Bioinformatics analysis of ferroptosis in spinal cord injury

Ferroptosis plays a key role in aggravating the progression of spinal cord injury(SCI),but the specific mechanism remains unknown.In this study,we constructed a rat model of T10 SCI using a modified Allen method.We identified 48,44,and 27 ferroptosis genes that were differentially expressed at 1,3,and 7 days after SCI induction.Compared with the sham group and other SCI subgroups,the subgroup at 1 day after SCI showed increased expression of the ferroptosis marker acyl-CoA synthetase long-chain family member 4 and the oxidative stress marker malondialdehyde in the injured spinal cord while glutathione in the injured spinal cord was lower.These findings with our bioinformatics results suggested that 1 day after SCI was the important period of ferroptosis progression.Bioinformatics analysis identified the following top ten hub ferroptosis genes in the subgroup at 1 day after SCI:STAT3,JUN,TLR4,ATF3,HMOX1,MAPK1,MAPK9,PTGS2,VEGFA,and RELA.Real-time polymerase chain reaction on rat spinal cord tissue confirmed that STAT3,JUN,TLR4,ATF3,HMOX1,PTGS2,and RELA mRNA levels were up-regulated and VEGFA,MAPK1 and MAPK9 mRNA levels were down-regulated.Ten potential compounds were predicted using the DSigDB database as potential drugs or molecules targeting ferroptosis to repair SCI.We also constructed a ferroptosis-related mRNA-miRNA-lncRNA network in SCI that included 66 lncRNAs,10 miRNAs,and 12 genes.Our results help further the understanding of the mechanism underlying ferroptosis in SCI.

Using network pharmacology and molecular docking to explore the mechanism of action of Huajiao against colon cancer

Background:The mechanism of Huajiao(Zanthoxylum bungeanum Maxim.),as a commonly used herbal medicine,has been suggested as a potential agent for colon cancer.This study aims to use network pharmacology and molecular docking to identify the bioactive constituents of Huajiao and the underlying mechanisms of cancer prevention.Methods:Putative components of Huajiao and their relevant targets were identified from the Traditional Chinese Medicine Systematic Pharmacology and Swiss target prediction database.Subsequently,targets interacting with colon cancer were collected using the databases of GeneCards,OMIM and Drugbank.Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology enrichment analyses were performed to explore the therapeutic signalling pathways related to Huajiao for carcinoma.P rotein-protein interaction and compound-target networks were constructed using Cytoscape 3.8.2.Finally,Discovery studio software was accustomed to identifying key genes and active components of Huajiao.Results:Seventeen potentially active compounds,197 interacting targets and 1,636 disease-related targets were collected,of which 111 cross-targets were obtained.A complete of twenty-two key targets were identified by PPI network analysis,including AKT1,TP53,TNF,JUN,IL6 and HSP90AA1.These key targets are significantly involved in biological processes and pathways,such as those involved in phosphatidylinositol 3-kinase signalling,promoting maturation,structural maintenance and proper regulation of specific target proteins,and regulating tumor cell growth arrest and apoptosis.KEGG enrichment showed that three signalling pathways were closely related to the cancer prevention,endocrine resistance and viral hepatitis pathways in carcinoma.AKT1,TP53,TNF,JUN,IL6 and HSP90AA1 were identified as the most vital genes and were validated by molecular docking simulations.Conclusion:The present study demonstrates that Huajiao produces preventive effects against colon cancer by modulating multiple components of multiple targets and pathways.Moreover,these data provide new insights into developing Huajiao compounds as new anti-colon cancer drugs.

Prediction of the anti-inflammatory mechanisms of curcumin by module-based protein interaction network analysis

Curcumin, the medically active component from Curcuma Tonga (Turmeric), is widely used to treat inflammatory diseases. Protein interaction network (PIN) analysis was used to predict its mechanisms of molecular action. Targets of curcumin were obtained based on ChEMBL and STITCH databases. Protein protein interactions (PPIs) were extracted from the String database. The PIN of curcumin was constructed by Cytoscape and the function modules identified by gene ontology (GO) enrichment analysis based on molecular complex detection (MCODE). A PIN of curcumin with 482 nodes and 1688 interactions was constructed, which has scale-free, small world and modular properties. Based on analysis of these function modules, the mechanism of curcumin is proposed. Two modules were found to be intimately associated with inflammation. With function modules analysis, the anti-inflammatory effects of curcumin were related to SMAD, ERG and mediation by the TLR family. TLR9 may be a potential target of curcumin to treat inflammation. (C) 2015 Chinese Pharmaceutical Association and Institute of Materia Medica, Chinese Academy of Medical Sciences. Production and hosting by Elsevier B.V.