Computational Identification of Small Interfering RNA Targets in SARS-CoV-2

Dear Editor,

At the end of 2019, a new virus, called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was reported (Benvenuto et al. 2020; Zhu et al. 2020). The sequences of SARS-CoV-2 reported by different research groups demonstrated that it is a positive strand RNA virus. The sequence of SARS-CoV-2 is approximately 30 kb long, and could encodes spike, envelope, membrane, nucleocapsid proteins, etc. (Phan 2020). These proteins are responsible for replicating the viral genome as well as generating nested transcripts that are used in the synthesis of the viral proteins.

As of April 3 2020, there was more than 1 million cases of SARS-COV-2 reported to World Health Organization with 50, 000 deaths globally. However, there have been no effective measures to prevent or treat the severe complications caused by SARS-COV-2.

RNA interference (RNAi) is a native and specific post-transcriptional gene silencing mechanism (Bobbin and Rossi 2016). The progress initiated by double-stranded RNA (dsRNA) to manipulate gene expression (RNAi) has been proved highly effective, at least 10 times more effective than either using sense or antisense RNAs alone (Chalk and Sonnhammer 2002). The RNAi triggered by dsRNA is a phenomenon of homology-dependent gene silencing and may play certain roles in affecting the process of virus expression and proliferation. Recently, several reports have demonstrated the use of RNAi in blocking virus infection and replication in animal cells (Ge et al. 2003), suggesting that the small interfering RNA (siRNA, 21–25 nt long) plays an important role in RNAi-related gene silencing pathways (Elbashir et al. 2001). Progress has been made in anti-HIV and anti-HCV drug design by applying the method of RNA interference (Wilson et al. 2003). The effectiveness of siRNA for inhibiting SARS coronavirus genes expression was also demonstrated by Shi et al. (2005). Besides silencing the targeted genes, the siRNAs can also inhibit the replication of the virus. For example, it has been demonstrated that, by targeting the Leader sequence of SARS-CoV, the siRNA demonstrate a strong inhibitory effect on SARS-CoV replication (Li et al. 2005). More recently, a CRISPR/Cas13d system was proposed for the treatment of SARS-COV-2 (Nguyen et al. 2020). These results indicate that both RNAi and CRISPR/Cas technology might become potential therapeutic approaches for treating viral diseases.

Accordingly, as complementary to the CRISPR/Cas13d system, we proposed an RNAi based strategy that might interfere the gene expression and block the replication of SARS-COV-2. The main idea of this strategy is to search for siRNA targets in the virus genome, which will be recognized and cleaved by the RNA-induced silencing complex (RISC).

In this work, we performed theoretical predictions of the potential siRNA targets in the virus genome. We firstly collected the representative SARS-COV-2 genome (MN908947, https://www.ncbi.nlm.nih.gov/nuccore/MN908947) and the mutation information of the SARS-COV-2 genomes from the 2019nCoVR database (Zhao et al. 2020), which is available at https://bigd.big.ac.cn/ncov/. The 2019nCoVR database not only integrates genomic and proteomic sequences of SARS-COV-2 from different resources, but also provides a series of scientific services, such as variation visualization, variation annotations, AI diagnosis, etc.

Next, we folded the SARS-COV-2 genome (MN908947) in a window of 3000 nucleotides with the step of 1500 nucleotides by using RNAstructure (version 4.5) program (Bellaousov et al. 2013). Only those 21–25 nt long non-base-paired regions can be served as the potential targets of siRNA (Huang et al. 2008), which is called free segments. The long non-base-paired region containing one or several short stems (total length of stems 1–3 base pairs), called quasi-free segments (Ji and Luo 2004), was also considered in the present work.

A given RNA sequence segment may have different configurations of secondary structure with lower free energy. The total frequency of a segment occurring in non-base-paired region of different folds (20 folds are selected for each segment) is called appearance rate (AR). If each quasi-free case is multiplied by a reduced factor in numeration, namely, by 0.9 for 1 base pair, 0.8 for 2 base pair, and 0.7 for 3 base pairs (base pairs may be continuous in structure or disconnected) then the total number of folds is called reduced appearance rate (RAR) (Ji and Luo 2004).

To guarantee the safety of the designed drug, we further performed alignment of the free and quasi-free segments with human genome (hg 38) by using BLAST and deleted the matching ones in siRNA target candidates.

Finally, we obtained nine potential siRNA targets in the SARS-COV-2 genome (MN908947). The information about their position and region in the virus genome, length, AR and RAR was provided in Table 1.

In addition, we also analyzed the mutations of the target sequences by comparing all the 143 high quality strains in the 2019nCoVR database (as of March 15, 2020). SNP were found in two of the nine target sequences (indicated by bold character in Table 1). For the potential target 'AAUAGUUUAAAAAUUACAGAAGA', only one SNP was found in the strain BetaCoV/Wuhan/HBCDC-HB-05/2020, which is a coding_sequence_variant that changes the coding sequence. For 'CAACUAUAAAUUAAACACAGA', the SNP was found in the strain BetaCoV/Singapore/6/2020 and BetaCoV/Singapore/2/2020, respectively, which is a missense_variant that changes G to A resulting in a different amino acid sequence. These results indicate that the selected targets are conserved among the existing SARS-COV-2 genomes.

Although there are still some challenges that needed to be overcome for the clinic applications of siRNA, progresses have been made to solve the fundamental problems, such as off-target effects and effective delivery. For example, the position-specific chemical modification of siRNAs could can significantly reduce off targeting; safe and effective in vivo delivery systems have also been developed, such as nanoparticles, cationic lipids, antibodies, cholesterol, aptamers delivery strategies. Therefore, we hope that the above results would be useful in drug design and treatments against SARS-COV-2.