RNAi-mediated siRNA sequences to combat the COVID-19 pandemic with the inhibition of SARS-CoV2.

The outbreak of the COVID-19 pandemic has cost five million lives to date, and was caused by a positive-sense RNA virus named SARS-CoV2. The lack of drugs specific to SARS-CoV2, leads us to search for an effective and specific therapeutic approach. Small interfering RNA (siRNA) is able to activate the RNA interference (RNAi) pathway to silence the specific targeted gene and inhibit the viral replication, and it has not yet attracted enough attention as a SARS-CoV2 antiviral agent. It could be a potential weapon to combat this pandemic until the completion of full scale, effective mass vaccination. For this study, specific siRNAs were designed using a web-based bioinformatics tool (siDirect2.0) against 14 target sequences. These might have a high probability of silencing the essential proteins of SARS-CoV2. such as: 3CLpro/Mpro/nsp5, nsp7, Rd-Rp/nsp12, ZD, NTPase/HEL or nsp13, PLpro/nsp3, envelope protein (E), spike glycoprotein (S), nucleocapsid phosphoprotein (N), membrane glycoprotein (M), ORF8, ORF3a, nsp2, and its respective 5' and 3'-UTR. Among these potential drug targets, the majority of them contain highly conserved sequences; the rest are chosen on the basis of their role in viral replication and survival. The traditional vaccine development technology using SARS-CoV2 protein takes 6-8 months; meanwhile the virus undergoes several mutations in the candidate protein chosen for vaccine development. By the time the protein-based vaccine reaches the market, the virus would have undergone several mutations, such that the antibodies against the viral sequence may not be effective in restricting the newly mutated viruses. However, siRNA technology can make sequences based on real time viral mutation status. This has the potential for suppressing SARS-CoV2 viral replication, through RNAi technology.

Introduction

In December 2019, the World Health Organization (WHO) announced a new type of virus called Severe Acute Respiratory Syndrome Coronavirus 2 or briefly, SARS-CoV2. SARS-CoV2 gives rise to violent damage to the world as a pandemic (called COVID-19 disease) affecting more than 222 countries and territories (Worldometer) with 253,982,410 confirmed cases, including 5,114,571 fatalities (WHO) until November 2021. The world is in great need of effective measures to prevent or treat this pandemic. Many different types of therapeutic agents of other targets (antiviral, anti-malarial, anti-cancer, etc.) have been tested to determine their potential effectiveness against SARS-CoV2, but their efficacy has not yet been confirmed (Ghosh et al., 2020). Likewise, drugs used against SARS-CoV and MERS-CoV were initially found to be ineffective against SARS-CoV2 (Naqvi et al., 2020). The tendency of potential adaptive mutations of the SARS-CoV2 genome possibly made it extremely pathogenic, causing problems in the development of drugs and vaccines (Xu et al., 2020). The challenges for the treatment require a novel dimension, especially when we are in need of an effective antiviral agent.

RNAi is a specific post-transcriptional gene-silencing mechanism that can be activated via siRNA (Saadat, 2013) and has the potential to block pathogenic viral replication and further infection in animal cells (Ge et al., 2003). siRNA-silencing technology was used to restrict HCV, HIV (Wilson et al., 2003), SARS and MERS viral replication (Li et al., 2005; Wu et al., 2005; Yi et al., 2005).

Genetic variance analyses of the complete genome in 48,635 SARS-CoV2 samples, comparing it with the reference genome (Wuhan genome) NC_045512.2, revealed a fair average of 7.23 mutations per sample (Mercatelli and Giorgi, 2020). Genetic variances of SARS-CoV2 even within the same country are an obstacle to finding a universally applicable therapeutic agent (Biswas and Mudi, 2020; Toyoshima et al., 2020). This reason leads us to think about specific siRNA-based universal therapeutics by focusing on conserved and various potential targets in SARS-CoV2 genome reference sequences. This effort may pave the way for precision/personalized medicine to treat individuals infected with SARS-CoV2.

Genome SARS-CoV2 contains 14 Open Reading Frames (ORFs), and 27 proteins (A. Wu et al., 2020). ORF1a, as well as ORF1b, is translated as a single large poly-protein. The ORF1a contains two viral proteases; papain-like proteases or PLpro (non-structural protein 3 or nsp3), and main proteases or Mpro also designated as 3-chymotrypsin-like proteases or 3CLpro (non-structural protein 5 or nsp5). Recent clinical trials of multiple antiviral agents have targeted the proteases (Ghosh et al., 2020). The ORF1b contains viral RNA-dependent RNA polymerase (Rd-Rp), which is non-structural protein 12 or nsp12. The site identified, downstream to the Rd-Rp is coding for the viral helicase (non-structural protein 13 or nsp13) (Ghosh et al., 2020). Both ORF1a and ORF1b include highly preserved sequences among the annotated genomes of SARS-CoV2 and earlier beta coronaviruses like SARS and MERS (F. Wu et al., 2020). The envelope protein (E), spike glycoprotein (S), nucleocapsid phosphoprotein (N), and membrane glycoprotein (M) are considered to be potential drug/vaccine targets (Naqvi et al., 2020). By comparing the inflammatory pathways and cytokine responses during SARS-CoV, MERS-CoV, and SARS-CoV2 infections, it has been recognized that ORF8 triggers DNA synthesis and ORF3a triggers necrotic cell death. And also nsp2 does proofreading which is necessary for viral replication (Naqvi et al., 2020). The 5′ and 3′-UTR sequences are necessary for RNA replication and transcription (Wu et al., 2005).

The siRNAs can silence the targeted genes and also inhibit the replication of the virus. Similar studies were reported for the previous SARS viruses (Li et al., 2005).

In this study, siRNAs have been designed targeting specifically conserved sequences and also other potential drug targets. These are: nsp5, nsp3, nsp12, nsp7, nsp13, nsp3, envelope protein (E), spike glycoprotein (S), nucleoprotein (N), membrane protein (M), ORF8, ORF3a, nsp2, 5′- and 3′-UTR. These siRNA sequences have the probable capability to inhibit viral replication as well as further viral infection. These sequence designs might support COVID-19 management, if found effective in drug delivery through liposome.

Materials and methods

Sequence retrieval & manual extraction

The reference genome of the SARS-Cov2 [NC_045512.2] was achieved from the database available at the National Center for Biotechnological Information (NCBI) (NCBI (accessed 18 February 2021)) and we manually extracted the sequences for 3CLpro/Mpro or non-structural protein 5/nsp5 [NC_045512.2:10055-10972], PLpro or non-structural protein 3/nsp3 [NC_045512.2:2720-8554], Rd-Rp or non-structural protein 12/nsp12 [NC_045512.2:13442-16236], non-structural protein 7/nsp7 [NC_045512.2:11843-12091], spike glycoprotein (S) [NC_045512.2:21563-25384], envelope protein (E) [NC_045512.2:26245-26472], membrane glycoprotein (M) [NC_045512.2:26523-27191], nucleocapsid phosphoprotein/nucleoprotein (N) [NC_045512.2:28274-29533], Open Reading Frame 8 (ORF8) [NC_045512.2:27894-28259], Open Reading Frame 3a (ORF3a) [NC_045512.2:25393-26220], non-structural protein 2(nsp2) [NC_045512.2:806-2719], Untranslated Region 5′ (5′-UTR) [NC_045512.2:1-265] and Untranslated Region 3′ (3′-UTR) [NC_045512.2:29675-29903].

siRNA design principles

Ui-Tei, K., and colleagues prescribed the characteristics of the hugely functional siRNAs, named “Ui-Tei rule”. The siRNA chosen according to the Ui-Tei rule persuades the subsequent four ambiances concurrently: (a) A/U at region 1 from the 5′terminus of the siRNA guide strand, (b) G/C in region 19, (c) AU richness (AU ≥4) in regions 1–7, and (d) the absence of long GC stretches ≥10 (Ui-Tei et al., 2004).

siRNA design web-based tool

The web-based siRNA design siDirect2.0 Tool (siDirect version 2.0 (accessed 18 February 2021)) has been used. It is used to design functional and target-specific siRNAs, which was proposed by Naito, Y., and colleagues (Naito et al., 2009). The siRNAs are satisfactory according to the Ui-Tei rule chosen in the default parameter as stated by Ui-Tei, K., and colleagues (Naito and Ui-Tei, 2012).

Target sequence selection& functional siRNA designing

21 nt targets with 2 nt overhang highly functional sequences were selected and sequence-specific siRNAs were designed with the web-based siRNA design siDirect2.0 Tool (siDirect version 2.0 (accessed 18 February 2021)) according to the Ui-Tei rule.

Off-target effect-reduced siRNA sequence selection

The siRNAs (both guide and other passenger strands) with low melting temperature (Tm) were chosen to avoid the seed-dependent off-target silencing. Even though the benchmark was fixed as Tm of 21.5 °C (Ui-Tei et al., 2008), in this study we tried to select nearly Tm < 10 °C.

Near-perfect matched off-target gene elimination

In order to exclude the near-perfect matched non-target genes, the siDirect 2.0 homology search option was used, as its accuracy level has been found to the best of all available homology search engines. Both (guide and other passenger) strands of candidate functional siRNAs that have at minimum two inconsistencies to any other non-targeted transcripts were chosen (Naito and Ui-Tei, 2012).

Results

In this study siRNA-based specific sequences were designed for therapeutic purposes of SARS-CoV2 with siDirect2.0 (siDirect version 2.0 (accessed 18 February 2021)) by following all the above-mentioned procedures. They are listed in Table 1, Table 2, Table 3, Table 4, Table 5, Table 6 with the title of specific genes and also their location in the genome is mentioned in brackets.

Table 1

List of siRNAs with the specifications of nsp2 gene.

Target gene	Target position	Target sequence21 nt target + 2 nt overhang	RNA oligo sequences21 nt guide (5′ → 3′)21 nt passenger (5′ → 3′)	Seed duplex stability (Tm)
				Guide	Passenger
nsp2 (NC_045512.2:806-2719)	285–307	TCCCTTAAATTCCATAATCAAGA	UUGAUUAUGGAAUUUAAGGGACCUUAAAUUCCAUAAUCAAGA	8.7 °C	−4.3 °C
	541–563	CCCCAAAATGCTGTTGTTAAAAT	UUUAACAACAGCAUUUUGGGGCCAAAAUGCUGUUGUUAAAAU	7.2 °C	4.2 °C
	812–834	TTGAAATACTCCAAAAAGAGAAA	UCUCUUUUUGGAGUAUUUCAAGAAAUACUCCAAAAAGAGAAA	10.3 °C	4.6 °C
	1397–1419	GGGAAATTGTTAAATTTATCTCA	AGAUAAAUUUAACAAUUUCCCGAAAUUGUUAAAUUUAUCUCA	1.8 °C	5.3 °C
	1567–1589	TTGAATTTAGGTGAAACATTTGT	AAAUGUUUCACCUAAAUUCAAGAAUUUAGGUGAAACAUUUGU	5.3 °C	−4.3 °C

Table 2

List of siRNAs with the specifications of nsp3 gene.

Target gene	Target position	Target sequence21 nt target + 2 nt overhang	RNA oligo sequences21 nt guide (5′ → 3′)21 nt passenger (5′ → 3′)	Seed duplex stability (Tm)
				Guide	Passenger
PLpro/nsp3 (NC_045512.2:2720-8554)	1732–1754	TTGAAAACTGGTGATTTACAACC	UUGUAAAUCACCAGUUUUCAAGAAAACUGGUGAUUUACAACC	6.9 °C	10.3 °C
	88–110	AGGATTGATAAAGTACTTAATGA	AUUAAGUACUUUAUCAAUCCUGAUUGAUAAAGUACUUAAUGA	6.6 °C	8.7 °C
	609–631	GACTATTGAAGTGAATAGTTTTA	AAACUAUUCACUUCAAUAGUCCUAUUGAAGUGAAUAGUUUUA	4.6 °C	8.9 °C
	652–674	GACAATGTATACATTAAAAATGC	AUUUUUAAUGUAUACAUUGUCCAAUGUAUACAUUAAAAAUGC	−9.1 °C	6.7 °C
	727–749	GCCAATGTTTACCTTAAACATGG	AUGUUUAAGGUAAACAUUGGCCAAUGUUUACCUUAAACAUGG	7.2 °C	5.3 °C
	945–967	TGCTTATGAAAATTTTAATCAGC	UGAUUAAAAUUUUCAUAAGCACUUAUGAAAAUUUUAAUCAGC	2.1 °C	8.9 °C
	1172–1194	AGGAAGTTAAGCCATTTATAACT	UUAUAAAUGGCUUAACUUCCUGAAGUUAAGCCAUUUAUAACU	−8.0 °C	4.9 °C
	1579–1601	GTGCTTAAAAAGTGTAAAAGTGC	ACUUUUACACUUUUUAAGCACGCUUAAAAAGUGUAAAAGUGC	4.9 °C	−3.8 °C
	1590–1612	GTGTAAAAGTGCCTTTTACATTC	AUGUAAAAGGCACUUUUACACGUAAAAGUGCCUUUUACAUUC	7.2 °C	4.9 °C
	1743–1765	TTCAACTATACAGCGTAAATATA	UAUUUACGCUGUAUAGUUGAACAACUAUACAGCGUAAAUAUA	6.9 °C	6.3 °C
	1813–1835	TACTTTTACACCAGTAAAACAAC	UGUUUUACUGGUGUAAAAGUACUUUUACACCAGUAAAACAAC	8.2 °C	7.2 °C
	1997–2019	CAGCGTATAATGGTTATCTTACT	UAAGAUAACCAUUAUACGCUGGCGUAUAAUGGUUAUCUUACU	6.9 °C	8.5 °C
	2136–2158	AGGTGATAAAAGTGTATATTACA	UAAUAUACACUUUUAUCACCUGUGAUAAAAGUGUAUAUUACA	1.1 °C	8.9 °C
	2138–2160	GTGATAAAAGTGTATATTACACT	UGUAAUAUACACUUUUAUCACGAUAAAAGUGUAUAUUACACU	1.1 °C	−4.3 °C
	2387–2409	AAGGTAAAACATTTTATGTTTTA	AAACAUAAAAUGUUUUACCUUGGUAAAACAUUUUAUGUUUUA	6.9 °C	8.2 °C
	2490–2512	AGCATTAAATCACACTAAAAAGT	UUUUUAGUGUGAUUUAAUGCUCAUUAAAUCACACUAAAAAGU	4.9 °C	−10.3 °C
	2522–2544	CACAAGTTAATGGTTTAACTTCT	AAGUUAAACCAUUAACUUGUGCAAGUUAAUGGUUUAACUUCU	4.9 °C	4.9 °C
	2531–2553	ATGGTTTAACTTCTATTAAATGG	AUUUAAUAGAAGUUAAACCAUGGUUUAACUUCUAUUAAAUGG	−7.5 °C	8.2 °C
	2868–2890	TTCTTATGAACAATTTAAGAAAG	UUCUUAAAUUGUUCAUAAGAACUUAUGAACAAUUUAAGAAAG	7.1 °C	8.9 °C
	2913–2935	TGGTAAACAAGCTACAAAATATC	UAUUUUGUAGCUUGUUUACCAGUAAACAAGCUACAAAAUAUC	5.3 °C	7.2 °C
	3047–3069	GTCACTATAAACATATAACTTCT	AAGUUAUAUGUUUAUAGUGACCACUAUAAACAUAUAACUUCU	6.3 °C	6.3 °C
	3056–3078	AACATATAACTTCTAAAGAAACT	UUUCUUUAGAAGUUAUAUGUUCAUAUAACUUCUAAAGAAACU	7.1 °C	1.1 °C
	3172–3194	ACCATAAAACCAGTTACTTATAA	AUAAGUAACUGGUUUUAUGGUCAUAAAACCAGUUACUUAUAA	6.6 °C	−0.3 °C
	3224–3246	ACCCTAAGTTGGACAATTATTAT	AAUAAUUGUCCAACUUAGGGUCCUAAGUUGGACAAUUAUUAU	−1.8 °C	9.8 °C
	3524–3546	ATGTTAACAATGCAACTAATAAA	UAUUAGUUGCAUUGUUAACAUGUUAACAAUGCAACUAAUAAA	4.6 °C	7.2 °C
	3782–3804	CAGCAAATAATAGTTTAAAAATT	UUUUUAAACUAUUAUUUGCUGGCAAAUAAUAGUUUAAAAAUU	−9.1 °C	−1.4 °C
	3847–3869	GACAATTCTAGTCTTACTATTAA	AAUAGUAAGACUAGAAUUGUCCAAUUCUAGUCUUACUAUUAA	6.3 °C	6.9 °C
	88–110	GCCTTTTCTTAACAAAGTTGTTA	ACAACUUUGUUAAGAAAAGGCCUUUUCUUAACAAAGUUGUUA	10.3 °C	5.5 °C
	4041–4063	TACTAATTATATGCCTTATTTCT	AAAUAAGGCAUAUAAUUAGUACUAAUUAUAUGCCUUAUUUCU	10.9 °C	−8.0 °C
	4051–4073	ATGCCTTATTTCTTTACTTTATT	UAAAGUAAAGAAAUAAGGCAUGCCUUAUUUCUUUACUUUAUU	4.9 °C	10.9 °C
	4052–4074	TGCCTTATTTCTTTACTTTATTG	AUAAAGUAAAGAAAUAAGGCACCUUAUUUCUUUACUUUAUUG	6.6 °C	−4.3 °C
	4053–4075	GCCTTATTTCTTTACTTTATTGC	AAUAAAGUAAAGAAAUAAGGCCUUAUUUCUUUACUUUAUUGC	4.6 °C	2.1 °C
	4073–4095	TGCTACAATTGTGTACTTTTACT	UAAAAGUACACAAUUGUAGCACUACAAUUGUGUACUUUUACU	4.9 °C	6.9 °C
	4098–4120	AAGTACAAATTCTAGAATTAAAG	UUAAUUCUAGAAUUUGUACUUGUACAAAUUCUAGAAUUAAAG	6.9 °C	6.9 °C
	4220–4242	AACTGATAAATATTATAATTTGG	AAAUUAUAAUAUUUAUCAGUUCUGAUAAAUAUUAUAAUUUGG	−8.0 °C	8.9 °C
	4296–4318	AGGTGTTTTAATGTCTAATTTAG	AAAUUAGACAUUAAAACACCUGUGUUUUAAUGUCUAAUUUAG	6.9 °C	7.2 °C
	4452–4474	TTCTTTAGAAACTATACAAATTA	AUUUGUAUAGUUUCUAAAGAACUUUAGAAACUAUACAAAUUA	6.9 °C	7.1 °C
	4524–4546	GTGGTTTTTGGCATATATTCTTT	AGAAUAUAUGCCAAAAACCACGGUUUUUGGCAUAUAUUCUUU	3.5 °C	5.6 °C
	4600–4622	AGCTATTTTGCAGTACATTTTAT	AAAAUGUACUGCAAAAUAGCUCUAUUUUGCAGUACAUUUUAU	6.9 °C	−1.4 °C
	4610–4632	CAGTACATTTTATTAGTAATTCT	AAUUACUAAUAAAAUGUACUGGUACAUUUUAUUAGUAAUUCU	6.3 °C	6.9 °C
	4972–4994	CAGTTTAAAAGACCAATAAATCC	AUUUAUUGGUCUUUUAAACUGGUUUAAAAGACCAAUAAAUCC	−1.4 °C	−9.1 °C
	5100–5122	CTCTCATTTTGTTAACTTAGACA	UCUAAGUUAACAAAAUGAGAGCUCAUUUUGUUAACUUAGACA	9.8 °C	7.4 °C
	5153–5175	TGCCTATTAATGTTATAGTTTTT	AAACUAUAACAUUAAUAGGCACCUAUUAAUGUUAUAGUUUUU	6.3 °C	−2.3 °C
	5154–5176	GCCTATTAATGTTATAGTTTTTG	AAAACUAUAACAUUAAUAGGCCUAUUAAUGUUAUAGUUUUUG	4.6 °C	−8.0 °C
	5168–5190	TAGTTTTTGATGGTAAATCAAAA	UUGAUUUACCAUCAAAAACUAGUUUUUGAUGGUAAAUCAAAA	8.9 °C	7.7 °C

Table 3

List of siRNAs with the specifications of nsp5, nsp7 and nsp12 genes.

Target gene	Target position	Target sequence21 nt target + 2 nt overhang	RNA oligo sequences21 nt guide (5′ → 3′)21 nt passenger (5′ → 3′)	Seed duplex stability (Tm)
				Guide	Passenger
3CLpro/Mpro/nsp5 (NC_045512.2:10055-10972)	151–173	AACCCTAATTATGAAGATTTACT	UAAAUCUUCAUAAUUAGGGUUCCCUAAUUAUGAAGAUUUACU	5.3 °C	10.9 °C
	153–175	CCCTAATTATGAAGATTTACTCA	AGUAAAUCUUCAUAAUUAGGGCUAAUUAUGAAGAUUUACUCA	10.0 °C	−8.0 °C
	444–466	TGGTTTTAACATAGATTATGACT	UCAUAAUCUAUGUUAAAACCAGUUUUAACAUAGAUUAUGACU	8.7 °C	0.0 °C
	526–548	GACTTAGAAGGTAACTTTTATGG	AUAAAAGUUACCUUCUAAGUCCUUAGAAGGUAACUUUUAUGG	4.9 °C	11.7 °C
	538–560	AACTTTTATGGACCTTTTGTTGA	AACAAAAGGUCCAUAAAAGUUCUUUUAUGGACCUUUUGUUGA	10.3 °C	−1.4 °C
	594–616	AACTATTACAGTTAATGTTTTAG	AAAACAUUAACUGUAAUAGUUCUAUUACAGUUAAUGUUUUAG	5.3 °C	8.5 °C
	795–817	TGCTTCATTAAAAGAATTACTGC	AGUAAUUCUUUUAAUGAAGCACUUCAUUAAAAGAAUUACUGC	10.0 °C	8.9 °C
nsp7 (NC_045512.2:11843-12091)	62–84	GAGTAGAATCATCATCTAAATTG	AUUUAGAUGAUGAUUCUACUCGUAGAAUCAUCAUCUAAAUUG	6.9 °C	16.0 °C
	65–87	TAGAATCATCATCTAAATTGTGG	ACAAUUUAGAUGAUGAUUCUAGAAUCAUCAUCUAAAUUGUGG	−1.4 °C	16.2 °C
RdRp/nsp12 (NC_045512.2:13442-16236)	133–155	TTGCTAAATTCCTAAAAACTAAT	UAGUUUUUAGGAAUUUAGCAAGCUAAAUUCCUAAAAACUAAU	3.2 °C	−4.3 °C
	134–156	TGCTAAATTCCTAAAAACTAATT	UUAGUUUUUAGGAAUUUAGCACUAAAUUCCUAAAAACUAAUU	4.9 °C	2.1 °C
	297–319	GACTTCTTTAAGTTTAGAATAGA	UAUUCUAAACUUAAAGAAGUCCUUCUUUAAGUUUAGAAUAGA	6.9 °C	7.1 °C
	407–429	AGGTAATTGTGACACATTAAAAG	UUUAAUGUGUCACAAUUACCUGUAAUUGUGACACAUUAAAAG	6.9 °C	6.9 °C
	417–439	GACACATTAAAAGAAATACTTGT	AAGUAUUUCUUUUAAUGUGUCCACAUUAAAAGAAAUACUUGU	4.6 °C	6.9 °C
	457–479	ATGATGATTATTTCAATAAAAAG	UUUUAUUGAAAUAAUCAUCAUGAUGAUUAUUUCAAUAAAAAG	−1.4 °C	8.7 °C
	704–726	TTCTTATTATTCATTGTTAATGC	AUUAACAAUGAAUAAUAAGAACUUAUUAUUCAUUGUUAAUGC	7.2 °C	−8.0 °C
	792–814	TACATTAAGTGGGATTTGTTAAA	UAACAAAUCCCACUUAAUGUACAUUAAGUGGGAUUUGUUAAA	5.3 °C	4.6 °C
	1573–1595	ATGCACTTTTCGCATATACAAAA	UUGUAUAUGCGAAAAGUGCAUGCACUUUUCGCAUAUACAAAA	8.2 °C	10.3 °C
	1711–1733	TTCATCAAAAATTATTGAAATCA	AUUUCAAUAAUUUUUGAUGAACAUCAAAAAUUAUUGAAAUCA	7.4 °C	7.4 °C
	1800–1822	ATGTTAAAAACTGTTTATAGTGA	ACUAUAAACAGUUUUUAACAUGUUAAAAACUGUUUAUAGUGA	−2.3 °C	−9.1 °C
	2066–2088	TGCTAATAGTGTTTTTAACATTT	AUGUUAAAAACACUAUUAGCACUAAUAGUGUUUUUAACAUUU	7.2 °C	6.3 °C
	2103–2125	GCCAATGTTAATGCACTTTTATC	UAAAAGUGCAUUAACAUUGGCCAAUGUUAAUGCACUUUUAUC	10.3 °C	6.9 °C
	2136–2158	AACAAAATTGCCGATAAGTATGT	AUACUUAUCGGCAAUUUUGUUCAAAAUUGCCGAUAAGUAUGU	6.3 °C	−3.3 °C
	2236–2258	ACGCATATTTGCGTAAACATTTC	AAUGUUUACGCAAAUAUGCGUGCAUAUUUGCGUAAACAUUUC	6.9 °C	−1.8 °C
	2237–2259	CGCATATTTGCGTAAACATTTCT	AAAUGUUUACGCAAAUAUGCGCAUAUUUGCGUAAACAUUUCU	5.3 °C	−1.8 °C
	2340–2362	AACTTTAAGTCAGTTCTTTATTA	AUAAAGAACUGACUUAAAGUUCUUUAAGUCAGUUCUUUAUUA	7.1 °C	4.9 °C
	2362–2384	ATCAAAACAATGTTTTTATGTCT	ACAUAAAAACAUUGUUUUGAUCAAAACAAUGUUUUUAUGUCU	−1.4 °C	5.6 °C

Table 4

List of siRNAs with the specifications of nsp13, envelope protein (E) and nucleocapsid phosphoprotein (N) genes.

Target Gene	Target position	Target sequence21 nt target + 2 nt overhang	RNA oligo sequences21 nt guide (5′ → 3′)21 nt passenger (5′ → 3′)	Seed duplex stability (Tm)
				Guide	Passenger
ZD, NTPase/HEL/nsp13 (NC_045512.2:16237-18039)	260–282	GACAAGTTTTTGGTTTATATAAA	UAUAUAAACCAAAAACUUGUCCAAGUUUUUGGUUUAUAUAAA	−8.0 °C	3.2 °C
	269–291	TTGGTTTATATAAAAATACATGT	AUGUAUUUUUAUAUAAACCAAGGUUUAUAUAAAAAUACAUGU	6.9 °C	1.4 °C
	568–590	AACAGTAAAGTACAAATAGGAGA	UCCUAUUUGUACUUUACUGUUCAGUAAAGUACAAAUAGGAGA	10.9 °C	9.8 °C
	1410–1432	ATGCTTTAAAATGTTTTATAAGG	UUAUAAAACAUUUUAAAGCAUGCUUUAAAAUGUUUUAUAAGG	−7.5 °C	−3.8 °C
	1516–1538	TGGAGAAAAGCTGTCTTTATTTC	AAUAAAGACAGCUUUUCUCCAGAGAAAAGCUGUCUUUAUUUC	6.9 °C	10.3 °C
	1528–1550	GTCTTTATTTCACCTTATAATTC	AUUAUAAGGUGAAAUAAAGACCUUUAUUUCACCUUAUAAUUC	−2.3 °C	−9.7 °C
	1665–1687	TTGTAATGTAAACAGATTTAATG	UUAAAUCUGUUUACAUUACAAGUAAUGUAAACAGAUUUAAUG	6.9 °C	8.5 °C
	1700–1722	GAGCAAAAGTAGGCATACTTTGC	AAAGUAUGCCUACUUUUGCUCGCAAAAGUAGGCAUACUUUGC	11.6 °C	10.3 °C
Envelope protein (E) (NC_045512.2:26245-26472)	149–171	GTCTTGTAAAACCTTCTTTTTAC	AAAAAGAAGGUUUUACAAGACCUUGUAAAACCUUCUUUUUAC	5.5 °C	7.2 °C
	170–192	ACGTTTACTCTCGTGTTAAAAAT	UUUUAACACGAGAGUAAACGUGUUUACUCUCGUGUUAAAAAU	7.2 °C	14.6 °C
Nucleocapsid phosphor protein (N) (NC_045512.2:28274-29533)	1064–1086	AGCATATTGACGCATACAAAACA	UUUUGUAUGCGUCAAUAUGCUCAUAUUGACGCAUACAAAACA	6.9 °C	8.7 °C
	1021–1043	GACAAAGATCCAAATTTCAAAGA	UUUGAAAUUUGGAUCUUUGUCCAAAGAUCCAAAUUUCAAAGA	7.4 °C	14.8 °C

Table 5

List of siRNAs with the specifications of spike glycoprotein (S) gene.

Target Gene	Target position	Target sequence21 nt target + 2 nt overhang	RNA oligo sequences21 nt guide (5′ → 3′)21 nt passenger (5′ → 3′)	Seed duplex stability (Tm)
				Guide	Passenger
Spike glycoprotein (S) (NC_045512.2:21563-25384)	167–189	TACCTTTCTTTTCCAATGTTACT	UAACAUUGGAAAAGAAAGGUACCUUUCUUUUCCAAUGUUACU	12.1 °C	10.3 °C
	222–244	TGGTACTAAGAGGTTTGATAACC	UUAUCAAACCUCUUAGUACCAGUACUAAGAGGUUUGAUAACC	8.9 °C	11.3 °C
	310–332	TGGATTTTTGGTACTACTTTAGA	UAAAGUAGUACCAAAAAUCCAGAUUUUUGGUACUACUUUAGA	9.8 °C	−3.3 °C
	365–387	ACGCTACTAATGTTGTTATTAAA	UAAUAACAACAUUAGUAGCGUGCUACUAAUGUUGUUAUUAAA	6.9 °C	11.3 °C
	366–388	CGCTACTAATGTTGTTATTAAAG	UUAAUAACAACAUUAGUAGCGCUACUAAUGUUGUUAUUAAAG	1.4 °C	6.3 °C
	369–391	TACTAATGTTGTTATTAAAGTCT	ACUUUAAUAACAACAUUAGUACUAAUGUUGUUAUUAAAGUCU	−4.3 °C	6.9 °C
	390–412	CTGTGAATTTCAATTTTGTAATG	UUACAAAAUUGAAAUUCACAGGUGAAUUUCAAUUUUGUAAUG	7.2 °C	7.4 °C
	413–435	ATCCATTTTTGGGTGTTTATTAC	AAUAAACACCCAAAAAUGGAUCCAUUUUUGGGUGUUUAUUAC	6.9 °C	−3.3 °C
	414–436	TCCATTTTTGGGTGTTTATTACC	UAAUAAACACCCAAAAAUGGACAUUUUUGGGUGUUUAUUACC	−0.3 °C	−3.3 °C
	486–508	TGCGAATAATTGCACTTTTGAAT	UCAAAAGUGCAAUUAUUCGCACGAAUAAUUGCACUUUUGAAU	10.3 °C	1.8 °C
	540–562	AGGAAAACAGGGTAATTTCAAAA	UUGAAAUUACCCUGUUUUCCUGAAAACAGGGUAAUUUCAAAA	7.4 °C	10.3 °C
	548–570	AGGGTAATTTCAAAAATCTTAGG	UAAGAUUUUUGAAAUUACCCUGGUAAUUUCAAAAAUCUUAGG	5.3 °C	−0.3 °C
	568–590	AGGGAATTTGTGTTTAAGAATAT	AUUCUUAAACACAAAUUCCCUGGAAUUUGUGUUUAAGAAUAU	7.1 °C	7.4 °C
	569–591	GGGAATTTGTGTTTAAGAATATT	UAUUCUUAAACACAAAUUCCCGAAUUUGUGUUUAAGAAUAUU	6.9 °C	5.3 °C
	583–605	AAGAATATTGATGGTTATTTTAA	AAAAUAACCAUCAAUAUUCUUGAAUAUUGAUGGUUAUUUUAA	−0.3 °C	−1.8 °C
	726–748	TGCTTTACATAGAAGTTATTTGA	AAAUAACUUCUAUGUAAAGCACUUUACAUAGAAGUUAUUUGA	4.6 °C	6.9 °C
	824–846	TTCTATTAAAATATAATGAAAAT	UUUCAUUAUAUUUUAAUAGAACUAUUAAAAUAUAAUGAAAAU	8.9 °C	−7.5 °C
	934–956	ATCTATCAAACTTCTAACTTTAG	AAAGUUAGAAGUUUGAUAGAUCUAUCAAACUUCUAACUUUAG	9.8 °C	8.9 °C
	977–999	TTGTTAGATTTCCTAATATTACA	UAAUAUUAGGAAAUCUAACAAGUUAGAUUUCCUAAUAUUACA	−8.0 °C	6.9 °C
	986–1008	TTCCTAATATTACAAACTTGTGC	ACAAGUUUGUAAUAUUAGGAACCUAAUAUUACAAACUUGUGC	10.3 °C	−2.7 °C
	1245–1267	TGGAAAGATTGCTGATTATAATT	UUAUAAUCAGCAAUCUUUCCAGAAAGAUUGCUGAUUAUAAUU	3.5 °C	5.3 °C
	1254–1276	TGCTGATTATAATTATAAATTAC	AAUUUAUAAUUAUAAUCAGCACUGAUUAUAAUUAUAAAUUAC	−8.0 °C	8.7 °C
	1577–1599	GACCTAAAAAGTCTACTAATTTG	AAUUAGUAGACUUUUUAGGUCCCUAAAAAGUCUACUAAUUUG	6.3 °C	−3.8 °C
	1578–1600	ACCTAAAAAGTCTACTAATTTGG	AAAUUAGUAGACUUUUUAGGUCUAAAAAGUCUACUAAUUUGG	4.6 °C	−3.8 °C
	1587–1609	GTCTACTAATTTGGTTAAAAACA	UUUUUAACCAAAUUAGUAGACCUACUAAUUUGGUUAAAAACA	0.0 °C	6.3 °C
	2143–2165	CCCACAAATTTTACTATTAGTGT	ACUAAUAGUAAAAUUUGUGGGCACAAAUUUUACUAUUAGUGU	2.8 °C	5.3 °C
	2271–2293	CAGTTTTTGTACACAATTAAACC	UUUAAUUGUGUACAAAAACUGGUUUUUGUACACAAUUAAACC	−1.4 °C	5.6 °C
	2902–2924	TCCAATTTTGGTGCAATTTCAAG	UGAAAUUGCACCAAAAUUGGACAAUUUUGGUGCAAUUUCAAG	7.4 °C	−3.3 °C

Table 6

List of siRNAs with the specifications of membrane glycoprotein (M), ORF3a, ORF8, 3′-UTR and 5′-UTR genes.

Target gene	Target position	Target sequence21 nt target + 2 nt overhang	RNA oligo sequences21 nt guide (5′ → 3′)21 nt passenger (5′ → 3′)	Seed duplex stability (Tm)
				Guide	Passenger
Membrane glycoprotein (M) (NC_045512.2:26523-27191)	136–158	TTGTATATAATTAAGTTAATTTT	AAUUAACUUAAUUAUAUACAAGUAUAUAAUUAAGUUAAUUUU	4.6 °C	−5.9 °C
	203–225	CTGCTGTTTACAGAATAAATTGG	AAUUUAUUCUGUAAACAGCAGGCUGUUUACAGAAUAAAUUGG	−10.3 °C	11.8 °C
	206–228	CTGTTTACAGAATAAATTGGATC	UCCAAUUUAUUCUGUAAACAGGUUUACAGAAUAAAUUGGAUC	11.3 °C	11.8 °C
ORF3a (NC_045512.2:25393-26220)	402–424	TTCCAAAAACCCATTACTTTATG	UAAAGUAAUGGGUUUUUGGAACCAAAAACCCAUUACUUUAUG	4.9 °C	5.6 °C
	403–425	TCCAAAAACCCATTACTTTATGA	AUAAAGUAAUGGGUUUUUGGACAAAAACCCAUUACUUUAUGA	6.6 °C	12.6 °C
ORF8 (NC_045512.2:27894-28259)	1–23	ATGAAATTTCTTGTTTTCTTAGG	UAAGAAAACAAGAAAUUUCAUGAAAUUUCUUGUUUUCUUAGG	5.5 °C	0.4 °C
	243–265	TTCCTGTTTACCTTTTACAATTA	AUUGUAAAAGGUAAACAGGAACCUGUUUACCUUUUACAAUUA	7.2 °C	11.8 °C
	244–266	TCCTGTTTACCTTTTACAATTAA	AAUUGUAAAAGGUAAACAGGACUGUUUACCUUUUACAAUUAA	6.9 °C	14.7 °C
	307–329	TCGTTCTATGAAGACTTTTTAGA	UAAAAAGUCUUCAUAGAACGAGUUCUAUGAAGACUUUUUAGA	3.2 °C	13.4 °C
3′-UTR (NC_045512.2:29675-29903)	126–148	GCCCTAATGTGTAAAATTAATTT	AUUAAUUUUACACAUUAGGGCCCUAAUGUGUAAAAUUAAUUU	−9.7 °C	11.6 °C
	127–149	CCCTAATGTGTAAAATTAATTTT	AAUUAAUUUUACACAUUAGGGCUAAUGUGUAAAAUUAAUUUU	−10.3 °C	13.5 °C
	132–154	ATGTGTAAAATTAATTTTAGTAG	ACUAAAAUUAAUUUUACACAUGUGUAAAAUUAAUUUUAGUAG	−4.3 °C	7.2 °C
	192–214	ATGACAAAAAAAAAAAAAAAAAA	UUUUUUUUUUUUUUUUGUCAUGACAAAAAAAAAAAAAAAAAA	−11.3 °C	5.6 °C
	194–216	GACAAAAAAAAAAAAAAAAAAAA	UUUUUUUUUUUUUUUUUUGUCCAAAAAAAAAAAAAAAAAAAA	−11.3 °C	−11.3 °C
5′-UTR (NC_045512.2:1-265)	123–145	CGCAGTATAATTAATAACTAATT	UUAGUUAUUAAUUAUACUGCGCAGUAUAAUUAAUAACUAAUU	6.3 °C	6.3 °C
	125–147	CAGTATAATTAATAACTAATTAC	AAUUAGUUAUUAAUUAUACUGGUAUAAUUAAUAACUAAUUAC	4.6 °C	−8.0 °C

Discussion

Due to the advancement of modern technologies, it could be possible to produce a vaccine in a shorter time but the acquisition of knowledge related to its effect on the human body may take a much longer time; maybe years or decades.

The question still remains unanswered- how can we combat the waves of COVID-19 disease during the vaccine trial period, as an effective drug does not exist?

Thus, antiviral drugs specific to SARS-CoV2 can be designed and developed by targeting conserved enzymes such as: 3C-like protease or main protease (3CLpro/Mpro or non-structural protein 5/nsp5), non-structural protein 7/nsp7, RNA dependent RNA polymerase shortly Rd-Rp or non-structural protein 12/nsp12, papain-like protease (PLpro or non-structural protein 3/nsp3), and non-structural protein 13/nsp13 (also known as ZD, NTPase/HEL) (Zumla et al., 2016; Naqvi et al., 2020). These drug targets were confirmed by executing sequence analysis of potential drug target proteins in SARS-CoV2 beside viruses called SARS-CoV and MERS. Also, it was observed that the envelope protein (E), spike glycoprotein (S), nucleocapsid phosphoprotein (N), and membrane glycoprotein (M) are considered as potential drug/vaccine targets (Naqvi et al., 2020). By comparing the pathways in inflammation, and cytokine responses during SARS-CoV, MERS-CoV, and SARS-CoV2 infections, it was revealed that DNA synthesis is triggered by ORF8, while necrotic cell death is triggered by ORF3a. And also nsp2 is necessary for proofreading of viral replication (Naqvi et al., 2020). Both sequences of the 5′ and 3′-UTR are crucial for RNA replication and transcription (Wu et al., 2005).

RNA interference (RNAi) is a widely applied approach by which small interfering RNA (siRNA) also known as silencing RNA, silence a specific target gene with a perfectly complementary sequence, for the purpose of therapeutic usage in human diseases (Ketting, 2011). siRNA is typically 21 nt in length, and is the functional agent in RNAi, and acts as a guide for specific mRNA degradation (Elbashir et al., 2001a; Elbashir et al., 2001b). In the mammal family, siRNA is thought to have potential, not only for the gene silencing necessary for functional genomics, but also for medicinal goals, including antiviral therapy (Gitlin and Andino, 2003; Saadat, 2013).

To design specific and effective siRNA (21 nt), a practical guideline has been proposed by Ui-Tei, K., and colleagues named the “Ui-Tei rule”. The siRNA chosen according to the Ui-Tei rule persuades the subsequent four ambiances concurrently: (a) A/U in region 1 from the 5′terminus of the siRNA guide strand, (b) G/C in region 19, (c) AU richness (AU ≥4) in regions 1–7, and (d) the absence of long GC stretches ≥10 (Ui-Tei et al., 2004). To avoid the seed-dependent off-target effects, choosing siRNAs with a low melting temperature (Tm) of the seed-target duplex can minimize the seed-dependent off-target silencing. The melting temperature (Tm) of 21.5 °C may serve as the benchmark (Naito and Ui-Tei, 2012) but the seed duplex selected here was nearly Tm < 10 °C. The siRNAs that have near-perfect matches to any other non-targeted transcripts were excluded by comparing both their strands, having at minimum two mismatches to any other non-targeted transcripts (Naito and Ui-Tei, 2012). siDirect2.0 (siDirect version 2.0 (accessed 18 February 2021)) provides a functional, target-specific siRNA design web-based tool according to the procedures mentioned above (Naito et al., 2009). siDirect 2.0 would be a more suitable and sensitive homology search engine for short sequences, in comparison to other search engines (Naito and Ui-Tei, 2012).

Conclusion

In conclusion, it can be said that our designed RNAi sequences specific for SARS-CoV2 would be a potential weapon against COVID-19 disease all over the world. Nebulization or suspension in the systemic circulation by using a liposome-based delivery system might be an appropriate mode of administration. Further experimental validation and related trials are needed to confirm these findings.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.