An in silico approach to design potential siRNA molecules for ICP22 (US1) gene silencing of different strains of human herpes simplex 1

The Promising Therapeutic Potential of Oligonucleotides for Pulmonary Fibrotic Diseases

INTRODUCTION

Fibrotic lung diseases represent a large subset of diseases with an unmet clinical need. Oligonucleotide therapies (ONT) are a promising therapeutic approach for the treatment of pulmonary disease as they can inhibit pathways that are otherwise difficult to target. Additionally, targeting the lung specifically with ONT is advantageous because it reduces the possibilities of systemic side effects and tolerability concerns.

AREAS COVERED

This review presents the chemical basis of designing various ONTs currently known to treat fibrotic lung diseases. Further, the authors have also discussed the delivery vehicle, routes of administration, physiological barriers of the lung, and toxicity concerns with ONTs.

EXPERT OPINION

ONTs provide a promising therapeutic approach for the treatment of fibrotic diseases of the lung, particularly because ONTs directly delivered to the lung show little systemic side effects compared to current therapeutic strategies. Dry powder aerosolized inhalers may be a good strategy for getting ONTs into the lung in humans. However, as of now, no dry powder ONTs have been approved for use in the clinical setting, and this challenge must be overcome for future therapies. Various delivery methods that can aid in direct targeting may also improve the use of ONTs for lung fibrotic diseases.

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.

Bioinformatics approach used in undergraduate research to predict siRNA as ZIKV therapeutics

Undergraduate research is an important component of a B.Tech. Biotechnology program. In the present study, a customizable approach designed with open-source bioinformatics tools and databases was introduced to predict siRNAs for ZIKV therapeutics. With minimal prior exposure to bioinformatics, this workflow can be executed with detailed steps as demonstrated in this paper. All software, databases, and servers used in this research are open-source, allowing this project-based learning methodology to be implemented remotely as well. The workflow designed in the present study is flexible and customizable according to the mentor and student's requirements.

Novel Computational Approaches to Developing Potential STAT4 Silencing siRNAs for Immunomodulation of Atherosclerosis

BACKGROUND

Small interfering RNAs (siRNAs) are known as commonly used targeting mRNAs tools for suppressing gene expression. Since Signal Transducer and Activator of Transcription 4 (STAT4) is considered as a significant transcription factor for generation and differentiation of Th1 cells during vascular dysfunction and atherosclerosis, suppressing STAT4 could represent novel immunomodulatory therapies against atherosclerosis.

OBJECTIVE

Therefore, the current study was conducted to design efficient siRNAs specific for STAT4 and to evaluate different criteria affecting their functionality.

METHODS

In the present study, all related sequences of STAT4 gene were retrieved from Gen Bank database. Multiple sequence alignment was carried out to recognize Open Reading Frame (ORF) and conserved region. Then, siDirect 2.0 server was applied for the development of candidate siRNA molecules and confirmation of predicted molecules was performed using Dharma siRNA technology and GeneScript siRNA targetfinder. In addition, BLAST tool was used against whole Genebank databases to identify potential off-target genes. DNA/RNA GC content calculator and mfold server were used to calculate GC content and secondary structure prediction of designed siRNA, respectively. Finally, IntaRNA program was used to study the thermodynamics of interaction between predicted siRNA and target gene.

RESULTS

Based on the obtained results, three efficient siRNA molecules were designed and validated for STAT4 gene silencing using computational methods, which may result in suppressing STAT4 gene expression.

CONCLUSION

According to our results, this study shows that siRNA targeting STAT4 can be considered as a therapeutic agent in many Th1-mediated pathologic conditions specially atherosclerosis.

Designing an effective therapeutic siRNA to silence RdRp gene of SARS-CoV-2

The devastating outbreak of COVID-19 has spread all over the world and has become a global health concern. There is no specific therapeutics to encounter the COVID-19. Small interfering RNA (siRNA)-based therapy is an efficient strategy to control human viral infections employing post-transcriptional gene silencing (PTGS) through neutralizing target complementary mRNA. RNA-dependent RNA polymerase (RdRp) encoded by the viral RdRp gene as a part of the replication-transcription complex can be adopted as an acceptable target for controlling SARS-CoV-2 mediated infection. Therefore, in the current study, accessible siRNA designing tools, including significant algorithms and parameters, were rationally used to design the candidate siRNAs against SARS-COV-2 encoded RdRp. The designed siRNA molecules possessed adequate nucleotide-based and other features for potent gene silencing. The targets of the designed siRNAs revealed no significant matches within the whole human genome, ruling out any possibilities for off-target silencing by the siRNAs. Characterization with different potential parameters of efficacy allowed selecting the finest siRNA among all the designed siRNA molecules. Further, validation assessment and target site accessibility prediction also rationalized the suitability of this siRNA molecule. Molecular docking study between the selected siRNA molecule and component of RNA interference (RNAi) pathway gave an excellent outcome. Molecular dynamics of two complexes: siRNA and argonaute complex, guide RNA, and target protein complex, have shown structural stability of these proteins. Therefore, the designed siRNA molecule might act as an effective therapeutic agent against the SARS-CoV-2 at the genome level and can prevent further outbreaks of COVID-19 in humans.

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

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 (Tm), heat capacity (Cp), 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.

Identification of possible siRNA molecules for TDP43 mutants causing amyotrophic lateral sclerosis: In silico design and molecular dynamics study

The DNA binding protein, TDP43 is a major protein involved in amyotrophic lateral sclerosis and other neurological disorders such as frontotemporal dementia, Alzheimer disease, etc. In the present study, we have designed possible siRNAs for the glycine rich region of tardbp mutants causing ALS disorder based on a systematic theoretical approach including (i) identification of respective codons for all mutants (reported at the protein level) based on both minimum free energy and probabilistic approaches, (ii) rational design of siRNA, (iii) secondary structure analysis for the target accessibility of siRNA, (iii) determination of the ability of siRNA to interact with mRNA and the formation/stability of duplex via molecular dynamics study for a period of 15ns and (iv) characterization of mRNA-siRNA duplex stability based on thermo-physical analysis. The stable GC-rich siRNA expressed strong binding affinity towards mRNA and forms stable duplex in A-form. The linear dependence between the thermo-physical parameters such as Tm, GC content and binding free energy revealed the ability of the identified siRNAs to interact with mRNA in comparable to that of the experimentally reported siRNAs. Hence, this present study proposes few siRNAs as the possible gene silencing agents in RNAi therapy based on the in silico approach.

Design of Potential RNAi (miRNA and siRNA) Molecules for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Gene Silencing by Computational Method

The Middle East respiratory syndrome coronavirus (MERS-CoV) is a virus that manifests itself in viral infection with fever, cough, shortness of breath, renal failure and severe acute pneumonia, which often result in a fatal outcome. MERS-CoV has been shown to spread between people who are in close contact. Transmission from infected patients to healthcare personnel has also been observed and is irredeemable with present technology. Genetic studies on MERS-CoV have shown that ORF1ab encodes replicase polyproteins and play a foremost role in viral infection. Therefore, ORF1ab replicase polyprotein may be used as a suitable target for disease control. Viral activity can be controlled by RNA interference (RNAi) technology, a leading method for post transcriptional gene silencing in a sequence-specific manner. However, there is a genetic inconsistency in different viral isolates; it is a great challenge to design potential RNAi (miRNA and siRNA) molecules which can silence the respective target genes rather than any other viral gene simultaneously. In the current study, four effective miRNA and five siRNA molecules for silencing of nine different strains of MERS-CoV were rationally designed and corroborated using computational methods, which might lead to knockdown the activity of virus. siRNA and miRNA molecules were predicted against ORF1ab gene of different strains of MERS-CoV as effective candidate using computational methods. Thus, this method may provide an insight for the chemical synthesis of antiviral RNA molecule for the treatment of MERS-CoV, at genomic level.

Design of potential RNAi (miRNA and siRNA) molecules for Middle East respiratory syndrome coronavirus (MERS-CoV) gene silencing by computational method

The Middle East respiratory syndrome coronavirus (MERS-CoV) is a virus that manifests itself in viral infection with fever, cough, shortness of breath, renal failure and severe acute pneumonia, which often result in a fatal outcome. MERS-CoV has been shown to spread between people who are in close contact. Transmission from infected patients to healthcare personnel has also been observed and is irredeemable with present technology. Genetic studies on MERS-CoV have shown that ORF 1ab encodes replicase polyproteins and play a foremost role in viral infection. Therefore, ORF 1ab replicase polyprotein may be used as suitable target for disease control. Viral activity can be controlled by RNA interference (RNAi) technology, a leading method for post transcriptional gene silencing in a sequence specific manner. However, there is a genetic inconsistency in different viral isolates; it is a great challenge to design potential RNAi (miRNA and siRNA) molecules which can silence the respective target genes rather than any other viral gene simultaneously. In current study four effective miRNA and five siRNA molecules for silencing of nine different strains of MERS-CoV were rationally designed and corroborated using computational methods, which might lead to knockdown the activity of virus. siRNA and miRNA molecules were predicted against ORF1ab gene of different strains of MERS-CoV as effective candidate using computational methods. Thus, this method may provide an insight for the chemical synthesis of antiviral RNA molecule for the treatment of MERS-CoV, at genomic level.

Design of potential RNAi (miRNA and siRNA) molecules for Middle East respiratory syndrome coronavirus (MERS-CoV) gene silencing by computational method

The Middle East respiratory syndrome coronavirus (MERS-CoV) is a virus that manifests itself in viral infection with fever, cough, shortness of breath, renal failure and severe acute pneumonia, which often result in a fatal outcome. MERS-CoV has been shown to spread between people who are in close contact. Transmission from infected patients to healthcare personnel has also been observed and is irredeemable with present technology. Genetic studies on MERS-CoV have shown that ORF 1ab encodes replicase polyproteins and play a foremost role in viral infection. Therefore, ORF 1ab replicase polyprotein may be used as suitable target for disease control. Viral activity can be controlled by RNA interference (RNAi) technology, a leading method for post transcriptional gene silencing in a sequence specific manner. However, there is a genetic inconsistency in different viral isolates; it is a great challenge to design potential RNAi (miRNA and siRNA) molecules which can silence the respective target genes rather than any other viral gene simultaneously. In current study four effective miRNA and five siRNA molecules for silencing of nine different strains of MERS-CoV were rationally designed and corroborated using computational methods, which might lead to knockdown the activity of virus. siRNA and miRNA molecules were predicted against ORF1ab gene of different strains of MERS-CoV as effective candidate using computational methods. Thus, this method may provide an insight for the chemical synthesis of antiviral RNA molecule for the treatment of MERS-CoV, at genomic level.