Computational prediction of potential siRNA and human miRNA sequences to silence orf1ab associated genes for future therapeutics against SARS-CoV-2

Abstract

The coronavirus disease 2019 (COVID-19) is an ongoing pandemic caused by an RNA virus termed as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). SARS-CoV-2 possesses an almost 30kbp long genome. The genome contains open-reading frame 1ab (ORF1ab) gene, the largest one of SARS-CoV-2, encoding polyprotein PP1ab and PP1a responsible for viral transcription and replication. Several vaccines have already been approved by the respective authorities over the world to develop herd immunity among the population. In consonance with this effort, RNA interference (RNAi) technology holds the possibility to strengthen the fight against this virus. Here, we have implemented a computational approach to predict potential short interfering RNAs including small interfering RNAs (siRNAs) and microRNAs (miRNAs), which are presumed to be intrinsically active against SARS-CoV-2. In doing so, we have screened miRNA library and siRNA library targeting the ORF1ab gene. We predicted the potential miRNA and siRNA candidate molecules utilizing an array of bioinformatic tools. By extending the analysis, out of 24 potential pre-miRNA hairpins and 131 siRNAs, 12 human miRNA and 10 siRNA molecules were sorted as potential therapeutic agents against SARS-CoV-2 based on their GC content, melting temperature (T m ), heat capacity (C p ), hybridization and minimal free energy (MFE) of hybridization. This computational study is focused on lessening the extensive time and labor needed in conventional trial and error based wet lab methods and it has the potential to act as a decent base for future researchers to develop a successful RNAi therapeutic.

Dysregulation of RNA interference components in COVID-19 patients

“…RNAi systems against SARS-CoV-2 using computational prediction approaches. They reported 24 pre-miRNA hairpins, 131 siRNAs, 12 human miRNA, and 10 siRNA molecules as active therapeutic agents against SARS-CoV-2 [28]. Previous studies have examined the antiviral defense potential of several miRNAs and siRNAs against some viruses including HIV-1 [29], Influenza [30], Zika [31] and Hepatitis C (HCV) [32].…”

Inhibition of SARS-CoV-2 Replication by a Small Interfering RNA Targeting the Leader Sequence

“…Several other in silico studies predicted siRNAs targeting ORF1ab [48][49][50][51], S gene [49,[51][52][53], ORF3 [49,51], E gene [49], M gene [49,51] and N gene [51,53] of SARS-CoV-2. Two in vitro studies further demonstrated a robust downregulation of S, M and N on the mRNA or protein levels by siRNAs in overexpression cell culture models [54,55].…”

Targeting genomic SARS-CoV-2 RNA with siRNAs allows efficient inhibition of viral replication and spread

“…For a more in-depth analysis of the SARS-CoV-2 variants that were defined by the WHO by the day of sequence retrieval as major variants of concern (VoC) or interest (VoI), we downloaded 20 000 sequences (each time considering only the latest submission dates) of each of the four VoC (WHO labels: Alpha, Beta, Gamma, and Delta variant) and all available sequences for the two VoI (WHO labels: Lambda and Mu variant) for which less sequences were available (848 and 5889). These included lineages that were defined by the Pango nomenclature system ( 27 ) as: B.1.1.7 and Q.x (Alpha variant); B.1.351, B.1.351.2 and B.1.351.3 (Beta variant), P.1 and P.1.x (Gamma variant), B.1.617.2 and AY.x (Delta variant), C.37 and C.37.1 (Lambda variant), as well as B.1.621 and B.1.621.1 (Mu variant). For each of the 12 siRNAs, a search was performed for the presence of the siRNA target site within each of the acquired data sets using an inhouse script written in Ruby programming language ( https://www.ruby-lang.org ).…”