In silico prediction and experimental validation of siRNAs targeting ORF1ab of MERS-CoV in Vero cell line

Designing siRNA for silencing the human ERBB2 gene in cancer treatment: Evaluating intracellular delivery strategies

The ERBB2 is one of the most studied genes in oncology for its significant role in human malignancies. The metastasis-associated properties that facilitate cancer metastasis can be enhanced by activating the ERBB2 receptor signaling pathways. Additionally, therapeutic resistance is conferred by ERBB2 overexpression via receptor-mediated antiapoptotic signals. Several ERBB2-blocking techniques have the effect of overexpressed ERBB2, and several of them have passed clinical trials for use as therapies. Small interfering RNAs (siRNA), which have the potential to silence genes, are attractive for treating such fatal malignancies. In this study, we rationally designed a siRNA molecule targeting the human ERBB2 gene. The selection process involved identifying a shared region among all ERBB2 transcripts for siRNA design. The ultimate siRNA candidate was chosen through rigorous evaluation using contemporary algorithms, considering off-target similarities, examination of thermodynamic properties, and analysis using molecular dynamics (MD) simulations. Further, we opted for cell-penetrating peptides (CPP) and RNA aptamer as carriers for the siRNA. Employing both steered MD simulations and traditional MD simulations, we investigated how these carriers facilitate siRNA delivery. Experimental confirmation revealed the stability of the selected carriers and siRNA on the lipid bilayer. The designed siRNA molecule and the simulations present a potential alternative therapeutic strategy against human ERBB2. This contributes to advances in developing and utilizing innovative carriers for the delivery of siRNA, enhancing the potential for therapeutic applications.

Mitigating off-target effects of small RNAs: conventional approaches, network theory and artificial intelligence

Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages over small-molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases. In preclinical research, synthetic small RNAs play an essential role in the investigation of physiological and pathological pathways as silencers of specific genes, facilitating discovery and validation of drug targets in different conditions. Off-target effects of small RNAs, however, could make it difficult to interpret experimental results in the preclinical phase and may contribute to adverse events of small RNA therapeutics. Out of the two major types of off-target effects we focused on the hybridization-dependent, especially on the miRNA-like off-target effects. Our main aim was to discuss several approaches, including sequence design, chemical modifications and target prediction, to reduce hybridization-dependent off-target effects that should be considered even at the early development phase of small RNA therapy. Because there is no standard way of predicting hybridization-dependent off-target effects, this review provides an overview of all major state-of-the-art computational methods and proposes new approaches, such as the possible inclusion of network theory and artificial intelligence (AI) in the prediction workflows. Case studies and a concise survey of experimental methods for validating in silico predictions are also presented. These methods could contribute to interpret experimental results, to minimize off-target effects and hopefully to avoid off-target-related adverse events of small RNA therapeutics. LINKED ARTICLES: This article is part of a themed issue Non-coding RNA Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc.

SiRNAs as antiviral drugs - Current status, therapeutic potential and challenges

Traditionally, antiviral drugs target viral enzymes and or structural proteins, identified through large drug screens or rational drug design. The screening, chemical optimisation, small animal toxicity studies and clinical trials mean time to market is long for a new compound, and in the event of a novel virus or pandemic, weeks, and months matter. Small interfering RNAs (siRNAs) as a gene silencing platform is an alluring alternative. SiRNAs are now approved for use in the clinic to treat a range of diseases, are cost effective, scalable, and can be easily programmed to target any viral target in a matter of days. Despite the large number of preclinical studies that clearly show siRNAs are highly effective antivirals this has not translated into clinical success with no products on the market. This review provides a comprehensive overview of both the clinical and preclinical work in this area and outlines the challenges the field faces going forward that need to be addressed in order to see siRNA antivirals become a clinical reality.

Antiviral Drug Discovery

A vast and painful price has been paid in the battle against viruses in global health [...].

An ncRNA transcriptomics-based approach to design siRNA molecules against SARS-CoV-2 double membrane vesicle formation and accessory genes

BACKGROUND

The corona virus SARS-CoV-2 is the causative agent of recent most global pandemic. Its genome encodes various proteins categorized as non-structural, accessory, and structural proteins. The non-structural proteins, NSP1-16, are located within the ORF1ab. The NSP3, 4, and 6 together are involved in formation of double membrane vesicle (DMV) in host Golgi apparatus. These vesicles provide anchorage to viral replicative complexes, thus assist replication inside the host cell. While the accessory genes coded by ORFs 3a, 3b, 6, 7a, 7b, 8a, 8b, 9b, 9c, and 10 contribute in cell entry, immunoevasion, and pathological progression.

METHODS

This in silico study is focused on designing sequence specific siRNA molecules as a tool for silencing the non-structural and accessory genes of the virus. The gene sequences of NSP3, 4, and 6 along with ORF3a, 6, 7a, 8, and 10 were retrieved for conservation, phylogenetic, and sequence logo analyses. siRNA candidates were predicted using siDirect 2.0 targeting these genes. The GC content, melting temperatures, and various validation scores were calculated. Secondary structures of the guide strands and siRNA-target duplexes were predicted. Finally, tertiary structures were predicted and subjected to structural validations.

RESULTS

This study revealed that NSP3, 4, and 6 and accessory genes ORF3a, 6, 7a, 8, and 10 have high levels of conservation across globally circulating SARS-CoV-2 strains. A total of 71 siRNA molecules were predicted against the selected genes. Following rigorous screening including binary validations and minimum free energies, final siRNAs with high therapeutic potential were identified, including 7, 2, and 1 against NSP3, NSP4, and NSP6, as well as 3, 1, 2, and 1 targeting ORF3a, ORF7a, ORF8, and ORF10, respectively.

CONCLUSION

Our novel in silico pipeline integrates effective methods from previous studies to predict and validate siRNA molecules, having the potential to inhibit viral replication pathway in vitro. In total, this study identified 17 highly specific siRNA molecules targeting NSP3, 4, and 6 and accessory genes ORF3a, 7a, 8, and 10 of SARS-CoV-2, which might be used as an additional antiviral treatment option especially in the cases of life-threatening urgencies.

Gene silencing of Helicobacter pylori through newly designed siRNA convenes the treatment of gastric cancer

BACKGROUND

Helicobacter pylori is a gastric pathogen that is responsible for causing chronic inflammation and increasing the risk of gastric cancer development. It is capable of persisting for decades in the harsh gastric environment because of the inability of the host to eradicate the infection. Several treatment strategies have been developed against this bacterium using different antibiotics. But the effectiveness of treating H. pylori has significantly decreased due to widespread antibiotic resistance, including an increased risk of gastric cancer. The small interfering RNAs (siRNA), which is capable of sequence-specific gene-silencing can be used as a new therapeutic approach for the treatment of a variety of such malignancies. In the current study, we rationally designed two siRNA molecules to silence the cytotoxin-associated gene A (CagA) and vacuolating cytotoxin A (VacA) genes of H. pylori for their significant involvement in developing cancer.

METHODS

We selected a common region of all the available transcripts from different countries of CagA and VacA to design the siRNA molecules. The final siRNA candidate was selected based on the results from machine learning algorithms, off-target similarity, and various thermodynamic properties.

RESULT

Further, we utilized molecular docking and all atom molecular dynamics (MD) simulations to assess the binding interactions of the designed siRNAs with the major components of the RNA-induced silencing complex (RISC) and results revealed the ability of the designed siRNAs to interact with the proteins of RISC complex in comparable to those of the experimentally reported siRNAs.

CONCLUSION

These designed siRNAs should effectively silence the CagA and VacA genes of H. pylori during siRNA mediated treatment in gastric cancer.

Khan R, Kumalo HM. Assessing the Potential Contribution of In Silico Studies in Discovering Drug Candidates That Interact with Various SARS-CoV-2 Receptors

The COVID-19 pandemic has spurred intense research efforts to identify effective treatments for SARS-CoV-2. In silico studies have emerged as a powerful tool in the drug discovery process, particularly in the search for drug candidates that interact with various SARS-CoV-2 receptors. These studies involve the use of computer simulations and computational algorithms to predict the potential interaction of drug candidates with target receptors. The primary receptors targeted by drug candidates include the RNA polymerase, main protease, spike protein, ACE2 receptor, and transmembrane protease serine 2 (TMPRSS2). In silico studies have identified several promising drug candidates, including Remdesivir, Favipiravir, Ribavirin, Ivermectin, Lopinavir/Ritonavir, and Camostat Mesylate, among others. The use of in silico studies offers several advantages, including the ability to screen a large number of drug candidates in a relatively short amount of time, thereby reducing the time and cost involved in traditional drug discovery methods. Additionally, in silico studies allow for the prediction of the binding affinity of the drug candidates to target receptors, providing insight into their potential efficacy. This study is aimed at assessing the useful contributions of the application of computational instruments in the discovery of receptors targeted in SARS-CoV-2. It further highlights some identified advantages and limitations of these studies, thereby revealing some complementary experimental validation to ensure the efficacy and safety of identified drug candidates.

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 JetPRIME^R 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 JetPRIME^R for the delivery of siRNAs in both cell lines.

An overview of the recent progress in Middle East Respiratory Syndrome Coronavirus (MERS-CoV) drug discovery

INTRODUCTION

The Middle East respiratory syndrome coronavirus (MERS-CoV) has remained a public health concern since it first emerged in 2012. Although many potential treatments for MERS-CoV have been developed and tested, none have had complete success in stopping the spread of this deadly disease. MERS-CoV replication comprises attachment, entry, fusion and replication steps. Targeting these events may lead to the creation of medications that effectively treat MERS-CoV infection.

AREAS COVERED

This review updates the research on the development of inhibitors of MERS-CoV. The main topics are MERS-CoV‒related proteins and host cell proteins that are involved in viral protein activation and infection.

EXPERT OPINION

Research on discovering drugs that can inhibit MERS-CoV started at a slow pace, and although efforts have steadily increased, clinical trials for new drugs specifically targeting MERS-CoV have not been extensive enough. The explosion in efforts to find new medications for the SARS-CoV-2 virus indirectly enhanced the volume of data on MERS-CoV inhibition by including MERS-CoV in drug assays. The appearance of COVID-19 completely transformed the data available on MERS-CoV inhibition. Despite the fact that new infected cases are constantly being diagnosed, there are currently no approved vaccines for or inhibitors of MERS-CoV.

An In-silico Approach to Design and Validate siRNA against Monkeypox Virus

INTRODUCTION

The monkeypox virus has emerged as an uncommon zoonotic infection. The recent outbreak of MPXV in Europe and abroad in 2022 presented a major threat to individuals at risk. At present, no specific MPXV vaccinations or medications are available.

METHODS

In this study, we predicted the most effective siRNA against the conserved region of the MPXV and validated the activity by performing molecular docking studies.

RESULTS

Ultimately, the most efficient siRNA molecule was shortlisted against the envelope protein gene (B6R) based on its toxicity, effectivity, thermodynamic stability, molecular interaction, and molecular dynamics simulations (MD) with the Human Argonaute 2 protein.

CONCLUSION

Thus, the strategy may offer a platform for the development of potential antiviral RNA therapeutics that target MPXV at the genomic level.

Designing potential siRNA molecules for silencing the gene of the nucleocapsid protein of Nipah virus: A computational investigation

Nipah virus (NiV), a zoonotic virus, engenders severe infections with noticeable complications and deaths in humans and animals. Since its emergence, it is frightening, this virus has been causing regular outbreaks in various countries, particularly in Bangladesh, India, and Malaysia. Unfortunately, no efficient vaccine or drug is available now to combat this baneful virus. NiV employs its nucleocapsid protein for genetic material packaging, which is crucial for viral replication inside the host cells. The small interfering RNAs (siRNAs) can play a central role in inhibiting the expression of disease-causing viral genes by hybridization and subsequent inactivation of the complementary target viral mRNAs through the RNA interference (RNAi) pathway. Therefore, potential siRNAs as molecular therapeutics against the nucleocapsid protein gene of NiV were designed in this study. First, ten prospective siRNAs were identified using the conserved nucleocapsid gene sequences among all available NiV strains collected from various countries. After that, off-target binding, GC (guanine-cytosine) content, secondary structure, binding affinity with the target, melting temperature, efficacy analysis, and binding capacity with the human argonaute protein 2 (AGO2) of these siRNAs were evaluated to predict their suitability. These designed siRNA molecules bear promise in silencing the NiV gene encoding the nucleocapsid protein and thus can alleviate the severity of this dangerous virus. Further in vivo experiments are recommended before using these designed siRNAs as alternative and effective molecular therapeutic agents against NiV.

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.

Design of siRNA molecules for silencing of membrane glycoprotein, nucleocapsid phosphoprotein, and surface glycoprotein genes of SARS-CoV2

The global COVID-19 pandemic caused by SARS-CoV2 infected millions of people and resulted in more than 4 million deaths worldwide. Apart from vaccines and drugs, RNA silencing is a novel approach for treating COVID-19. In the present study, siRNAs were designed for the conserved regions targeting three structural genes, M, N, and S, from forty whole-genome sequences of SARS-CoV2 using four different software, RNAxs, siDirect, i-Score Designer, and OligoWalk. Only siRNAs which were predicted in common by all the four servers were considered for further shortlisting. A multistep filtering approach has been adopted in the present study for the final selection of siRNAs by the usage of different online tools, viz., siRNA scales, MaxExpect, DuplexFold, and SMEpred. All these web-based tools consider several important parameters for designing functional siRNAs, e.g., target-site accessibility, duplex stability, position-specific nucleotide preference, inhibitory score, thermodynamic parameters, GC content, and efficacy in cleaving the target. In addition, a few parameters like GC content and dG value of the entire siRNA were also considered for shortlisting of the siRNAs. Antisense strands were subjected to check for any off-target similarities using BLAST. Molecular docking was carried out to study the interactions of guide strands with AGO2 protein. A total of six functional siRNAs (two for each gene) have been finally selected for targeting M, N, and S genes of SARS-CoV2. The siRNAs have not shown any off-target effects, interacted with the domain(s) of AGO2 protein, and were efficacious in cleaving the target mRNA. However, the siRNAs designed in the present study need to be tested in vitro and in vivo in the future.

Nanoparticle Delivery Platforms for RNAi Therapeutics Targeting COVID-19 Disease in the Respiratory Tract

Since December 2019, a pandemic of COVID-19 disease, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly spread across the globe. At present, the Food and Drug Administration (FDA) has issued emergency approval for the use of some antiviral drugs. However, these drugs still have limitations in the specific treatment of COVID-19, and as such, new treatment strategies urgently need to be developed. RNA-interference-based gene therapy provides a tractable target for antiviral treatment. Ensuring cell-specific targeted delivery is important to the success of gene therapy. The use of nanoparticles (NPs) as carriers for the delivery of small interfering RNA (siRNAs) to specific tissues or organs of the human body could play a crucial role in the specific therapy of severe respiratory infections, such as COVID-19. In this review, we describe a variety of novel nanocarriers, such as lipid NPs, star polymer NPs, and glycogen NPs, and summarize the pre-clinical/clinical progress of these nanoparticle platforms in siRNA delivery. We also discuss the application of various NP-capsulated siRNA as therapeutics for SARS-CoV-2 infection, the challenges with targeting these therapeutics to local delivery in the lung, and various inhalation devices used for therapeutic administration. We also discuss currently available animal models that are used for preclinical assessment of RNA-interference-based gene therapy. Advances in this field have the potential for antiviral treatments of COVID-19 disease and could be adapted to treat a range of respiratory diseases.

In Vitro Inhibitory Analysis of Rationally Designed siRNAs against MERS-CoV Replication in Huh7 Cells

MERS-CoV was identified for the first time in Jeddah, Saudi Arabia in 2012 in a hospitalized patient. This virus subsequently spread to 27 countries with a total of 939 deaths and 2586 confirmed cases and now has become a serious concern globally. Camels are well known for the transmission of the virus to the human population. In this report, we have discussed the prediction, designing, and evaluation of potential siRNA targeting the ORF1ab gene for the inhibition of MERS-CoV replication. The online software, siDirect 2.0 was used to predict and design the siRNAs, their secondary structure and their target accessibility. ORF1ab gene folding was performed by RNAxs and RNAfold software. A total of twenty-one siRNAs were selected from 462 siRNAs according to their scoring and specificity. siRNAs were evaluated in vitro for their cytotoxicity and antiviral efficacy in Huh7 cell line. No significant cytotoxicity was observed for all siRNAs in Huh7 cells. The in vitro study showed the inhibition of viral replication by three siRNAs. The data generated in this study provide preliminary and encouraging information to evaluate the siRNAs separately as well as in combination against MERS-CoV replication in other cell lines. The prediction of siRNAs using online software resulted in the filtration and selection of potential siRNAs with high accuracy and strength. This computational approach resulted in three effective siRNAs that can be taken further to in vivo animal studies and can be used to develop safe and effective antiviral therapies for other prevalent disease-causing viruses.