Construction of microRNA-messenger RNA negative regulatory network and screening of potential therapeutic drugs in Chikungunya virus infection

Tang Yujie; Zhao Peng; Hou Chuandong; Zhang Haojun; Sun Xin; Huang Lei; Lu Xuechun

doi:10.3760/j.issn.1673-4777.2026.04.014

Abstract：Objective To reveal the regulatory mechanism of microRNA(miR)during Chikungunya virus(CHIKV)infection and predict potential therapeutic drugs for CHIKV infection,this study integrating multi-omics analysis methods based on public multi-omics databases of CHIKV.Methods By analyzing multiple datasets(GSE49985,GSE49884,GSE143390)in the Gene Expression Omnibus database,the limma package of R language was used to identify differentially expressed messenger RNAs(DEmRNAs)and differentially expressed miRs(DEmiRs).The miRTarBase,miRDB and TargetScanHuman databases were applied to predict the target genes of DEmiRs,and the miR-mRNA negative regulatory network in CHIKV infection was constructed.Finally,potential therapeutic drugs were predicted based on the EpiMed platform,Connectivity Map database and high-throughput virtual screening.Results A total of 1134 DEmRNAs and 54 DEmiRs were identified in this study.Gene Ontology analysis showed that DEmRNAs were significantly involved in biological processes such as cell cycle,chromosome segregation and protein folding.Kyoto Encyclopedia of Genes and Genomes analysis indicated that DEmRNAs were enriched in pathways including viral infection,protein processing,lysosome and neurodegenerative diseases.The miR-mRNA negative regulatory network contained 29 pairs of up-regulated miR with down-regulated mRNA and 90 pairs of down-regulated miR with up-regulated mRNA.The maximal clique centrality algorithm in the cytoHubba plug-in of Cytoscape software was used to screen the predicted target genes and construct a sub-regulatory network.Through drug prediction,94 candidate drugs were identified by the EpiMed platform and 2907 candidate drugs were screened out by the Connectivity Map database.Comprehensive evaluation was performed via high-throughput virtual screening,and finally 5 potential therapeutic drugs associated with typical clinical symptoms of CHIKV infection were determined,including clonazepam,nevirapine,itracon-azole,pimecrolimus and meloxicam.Conclusions This study constructed the CHIKV infection-related miR-mRNA negative regulatory network and screened key genes,and further predicted 5 potential candidate drugs by combining drug repurposing and virtual screening,which provides systems biology clues and candidate resources for targeted intervention of CHIKV.