Sercan Baran ◽  
Tuğba Somay Doğan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Docking ◽  
Anticancer Activity ◽  
Cell Line ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Antineoplastic Activity ◽  
Design Synthesis ◽  
Mcf 7

Several indole-thiazolidinedione derivatives (9–24) were designed and synthesized as CDK6 inhibitors, and their anticancer activity was probed on the MCF-7 cell line and the effects on gene expression profiles were elucidated.

A Study on the Mechanism of Lavender in the Treatment of Insomnia Based on Network Pharmacology

2020 ◽  
Vol 23 (5) ◽  
pp. 419-432
Author(s):  
Yao Wang ◽  
Junbo Zou ◽  
Yanzhuo Jia ◽  
Yulin Liang ◽  
Xiaofei Zhang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Protein ◽  
Ammonium Ion ◽  
Network Pharmacology ◽  
Common Disease ◽  
Active Components ◽  
Target Proteins ◽  
Analysis Platform

Aim and Objective: The common disease of insomnia has complex and diverse clinical manifestations. Lavender represents an effective treatment of insomnia, but the molecular mechanism underlying the effectiveness of this treatment is not clear. The purpose of this study is to investigate the active components, target proteins and molecular pathways of lavender in the treatment of insomnia, thus explaining its possible mechanism. Materials and Methods: Firstly, 54 active components of lavender were identified by gas chromatography-mass spectrometry (GC-MS). The target protein of lavender was predicted by the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform and the SwissTargetPredicating tool, and the target protein of insomnia was predicted by the DisGeNET and DrugBank databases. Then, the "component-target-disease" network diagram was constructed using the Cytoscape 3.7.1 software. KEGG and GO enrichments were analyzed using the R statistical language. Finally, the key target proteins were verified by collecting and verifying the target protein GEO data using the Discovery Studio 3.5 molecular docking verification software. Results: 906 target proteins of lavender were predicted by the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform and the SwissTargetPredicating tool, and 182 insomnia target proteins were predicted by the DisGeNET and DrugBank databases. The results of GO enrichment analysis showed that it included the reaction process of ammonium ion, the regulation of the membrane potential and the secretion of catecholamine, while the results of KEGG enrichment included the calcium signaling pathway, serotonin synapse, morphine addiction and many more. Finally, using the Discovery Studio3.5 molecular docking verification software, it was verified that the key target proteins are ADRB1 and HLA-DRB1. Conclusion: The components in the lavender essential oil include the Ethyl 2-(5-methyl-5-vinyltetrahydrofuran- 2-yl)propan-2-ylcarbonate (0.774); 5-Oxatricyclo[8.2.0.04,6]dodecane, 4,12,12-trimethyl- 9-methylene-, (1R,4R,6R,10S)-(0.147); P-Cymen-7-ol (0.063); .alpha-Humulenem (0.317); Acetic acid, hexyl ester (1.374); etc. The role lavender plays in the treatment of insomnia might be accomplished through the regulation of the key targets ADRB1 and HLA-DRB1.

scholarly journals HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine

2020 ◽  
Vol 49 (D1) ◽  
pp. D1197-D1206 ◽  
Author(s):  
ShuangSang Fang ◽  
Lei Dong ◽  
Liu Liu ◽  
JinCheng Guo ◽  
LianHe Zhao ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
High Throughput ◽  
Drug Targets ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Modern Drug ◽  
Powerful Approach ◽  
High Throughput Experiments ◽  
Systematic Database

Abstract Pharmacotranscriptomics has become a powerful approach for evaluating the therapeutic efficacy of drugs and discovering new drug targets. Recently, studies of traditional Chinese medicine (TCM) have increasingly turned to high-throughput transcriptomic screens for molecular effects of herbs/ingredients. And numerous studies have examined gene targets for herbs/ingredients, and link herbs/ingredients to various modern diseases. However, there is currently no systematic database organizing these data for TCM. Therefore, we built HERB, a high-throughput experiment- and reference-guided database of TCM, with its Chinese name as BenCaoZuJian. We re-analyzed 6164 gene expression profiles from 1037 high-throughput experiments evaluating TCM herbs/ingredients, and generated connections between TCM herbs/ingredients and 2837 modern drugs by mapping the comprehensive pharmacotranscriptomics dataset in HERB to CMap, the largest such dataset for modern drugs. Moreover, we manually curated 1241 gene targets and 494 modern diseases for 473 herbs/ingredients from 1966 references published recently, and cross-referenced this novel information to databases containing such data for drugs. Together with database mining and statistical inference, we linked 12 933 targets and 28 212 diseases to 7263 herbs and 49 258 ingredients and provided six pairwise relationships among them in HERB. In summary, HERB will intensively support the modernization of TCM and guide rational modern drug discovery efforts. And it is accessible through http://herb.ac.cn/.

scholarly journals Identification of Novel Biomarkers in Hepatocellular Carcinoma by Integrated Bioinformatical Analysis and Experimental Validation

2021 ◽  
Author(s):  
Chen Liao ◽  
Lanlan Wang ◽  
Xiaoqiang Li ◽  
Jinyu Bai ◽  
Jieqiong Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Small Molecule ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Venn Diagram ◽  
Ppi Network ◽  
Qrt Pcr ◽  
Small Molecule Drugs ◽  
Novel Biomarkers

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common poorly prognosed virulent neoplasms of the digestive system. In this study, we identified novel biomarkers associated with the pathogenesis of HCC aiming to provide new diagnostic and therapeutic approaches for HCC. Methods: Gene expression profiles of GSE62232, GSE84402,GSE121248 and GSE45267 were obtained in GEO database. Differential expressed genes (DEGs) between HCC and normal samples were identified using the GEO2R tool and Venn diagram software.Database for Annotation, Visualization and Integrated Discovery (DAVID) were used to carry out enrichment analysis on gene ontology (GO) and the Kyoto Encyclopaedia of Genes and Genomes pathway (KEGG). The protein-protein interaction (PPI) network of DEGs was constructed by the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized by Cytoscape. Expressions and prognostic values of hub genes were validated through Kaplan-Meier plotter, Gene Expression Profiling Interactive Analysis (GEPIA), the Human Protein Atlas Database (HPA), western blot (WB) and quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, potential small molecule drugs were screened by Connectivity Map (CMAP). Results: A total of 100 overlapped DEGs were detected and results showed 23 of which were up-regulated with the rest being down-regulated. STRING screened the 70 edges and the 199 nodes in the PPI network. Survival analysis showed that aberrant mRNA expression of TOP2A, DTL, ANLN, CDKN3, BUB1B, CDK1, PBK, RRM2, RACGAP1, PRC1, NEK2, ECT2, CCNB1, HMMR, ASPM was significantly associated with a low survival rate. Results of WB and qRT-PCR showed that the expression levels of ANLN, CCNB1, DTL, RACGAP1, RRM2 and TOP2A were all increased in HCC tissues. Furthermore, CMAP predict suggest the 10 most vital small molecule drugs could reverse the progression of HCC. Conclusions: Core DEGs (ANLN, CCNB1, DTL, RACGAP1, RRM2 and TOP2A) with poor prognosis and candidate drugs for HCC treatment were identified through integrated bioinformatic analysis.This study will contribute to providing prognostic biomarker and therapeutic strategies in HCC. Background : Hepatocellular carcinoma (HCC) is one of the most common poorly prognosed virulent neoplasms of the digestive system. In this study, we identified novel biomarkers associated with the pathogenesis of HCC aiming to provide new diagnostic and therapeutic approaches for HCC. Methods : Gene expression profiles of GSE62232, GSE84402,GSE121248 and GSE45267 were obtained in GEO database. Differential expressed genes (DEGs) between HCC and normal samples were identified using the GEO2R tool and Venn diagram software.Database for Annotation, Visualization and Integrated Discovery (DAVID) were used to carry out enrichment analysis on gene ontology (GO) and the Kyoto Encyclopaedia of Genes and Genomes pathway (KEGG). The protein-protein interaction (PPI) network of DEGs was constructed by the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized by Cytoscape. Expressions and prognostic values of hub genes were validated through Kaplan-Meier plotter, Gene Expression Profiling Interactive Analysis (GEPIA), the Human Protein Atlas Database (HPA), western blot (WB) and quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, potential small molecule drugs were screened by Connectivity Map (CMAP). Results : A total of 100 overlapped DEGs were detected and results showed 23 of which were up-regulated with the rest being down-regulated. STRING screened the 70 edges and the 199 nodes in the PPI network. Survival analysis showed that aberrant mRNA expression of TOP2A, DTL, ANLN, CDKN3, BUB1B, CDK1, PBK, RRM2, RACGAP1, PRC1, NEK2, ECT2, CCNB1, HMMR, ASPM was significantly associated with a low survival rate. Results of WB and qRT-PCR showed that the expression levels of ANLN, CCNB1, DTL, RACGAP1, RRM2 and TOP2A were all increased in HCC tissues. Furthermore, CMAP predict suggest the 10 most vital small molecule drugs could reverse the progression of HCC. Conclusions : Core DEGs (ANLN, CCNB1, DTL, RACGAP1, RRM2 and TOP2A) with poor prognosis and candidate drugs for HCC treatment were identified through integrated bioinformatic analysis.This study will contribute to providing prognostic biomarker and therapeutic strategies in HCC.

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