Department of Biochemistry and Molecular Biology, Laboratory of Population Genetics, University of Dhaka, Dhaka, 1000, Bangladesh.
Department of Biochemistry and Molecular Biology, Systems Cell-Signalling Laboratory, University of Dhaka, Dhaka, 1000, Bangladesh.
Future Microbiol. 2022 Apr;17:449-463. doi: 10.2217/fmb-2021-0130. Epub 2022 Mar 14.
To predict siRNAs as a therapeutic intervention for highly infectious new variants of SARS-CoV-2. Conserved coding sequence regions of 11 SARS-CoV-2 proteins were used to construct siRNAs through sampling of metadata comprising 214,256 sequences. Predicted siRNAs S1: 5'-UCAUUGAGAAAUGUUUACGCA-3' and S2: 5'-AAAGACAUCAGCAUACUCCUG-3' against RdRp of SARS-CoV-2 satisfied all the stringent filtering processes and showed good binding characteristics. The designed siRNAs are expected to inhibit viral replication and transcription of various coronavirus strains encompassing variants of concern and interest. The predicted siRNAs are expected to be potent against SARS-CoV-2, and following and validations may be considered as potential therapeutic measures.
为预测作为治疗干预手段的 siRNA,针对 11 种 SARS-CoV-2 蛋白的保守编码序列区域,通过对包含 214256 条序列的元数据进行采样,构建了 siRNAs。针对 SARS-CoV-2 RdRp 的预测 siRNA S1:5'-UCAUUGAGAAAUGUUUACGCA-3' 和 S2:5'-AAAGACAUCAGCAUACUCCUG-3' 通过了所有严格的过滤过程,显示出良好的结合特性。设计的 siRNAs有望抑制各种冠状病毒株的病毒复制和转录,包括关注和感兴趣的变体。预测的 siRNAs有望对 SARS-CoV-2 有效,并且在后续验证后,可能被视为潜在的治疗措施。