Computational Design and Experimental Evaluation of MERS-CoV siRNAs in Selected Cell Lines.

Middle East respiratory syndrome coronavirus (MERS-CoV) is caused by a well-known coronavirus first identified in a hospitalized patient in the Kingdom of Saudi Arabia. MERS-CoV is a serious pathogen affecting both human and camel health globally, with camels being known carriers of viruses that spread to humans. In this work, MERS-CoV genomic sequences were retrieved and analyzed by multiple sequence alignment to design and predict siRNAs with online software. The siRNAs were designed from the orf1ab region of the virus genome because of its high sequence conservation and vital role in virus replication. The designed siRNAs were used for experimental evaluation in selected cell lines: Vero cells, HEK-293-T, and Huh-7. Virus inhibition was assessed according to the cycle threshold value during a quantitative real-time polymerase chain reaction. Out of 462 potential siRNAs, we filtered out 21 based on specific selection criteria without off-target effect. The selected siRNAs did not show any cellular toxicity in the tested cell lines at various concentrations. Based on our results, it was obvious that the combined use of siRNAs exhibited a reduction in MERS-CoV replication in the Vero, HEK-293-T, and Huh-7 cell lines, with the highest efficacy displayed in the Vero cells.

Delivery of siRNAs against MERS-CoV in Vero and HEK-293 cells: A comparative evaluation of transfection reagents.

Background: A new coronavirus was identified in Jeddah, Saudi Arabia in 2012 and designated as Middle East Respiratory Syndrome Coronavirus (MERS-CoV). To date, this virus has been reported in 27 countries. The virus transmission to humans has already been reported from camels. Currently, there is no vaccine or antiviral therapy available against this virus. Methods: The siRNAs were in silico predicted, designed, and chemically synthesized by using the MERS-CoV-orf1ab region as a target. The antiviral activity was experimentally evaluated by delivering the siRNAs with Lipofectamine™ 2000 and JetPRIMER as transfection reagents in both Vero cell and HEK-293-T cell lines at two different concentrations (10.0 nM and 5.0 nM). The Ct value of quantitative Real-Time PCR (qRT-PCR) was used to calculate and determine the reduction of viral RNA level in both cell supernatant and cell lysate isolated from both cell lines. Results: The sequence alignment resulted in the selection of highly conserved regions. The orf1ab region was used to predict and design the siRNAs and a total of twenty-one siRNAs were finally selected from four hundred and twenty-six siRNAs generated by online software. Inhibition of viral replication and significant reduction of viral RNA was observed against selected siRNAs in both cell lines at both concentrations. Based on the Ct value, the siRNAs # 11, 12, 18, and 20 were observed to be the best performing in both cell lines at both concentrations. Conclusion: Based on the results and data analysis, it is concluded that the use of two different transfection reagents was significantly effective. But the Lipofectamine™ 2000 was found to be a better transfection reagent than the JetPRIMER for the delivery of siRNAs in both cell lines.

In silico prediction and experimental evaluation of potential siRNAs against SARS-CoV-2 inhibition in Vero E6 cells.

Objective: The acute cases of pneumonia (COVID-19) were first reported from China in December 2019, and the pathogen was identified as SARS-CoV-2. Currently, many vaccines have been developed against this virus by using multiple genes, applying different platforms, and used for the vaccinations of the human population. Spike protein genes play an important role in host cell attachment and viral entry and have been extensively used for the development of vaccine and antiviral therapeutics. Short interfering RNA is also known as silencing RNA and contribute a significant role to regulate the expression of a specific gene. By using this technology, virus inhibition has been demonstrated against many viral diseases. Methods: In this work, we have reported the Insilico prediction, designing, and experimental validation of siRNAs antiviral potency against SARS-CoV-2-S-RBD. The siDirect 2.0 was selected for siRNAs prediction, and secondary structure was predicted by RNAfold while the HNADOCK was used for molecular docking analysis and specific binding of siRNAs to the selected target. We have used and evaluated four siRNAs for cellular toxicity and determination of antiviral efficiency based on the Ct value of q-real-time PCR in Vero E6 cells. Results: Based on the experimental evaluation and analysis of results from generated data, we observed that there is no cytotoxicity for any tested siRNAs in Vero E6 cells. Total four siRNA were filtered out from twenty-one siRNAs following the strict selection and scoring criteria. The better antiviral efficiency was observed in 3rd siRNAs based on the Ct value of q-real-time PCR. The results that emerged from this study encouraged us to validate the efficiency of these siRNAs in multiple cells by using alone and in a combination of two or more siRNAs to inhibit the SARS-CoV-2 proliferation. Conclusion: The Insilico prediction, molecular docking analysis provided the selection of better siRNAs. Based on the experimental evaluation only 3rd siRNA was found to be more effective than others and showed better antiviral efficiency. These siRNAs should also be evaluated in other cell lines either separately or in combination against SARS-CoV-2 to determine their antiviral efficiency.

Effect of insilico predicted and designed potential siRNAs on inhibition of SARS-CoV-2 in HEK-293 cells.

Objectives: The COVID-19 was identified for the first time from the sea food market, Wuhan city, China in 2019 and the pathogenic organism was identified as SARS-CoV-2. Currently, this virus has spread to 223 countries and territories and known as a serious issue for the global human community. Many vaccines have been developed and used for immunization. Methods: We have reported the insilico prediction, designing, secondary structure prediction, molecular docking analysis, and in vitro assessment of siRNAs against SARS-CoV-2. The online bioinformatic approach was used for siRNAs selection and designing. The selected siRNAs were evaluated for antiviral efficacy by using Lipofectamine 2000 as delivery agent to HEK-293 cells. The MTT assay was used for cytotoxicity determination. The antiviral efficacy of potential siRNAs was determined based on the Ct value of q-RT-PCR and the data analysis was done by Prism-GraphPad software. Results: The analyzed data resulted in the selection of only three siRNAs out of twenty-six siRNAs generated by online software. The secondary structure prediction and molecular docking analysis of siRNAs revealed the efficient binding to the target. There was no cellular toxicity observed in the HEK-293 cells at any tested concentrations of siRNAs. The purification of RNA was completed from inoculated cells and subjected to q-RT-PCR. The highest Ct value was observed in siRNA 3 than the others. The results offered valuable evidence and invigorated us to assess the potency of siRNAs by using alone or in combination in other human cells. Conclusion: The data generated from this study indicates the significance of in silico prediction and narrow down the potential siRNA' against SARS-CoV-2, and molecular docking investigation offered the effective siRNAs binding with the target. Finally, it is concluded that the online bioinformatics approach provided the prediction and selection of siRNAs with better antiviral efficacy. The siRNA-3 was observed to be the best for reduction of viral RNA in cells.

siRNAs and Viruses: The good, the Bad and the Way Forward.

There are no available antivirals for many viruses or strains, while current antivirals are limited by toxicity and drug resistance. Therefore, alternative strategies, such as RNA interference (RNAi) are required. RNAi suppresses gene expression of any mRNA, making it an attractive candidate for antiviral therapeutics. Studies have evaluated siRNAs in a range of viruses, with some showing promising results. However, issues with stability and delivery of siRNAs remain. These issues may be minimized by modifying the siRNA structure, using an efficient delivery vector and targeting multiple regions of a virus's genome in a single dose. Finding these solutions could accelerate the progress of RNAi-based antivirals. This review highlights selected examples of antiviral siRNAs, limitations of RNAi and strategies to overcome these limitations.

From bench side to clinic: Potential and challenges of RNA vaccines and therapeutics in infectious diseases.

The functional and structural versatility of Ribonucleic acids (RNAs) makes them ideal candidates for overcoming the limitations imposed by small molecule-based drugs. Hence, RNA-based biopharmaceuticals such as messenger RNA (mRNA) vaccines, antisense oligonucleotides (ASOs), small interfering RNAs (siRNAs), microRNA mimics, anti-miRNA oligonucleotides (AMOs), aptamers, riboswitches, and CRISPR-Cas9 are emerging as vital tools for the treatment and prophylaxis of many infectious diseases. Some of the major challenges to overcome in the area of RNA-based therapeutics have been the instability of single-stranded RNAs, delivery to the diseased cell, and immunogenicity. However, recent advancements in the delivery systems of in vitro transcribed mRNA and chemical modifications for protection against nucleases and reducing the toxicity of RNA have facilitated the entry of several exogenous RNAs into clinical trials. In this review, we provide an overview of RNA-based vaccines and therapeutics, their production, delivery, current advancements, and future translational potential in treating infectious diseases.

Design of advanced siRNA therapeutics for the treatment of COVID-19.

COVID-19 is a newly emerged viral disease that is currently affecting the whole globe. A variety of therapeutic approaches are underway to block the SARS-CoV-2 virus. Among these methods, siRNAs could be a safe and specific option, as they have been tested against other viruses. siRNAs are a class of inhibitor RNAs that act promisingly as mRNA expression blockers and they can be designed to interfere with viral mRNA to block virus replication. In order to do this, we designed and evaluated the efficacy of six highly specific siRNAs, which target essential viral mRNAs with no predicted human genome off-targets. We observed a significant reduction in the copy number viral mRNAs after treatment with the siRNAs, and are expected to inhibit virus replication. We propose siRNAs as a potential co-therapy for acute SARS-CoV-2 infection.

Recognition of plausible therapeutic agents to combat COVID-19: An omics data based combined approach.

Coronavirus disease-2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has become an immense threat to global public health. In this study, we performed complete genome sequencing of a SARS-CoV-2 isolate. More than 67,000 genome sequences were further inspected from Global Initiative on Sharing All Influenza Data (GISAID). Using several in silico techniques, we proposed prospective therapeutics against this virus. Through meticulous analysis, several conserved and therapeutically suitable regions of SARS-CoV-2 such as RNA-dependent RNA polymerase (RdRp), Spike (S) and Membrane glycoprotein (M) coding genes were selected. Both S and M were chosen for the development of a chimeric vaccine that can generate memory B and T cells. siRNAs were also designed for S and M gene silencing. Moreover, six new drug candidates were suggested that might inhibit the activity of RdRp. Since SARS-CoV-2 and SARS-CoV-1 have 82.30% sequence identity, a Gene Expression Omnibus (GEO) dataset of Severe Acute Respiratory Syndrome (SARS) patients were analyzed. In this analysis, 13 immunoregulatory genes were found that can be used to develop type 1 interferon (IFN) based therapy. The proposed vaccine, siRNAs, drugs and IFN based analysis of this study will accelerate the development of new treatments.

In Silico Prediction and Designing of Potential siRNAs to be used as Antivirals Against SARS-CoV-2.

BACKGROUND: The unusual pneumonia outbreak that originated in the city of Wuhan, China in December 2019 was found to be caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or COVID-19. METHODS: In this work, we have performed an in silico design and prediction of potential siRNAs based on genetic diversity and recombination patterns, targeting various genes of SARS-CoV-2 for antiviral therapeutics. We performed extensive sequence analysis to analyze the genetic diversity and phylogenetic relationships, and to identify the possible source of virus reservoirs and recombination patterns, and the evolution of the virus as well as we designed the siRNAs which can be used as antivirals against SARS-CoV-2. RESULTS: The sequence analysis and phylogenetic relationships indicated high sequence identity and closed clusters with many types of coronavirus. In our analysis, the full-genome of SARS-CoV-2 showed the highest sequence (nucleotide) identity with SARS-bat-ZC45 (87.7%). The overall sequence identity ranged from 74.3% to 87.7% with selected SARS viruses. The recombination analysis indicated the bat SARS virus is a potential recombinant and serves as a major and minor parent. We have predicted 442 siRNAs and finally selected only 19 functional, and potential siRNAs. CONCLUSION: The siRNAs were predicted and selected based on their greater potency and specificity. The predicted siRNAs need to be validated experimentally for their effective binding and antiviral activity.