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• W3084159548 endingPage "2468" @default.
• W3084159548 startingPage "2454" @default.
• W3084159548 abstract "Abstract The newly identified SARS CoV2 has become a global pandemic since December 2019. Various researchers are trying to design a vaccine candidate against the virus. On the other hand, another group is focussing on repurposing approved or clinically tested drugs for treatment. However, there is always a search for alternative therapies. Thus, we propose an alternative approach apart from chemotherapy that is the usage of miRNA as novel antisense therapy to cure SARS CoV2 infected patients. To address the objective, miRNAs have been designed by targeting the genome of SARS CoV2 (Indian isolate). First, the open reading frames in the viral genome have been identified, and the proteins encoded by those open reading frames have been predicted. Using computational biology, several miRNAs have been designed and their probability to bind to a viral gene has been predicted. In addition, miRNA target mining in the host cell has been done to rule out the possibility of non‐specific binding of the miRNAs. The miRNAs having the highest chances to bind to the viral genome have been converted into pre‐miRNAs, and their interaction with dicer endoribonuclease has been studied by molecular docking. Results revealed that the pre‐miRNAs interact with the RNAse III 2 domain of dicer. Thus, it is predicted that the pre‐miRNAs after delivery to the infected host cell will be processed by dicer to generate mature miRNAs that will target the SARS CoV2 viral genome. Therefore, miRNA therapy can be an alternative approach for the treatment of SARS CoV2 infection." @default.
• W3084159548 created "2020-09-14" @default.
• W3084159548 creator A5016383025 @default.
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• W3084159548 date "2020-09-10" @default.
• W3084159548 modified "2023-09-26" @default.
• W3084159548 title "Targeting <scp>SARS CoV2</scp> (Indian isolate) genome with <scp>miRNA</scp>: An in silico study" @default.
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• W3084159548 doi "https://doi.org/10.1002/iub.2373" @default.
• W3084159548 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32909697" @default.
• W3084159548 hasPublicationYear "2020" @default.
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