{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Bie Y"],"funding":["Chinese Academy of Sciences","Ministry of Science and Technology of the People's Republic of China","National Natural Science Foundation of China","National Key Research and Development Program of China"],"pagination":["645-654"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11401469"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["39(4)"],"pubmed_abstract":["The increasing emergence and re-emergence of RNA virus outbreaks underlines the urgent need to develop effective antivirals. RNA interference (RNAi) is a sequence-specific gene silencing mechanism that is triggered by small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs), which exhibits significant promise for antiviral therapy. AGO2-dependent shRNA (agshRNA) generates a single-stranded guide RNA and presents significant advantages over traditional siRNA and shRNA. In this study, we applied a logistic regression algorithm to a previously published chemically siRNA efficacy dataset and built a machine learning-based model with high predictive power. Using this model, we designed siRNA sequences targeting diverse RNA viruses, including human enterovirus A71 (EV71), Zika virus (ZIKV)"],"journal":["Virologica Sinica"],"pubmed_title":["Design of antiviral AGO2-dependent short hairpin RNAs."],"pmcid":["PMC11401469"],"funding_grant_id":["2023YFC2305900","82172269","U21A20423","82222028"],"pubmed_authors":["Qiu Y","Bie Y","Zhang J","Chen J","Zhang Y","Huang M","Zhang L","Zhou X"],"additional_accession":[]},"is_claimable":false,"name":"Design of antiviral AGO2-dependent short hairpin RNAs.","description":"The increasing emergence and re-emergence of RNA virus outbreaks underlines the urgent need to develop effective antivirals. RNA interference (RNAi) is a sequence-specific gene silencing mechanism that is triggered by small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs), which exhibits significant promise for antiviral therapy. AGO2-dependent shRNA (agshRNA) generates a single-stranded guide RNA and presents significant advantages over traditional siRNA and shRNA. In this study, we applied a logistic regression algorithm to a previously published chemically siRNA efficacy dataset and built a machine learning-based model with high predictive power. Using this model, we designed siRNA sequences targeting diverse RNA viruses, including human enterovirus A71 (EV71), Zika virus (ZIKV)","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Aug","modification":"2026-07-15T13:10:24.383Z","creation":"2025-04-06T12:28:51.534Z"},"accession":"S-EPMC11401469","cross_references":{"pubmed":["38734183"],"doi":["10.1016/j.virs.2024.05.001"]}}