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Dataset Information

In Silico and In Vitro development of novel small interfering RNAs (siRNAs) to inhibit SARS-CoV-2.


ABSTRACT: SARS-CoV-2 is causing severe to moderate respiratory tract infections, posing global health, social life, and economic threats. Our design strategy for siRNAs differs from existing studies through a step-by-step filtration process utilizing integrative bioinformatics protocols and web tools. Stage one: Multiple Sequence Alignment was employed to identify the most conserved areas. Stage two involves using various online tools, among the most reputable tools for building siRNA. The first filtration step of siRNA uses the Huesken dataset, estimating a 90 % experimental inhibition. The second filtration stage involves choosing the most suitable and targeted siRNA by utilizing thermodynamics and Target Accessibility of siRNAs. The final filtration step is off-target filtration using BLAST with

SUBMITTER: Taibe NS 

PROVIDER: S-EPMC12008453 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature