Anti-Breast Cancer Mechanism Research Of Polygonum Cuspidatum Via Bioinformatics And Network Pharmacology And Molecular Docking

ObjectiveIntegrating chip data sets and jointing TCGA database to mine hub genes provides a new reference for the study of breast cancer biomarkers.The mechanism of anti-breast cancer action of Polygonum cuspidatum was systematically explained by network pharmacology.At the same time,molecular docking and molecular fingerprint technology were used to verify hub genes and analyze structure similarity of the hub genes,which provided reference for experimental design and new drug development.Method1.Integrated gene expression profiting analysisUse R language to download chip data and then use limma packet to conduct normalization and differentially expressed genes analysis(DEGs)of the chip data.And differential expression of TCGA data was analyzed by using edgeR packages.Using Robust Rank Aggregation(RRA)algorithm to integrate the chip data set,and then intersect the TCGA DEGs gene to obtain their intersection DEGs genes.Utilizing DAVID 6.8 to carry out GO and KEGG pathway enrichment analysis of intersection DEGs genes.CMAP database was used to predict potential negative small molecule compounds of intersection DEGs genes.STRING database was used for intersection DEGs gene PPI analysis.Meanwhile,provide degree(Deg),maximal clique centrality(MCC)and density of maximum neighborhood component(DMNC),edge percolated component(EPC),betweenness(BC),Closeness(Clo)algorithms for network topology analysis to mine hub genes.Then analyzed animation prognosis of hub genes.2.Network pharmacology analysisActive components of Polygonum cuspidatum were obtained through TCMSP database and PharmMapper database was used for reverse docking with the active components of Polygonum cuspidatum,aiming to obtain the component targets.Breast cancer targets,obtaining from NCBI 、 CooLGeN and Genecards,intersected with component targets to obtain intersection targets.The intersection targets use ClueGO for KEGG、GO enrichment analysis and STRING database for protein interaction PPI analysis,and mine core targets by combining cytoHubba plug-in which provided the algorithms like Deg、MCC、DMNC、EPC、BC and Clo for network topology analysis.3.Molecular docking and molecular fingerprinting analysisThe core target genes obtained in this study were integrated for molecular docking.Receptor pdb files of the core target genes were derived from the PDB database and the core target genes’ ligand files were the potential active components of Polygonum cuspidatum and the positive drug doxorubicin.At the same time,molecular fingerprint technology was used to study the structural similarity comparison among small molecular compounds predicted by CMAP,positive drug doxorubicin and potential active components of Polygonum cuspidatum,which aimed to dig into the potential active components of Polygonum cuspidatum.Result1.Integrated gene expression profiting analysisBy synthesizing multiple sets of chips for differential analysis and combining TCGA data for intersection gene mining,201 differential genes were obtained.In these 201 differential genes,there were 69 up-regulation genes and 132 down-regulated genes.The first 7 negative small molecule compounds were obtained from the CMAP database.Functional annotation analysis found that up-regulated genes were mainly involved in protein catabolism,CXCR3 chemokine receptor binding,CXCR chemokine receptor binding,and histone kinase activity;The down-regulated genes were mainly involved in the negative regulation of smooth muscle cell proliferation,activation of protein homodimers and activation of steroid monooxygenase,etc;The action pathway mainly involves PPAR signal pathway,ECM signal pathway,AMPK signal pathway and so on.Twelve hub genes(EZH2、CCNB1、KIAA0101、PBK、CDK1、PTTG1、AURKA、UBE2C、BUB1B、HMMR、UBE2T、RMI2)were mined by using Deg、MCC、DMNC、EPC、BC、Clo algorithm.Except for RMI2 genes,the other genes are related to the animation prognosis of breast cancer,which may be biomarkers of breast cancer.2.Network pharmacology analysisIn this study,32 potential active components and 321 component targets of Polygonum cuspidatum were obtained.There are 3827 disease targets from OMIM,726 disease targets from Coo LGeN and 810 disease targets from Genecards.Crossing component targets and disease targets,73 intersection targets were obtained.The intersection targets were significantly enriched in cell proliferation,migration,apoptosis,protein phosphorylation,angiogenesis and other processes,involving cancer pathways,PI3K-Akt signaling pathways,VEGF signaling pathways,etc.Simultaneously,mining PPI networks by using Deg、MCC、DMNC、EPC、BC、Clo algorithms,11 hub targets(IGF1R、MAP2K1、JAK2、AKT2、CDC42、PGR、XIAP、GRB2、KDR、STAT1、ABL1)were obtained.3.Molecular docking and molecular fingerprinting analysisMolecular docking results showed that the potentially active compounds of Polygonum cuspidatum could bind to the core target to a certain extent,among which resveratrol,polydatin,quercetin and other compounds have been reported in relevant literatures.The results of empirical function score showed that the molecular docking scores of compounds such as emodin methyl ether diglucoside,sitogluside,anthraglycoside B were close to doxorubicin,which suggested that these compounds might have similar pharmacological effects with doxorubicin.The molecular fingerprint results showed that the structure of multiple compounds in Polygonum cuspidatum was similar to doxorubicin,genistein,deferoxamine and resveratrol,such as Polydatin,hydroxyemodin,luteolin and quercetin.ConclusionThis study provides a new reference for biomarkers discovery of breast cancer by integrating databases and combining with multiple algorithms to mine core genes.The mechanism of anti-breast cancer action of Polygonum cuspidatum was preliminarily explained by network pharmacology.At the same time,molecular docking and fingerprinting were used to verify the core targets and investigate the structure similarity of the core targets,which provides new ideas for drug development and experimental research.However,this study was mainly based on data prediction and the existing literatures to verify the results,so the results need to be further verified in vitro and in vivo experiments.