Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains

Advancing siRNA Therapeutics targeting MCT-4: A Multifaceted approach integrating Arithmetical Designing, Screening, and molecular dynamics validation

Monocarboxylate transporter 4 (MCT-4) is involved in various metabolic processes which are crucial in maintaining cellular pH and energy metabolism, and thus influence the tumor microenvironment. The study is aimed to rationally design effective Small interfering RNA (siRNA) that can silence MCT-4. We utilized a comprehensive workflow integrating multiple tools such as siDirect version 2.0, Oligowalk and i-score designer, to evaluate sequence features and predict target site accessibility, Guanine-Cytosine (GC) content and thermodynamic stability. Five (M1, M2, M3, M4 and M5) siRNAs sequences were retrived and subjected to further scrutiny on the account of off-target elimation, sequence conservation, secondary structure formation, and thermodynamic properties. The M1 demonstrated off targets and the M2 sequence showed secondry conformation and therefore M3, M4 and M5 were considered for further evaluation. Additionally, molecular docking and simulations (50 ns) were conducted with human Argonaute 2 protein (h-Arg-2). The post- molecular dynamics (MD) analysis revealed M4 (5'UUGAAGAAGACACUGACGG3') as a most appropriate siRNA candidate agsint MCT-4 on the basis of Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and H-Bond results. The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis was also performed to further validate the selected siRNA candidates, which further affirmed M4 (5'UUGAAGAAGACACUGACGG3') as an potential candidate for future in-vitro and in-vivo evaluation.

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.

RNAi-Induced Gene Silencing against Chikungunya and COVID-19: What Have We Learned So Far, and What Is the Way Forward?

RNA interference (RNAi) is a process in which small RNA molecules (such as small interfering RNAs or siRNAs) bind to specific messenger RNAs (mRNAs), leading to its degradation and inhibition of protein synthesis. Our studies have shown that RNAi can effectively silence genes involved in the replication of the Chikungunya virus (CHIKV) in cells. However, these investigations were performed only in laboratory settings and have yet to be tested in human clinical trials. Researchers need to conduct more research to determine the safety and efficacy of RNAi-based therapies as a therapeutic agent to treat viral infections. In this review, the history of evolution of siRNA as an inhibitor of protein synthesis, along with its current developments, is discussed based on our experience. Moreover, this review examines the hurdles and future implications associated with siRNA based therapeutic approaches.

Exploring the potential of structural modeling and molecular docking for efficient siRNA screening: A promising approach to Combat viral mutants, with a focus on HIV-1

RNA interference (RNAi) holds immense potential for sequence-specific downregulation of disease-related genes. Small interfering RNA (siRNA) therapy has made remarkable strides, with FDA approval for treating specific human diseases, showcasing its promising future in disease treatment. Designing highly efficient siRNAs is a critical step in this process. Previous studies have introduced various algorithms and parameters for siRNA design and scoring. However, these attempts have often fallen short of meeting all essential criteria or required modifications, resulting in variable and unclear effectiveness of screened siRNAs, particularly against viral mutants with non-conserved short sequences. In this study, we present a fully optimized siRNA screening system considering all necessary parameters. Notably, we highlight the critical role of molecular docking simulations between siRNA and two functional domains of the Argonaute protein (PAZ and PIWI) in identifying the most efficient siRNAs, since the appropriate interaction between the guide siRNA strand and the RISC complex is crucial. Through our stringent method, we designed approximately 50 potential siRNAs targeting the HIV-1 vpr gene. Evaluation through XTT, qRT-PCR, and flow cytometry analysis on RAW 264.7 macrophage stable cells revealed negligible cytotoxicity and exceptional gene-silencing efficiency at both the transcriptional and translational levels for the top-ranked screened siRNAs. Given the growing interest in siRNA-based therapeutics, we anticipate that the insights from this study will contribute to improving treatment strategies against mutant viruses, particularly HIV-1.

Computational design and validation of effective siRNAs to silence oncogenic KRAS

Oncogenic KRAS mutations drive cancer progression in lung, colon, breast, and pancreatic ductal adenocarcinomas. Apart from the current strategies, such as KRAS upstream inhibitors, downstream effector inhibitors, interaction inhibitors, cell cycle inhibitors, and direct KRAS inhibitors, against KRAS-mutated cancers, the therapeutic small interfering RNAs (siRNAs) represent a promising alternative strategy that directly binds with the target mRNA and inhibits protein translation via mRNA degradation. Here, in the present study, we utilized various in silico approaches to design potential siRNA candidates against KRAS mRNA. We have predicted nearly 17 siRNAs against the KRAS mRNA, and further through various criteria, such as U, R, and A rules, GC%, secondary structure formation, mRNA-siRNA duplex stability, Tm (Cp), Tm (Conc), and inhibition efficiency, they have been filtered into 4 potential siRNAs namely siRNA8, siRNA11, siRNA12, and siRNA17. Further, the molecular docking analysis revealed that the siRNA8, siRNA11, siRNA12, and siRNA17 showed higher negative binding energies, such as - 379.13 kcal/mol, - 360.19 kcal/mol, - 288.47 kcal/mol, and - 329.76 kcal/mol, toward the human Argonaute2 protein (hAgo2) respectively. In addition, the normal mode analysis of the hAgo2-siRNAs complexes indicates the structural changes and deformation of the hAgo2 protein upon the binding of siRNA molecules in the dynamic environment which suggests that these siRNAs could be effective. Finally, we conclude that these 4 siRNAs have therapeutic potential against KRAS mRNA and also have to be studied in vitro and in vivo to evaluate their specificity toward mutant KRAS (not degrading wild-type KRAS). Also, the current challenges in the use of siRNA therapeutics could be overcome by the emerging siRNA delivery methods, such as Antibody-siRNA conjugates (ARCs) and Gelatin-Antibody Delivery System (GADS), in the near future and these siRNAs could be employed as potential therapeutic agents against KRAS-mutated cancers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03767-w.

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.