Herein, we conducted four independent analyses on RNA interference (RNAi)-based therapy with computational and bioinformatic methods in order to target the evolutionarily conserved regions in SARS-CoV-2 genome, resulting in down-regulation or silencing its RNA. miRNAs are denoted to play a role in the resistance of some species to viral infections. A comprehensive analysis on the miRNAs available in the body of human, as wells as the miRNAs in bats and other species, were done to find efficient candidates with low side-effects in the human body. Moreover, the evolutionarily conserved regions in SARS-CoV-2 genome were considered for designing novel significant siRNA with high specificity. Multiple miRNAs and two siRNA were suggested as the possible efficient candidates with a high affinity to SARS-CoV-2 genome and low side effects. The suggested candidates are promising therapeutics for the experimental evaluations and may speed up the procedure of treatment design.

In this research project, we addressed these questions using computational methods:

See results in Analysis1.xlsx.

See results in Analysis2.xlsx.

See results in Analysis3.xlsx.

See results in Result and Data folder.

1. Install Python 3.x
2. Install biopython
3. Install IntaRNA
4. Install subprocess
5. Install Pandas

pip install biopython

conda install -c conda-forge -c bioconda intarna

pip install subprocess.run

pip install pandas

Alternatively, you can use IntaRNA WebTool for calculating MFE.

1. Finding UCRs: Candidate UCRs are calculated using codes in this repository.
2. Computing MFE : You can compute MFE with IntaRNA.py (address path of miRNA sequences and UCR files, then run the code) or use IntaRNA WebTool.
3. Investigating possible side-effects: For finding probable targets for candidate miRNA/ siRNA, we used mirDB WebTool. The top possible target is enriched on UniProt and Reactome.
4. Suggesting siRNAs: siDirect WebTool is used for designing potential siRNAs. You can find all results and data in Results and dataset folder in this repository.

The complete genome sequence of SARS-CoV-2 was obtained with accession No. NC045512.2 from the GeneBank database. The complete genome of betacoronavirus sequences from the NCBI database and sequences compiled by Ceraolo and Giorgi were considered for finding evolutionarily conserved regions. Besides, the sequences of known miRNAs in human and other species were downloaded from the miRNA registry, MirBase. We obtained the sequences of bat-specific miRNAs from the previously published paper by Huang et al.. Also, the miRNA-mRNA interaction data, as well as the free binding energy of interactions and the sequences of miRNAs and mRNAs involving in the interactions were collected from CLASH.

• Narjes Rohani, Fatemeh Ahmadi Moughari and Changiz Eslahchi Please do not hesitate to contact us if you have any question: Mail: n.rohani@mail.sbu.ac.ir

Please cite the study if you find this study helpful.