With the rise of small interfering RNA (siRNA) as a therapeutic tool, effective siRNA design is crucial. Current methods often emphasize sequence-related features, overlooking structural information. To address this, we introduce ENsiRNA, a multimodal approach utilizing a geometric graph neural network to predict the efficacy of both standard and modified siRNA. ENsiRNA integrates sequence features from a pretrained RNA language model, structural characteristics, and thermodynamic data or chemical modifications to enhance prediction accuracy. Our results indicate that ENsiRNA outperforms existing methods, achieving over a 13% improvement in Pearson Correlation Coefficient (PCC) for standard siRNA across various tests. For modified siRNA, despite challenges associated with RNA folding methods, ENsiRNA still demonstrates competitive performance in different datasets. This novel method highlights the significance of structural information and multimodal strategies in siRNA prediction, advancing the field of therapeutic design.

In recent years, success has been achieved in treating several eye conditions with oligonucleotide-based therapies. Herein, we outline the experimentation involved in progressing selection and development of a lead therapeutic siRNA for R124H mutation of TGFBI gene which causes Granular Corneal Dystrophy Type 2 (GCD2/Avellino CD). Firstly, a series of siRNA designs, generated by a gene walk across the R124H TGFBI mutation site, were tested and a lead siRNA identified. The lead siRNA was delivered into an immortalised human corneal epithelial cell line to assess on-target efficacy and off-target effects. The in vivo efficacy of the lead R124H TGFBI siRNA, complexed with Bio-Courier technology, silicon stabilized hybrid lipid nanoparticles (sshLNP), was assessed in a mouse model of GCD2 which expressed the human R124H TGFBI transgene. Following topical siRNA application for 5 consecutive days, expression of the R124H mutant TGFBI transgene was measured and shown to be reduced by 22.4 % (± 15.7 %, p < 0.05). We investigated gene expression in the mouse cornea and showed expression of murine Tgfbi was 20-fold lower than TGFBI in human cornea, and expression of the mutant TGFBI transgene was a further 3-fold lower. This estimated 60-fold lower mutant transgene expression may explain the low frequency of corneal deposits observed in this mouse model, limiting its usefulness to test whether siRNA silencing is capable of phenotypic improvement or regression of GCD2/Avellino corneal dystrophy. We assessed WT TGFBI silencing in human primary corneal epithelial cells (PCEC) derived from human corneal limbal biopsy material, which express TGFBI at a similar level to human corneal biopsy. We demonstrated that a single 100 nM siRNA treatment, delivered by the sshLNP to the primary human corneal epithelial cells, gave 26.6 % (± 6.6 %, p < 0.001) reduction in TGFBI mRNA and a 15.4 % (±10.5 %, p < 0.05 %) reduction in TGFBi protein after 48 h. In consideration of the mutant gene expression levels in existing models of GCD2 disease, an ex vivo model of mutation-expressing primary corneal epithelial cells generated from corneal limbal biopsies from GCD2 patients would be more suitable than existing transgenic mouse models for future pre-clinical work in the development of gene silencing therapies for corneal dystrophies.

Angiotensinogen (AGT) is the precursor of angiotensin II, a potent vasopressor in the renin-angiotensin-aldosterone system. Small interfering RNAs (siRNAs) targeting hepatic AGT can lower blood pressure in hypertension patients by reducing AGT levels, with effects lasting over 6 months. Existing siRNA molecules are effective, but novel ones with better inhibitory activity and longer duration periods may be developed. In this study, we demonstrated an entire development process for a novel siRNA targeting hepatic AGT. Through the proper combination of bioinformatic on-target/off-target screening on sequences, chemical modification patterns optimization, and liver-targeting delivery ligands conjugation, we have successfully developed several promising siRNAs with equivalent or better inhibitory activity, duration of effect, and safety profile compared with previously reported siRNA. Moreover, our comprehensive analysis has elucidated the correlation between the efficacy and free energy of siRNAs. Currently, there exists no reliable model capable of precisely predicting the activity and off-target risk associated with fully modified siRNAs. Therefore, the implementation of efficient screening procedures is of utmost importance during the development of siRNA candidates. This study presents a meticulous and valuable reference for the development of potent and safe siRNAs on other targets.

Cancer has become a significant public health concern worldwide. It is a group of diseases, often resulting from the dysregulation of multiple cellular pathways involved in differentiation, cell proliferation, cell cycle regulation, and DNA repair. These disruptions are primarily caused by genetic mutation and epigenetic alterations which lead to uncontrolled growth and tumor formation. Targeted therapy is a precise and effective strategy to overcome the shortcomings of conventional therapy. RNA interference (RNAi) is a gene-silencing mechanism that has an uncanny ability to target disease-associated genes. Small interfering RNA (siRNA) is a key component of RNAi and has shown promise in silencing oncogenes and inhibiting cancer progression. However, the therapeutic application of siRNA faces several challenges such as poor cellular uptake, short half-life, endosomal escape, immune system activation, and off-target. Strategies to address these challenges are optimized designing of siRNA, advanced delivery systems, and chemical modification to improve cellular uptake and protect from degradation. This review focuses on the therapeutic potential of siRNA in cancer treatment and discusses the action mechanism of siRNA, barriers in siRNA, and strategies to overcome them. The review shed light on the current clinical trial of siRNA-based cancer therapy, along with outcomes and limitations.

Hypoxia-inducible factor-1 alpha (HIF-1α) is an important transcription factor regulating glycolysis, angiogenesis, metastasis, and erythropoiesis under hypoxic conditions in solid tumors. Small interfering RNAs (siRNAs) have emerged as a promising therapeutic approach for solid tumors by selectively silencing target genes. This study explored siRNA-mediated degradation of HIF-1α by specifically targeting HIF-1α mRNA. We retrieved the HIF-1α gene sequence from the database and used various computational tools like siDirect and OligoWalk to get potential 19-21nts long siRNAs. Furthermore, these siRNAs were screened using parameters like sequence specificity, BLASTn, secondary structure formation, GC content, binding affinity between siRNA and mRNA, and thermodynamic properties. The potential siRNAs were further evaluated through molecular docking studies for interaction with the human Argonaute-2 protein (hAgo2), followed by molecular dynamics simulation studies. Post-MD studies revealed S4 (5'UAUAUGGUGAUGAUGUGGC3') as the most potential siRNA candidate against HIF-1α, based on root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), and H-bond analysis. Molecular mechanics Poisson-Boltzmann surface area (MMPBSA) analysis was also performed to further validate the selected siRNA candidates, which further affirmed S4 (5'UAUAUGGUGAUGAUGUGGC3') as a potential candidate against HIF-1α.

Antisense oligonucleotides (ASOs) are a promising class of gene therapies that can modulate the gene expression. However, designing ASOs manually is resource-intensive and time-consuming. To address this, we introduce a user-friendly web server for ASOptimizer, a deep learning-based computational framework for optimizing ASO sequences and chemical modifications. Given a user-provided ASO sequence, the web server systematically explores modification sites within the nucleic acid and returns a ranked list of promising modification patterns. With an intuitive interface requiring no expertise in deep learning tools, the platform makes ASOptimizer easily accessible to the broader research community. The web server is freely available at https://asoptimizer.s-core.ai/.

The shear stress resulting from blood flow is a major regulator of endothelial cell (EC) biology and morphology. Rho protein-mediated cytoskeleton remodeling is an early and essential step of EC responses to flow. However, how Rho protein signaling is controlled by shear stress remains unclear. Here we demonstrate that phosphorylation, activity, and expression of the Rho nucleotide exchange factor (RhoGEF) ARHGEF18 in ECs are modulated by the magnitude of shear stress. When phosphorylated, ARHGEF18 interacts with tight junctions; participates in EC elongation, alignment, and migration; and allows the maintenance of the endothelial barrier under physiological flow conditions. In mice, ARHGEF18 is involved in tight junction formation, flow response of ECs, and the control of vascular permeability. Together, our results identified ARHGEF18 as the first flow-sensitive RhoGEF in ECs, whose activity is essential for the maintenance of intercellular junctions and the control of vascular permeability in vivo.

SARS-CoV-2 is causing severe to moderate respiratory tract infections, posing global health, social life, and economic threats. Our design strategy for siRNAs differs from existing studies through a step-by-step filtration process utilizing integrative bioinformatics protocols and web tools. Stage one: Multiple Sequence Alignment was employed to identify the most conserved areas. Stage two involves using various online tools, among the most reputable tools for building siRNA. The first filtration step of siRNA uses the Huesken dataset, estimating a 90 % experimental inhibition. The second filtration stage involves choosing the most suitable and targeted siRNA by utilizing thermodynamics and Target Accessibility of siRNAs. The final filtration step is off-target filtration using BLAST with specific parameters. Four of the 258 siRNAs were chosen for their potency and specificity, targeting conserved regions (NSP8, NSP12, and NSP14) with minimal human transcripts off-targets. We conducted in-vitro experiments, including cytotoxicity, TCID50, and RT-PCR assays. When tested on the SARS-CoV-2 strain hCoV-19/Egypt/NRC-03/2020 at 100 nM, none showed cellular toxicity. The TCID50 assay confirmed viral replication reduction at 12 h.p.i; the efficacy of the four siRNAs and their P value were highly significant. siRNA2 maintaining efficacy at 24, 36, and 48 h.p.i, while siRNA4 had a significant P value (≤0.0001) at 48 h.p.i. At 24 h.p.i, siRNA2 and siRNA4 showed statistical significance in viral knockdown of the virus's S gene and ORF1b gene by 95 %, 89 %, and 96 %, 97 %, respectively. Our computational method and experimental assessment of specific siRNAs have led us to conclude that siRNA2 and siRNA4 could be promising new therapies for SARS-CoV-2 that need further development.

The ability of small nucleic acids to modulate gene expression via a range of processes has been widely explored. Compared with conventional treatments, small nucleic acid therapeutics have the potential to achieve long-lasting or even curative effects via gene editing. As a result of recent technological advances, efficient small nucleic acid delivery for therapeutic and biomedical applications has been achieved, accelerating their clinical translation. Here, we review the increasing number of small nucleic acid therapeutic classes and the most common chemical modifications and delivery platforms. We also discuss the key advances in the design, development and therapeutic application of each delivery platform. Furthermore, this review presents comprehensive profiles of currently approved small nucleic acid drugs, including 11 antisense oligonucleotides (ASOs), 2 aptamers and 6 siRNA drugs, summarizing their modifications, disease-specific mechanisms of action and delivery strategies. Other candidates whose clinical trial status has been recorded and updated are also discussed. We also consider strategic issues such as important safety considerations, novel vectors and hurdles for translating academic breakthroughs to the clinic. Small nucleic acid therapeutics have produced favorable results in clinical trials and have the potential to address previously "undruggable" targets, suggesting that they could be useful for guiding the development of additional clinical candidates.

Small interfering RNA (siRNA) has emerged as a promising therapeutic candidate against previously intractable diseases. An effective siRNA must have high on-target activity while off-target effects are minimized. This balance can be achieved by enhancing the selectivity of the antisense strand through sequence optimization and appropriate chemical modifications. Acyclic artificial nucleic acids such as serinol nucleic acids (SNA) have demonstrated on-target activity while suppressing off-target effects. This article provides guidelines for designing SNA-modified siRNA and outlines a method for the experimental evaluation of the on-target and off-target activities of siRNAs, ensuring accurate functional validation in cell systems. These protocols benefit researchers developing siRNA-based therapeutics to optimize siRNA selectivity and efficacy while minimizing off-target effects through innovative design strategies. © 2025 Wiley Periodicals LLC. Basic Protocol 1: Design of SNA-modified siRNA Basic Protocol 2: Design and preparation of vector plasmids using inverse PCR Alternate Protocol: Design and preparation of vector plasmid using restriction enzymes and ligase Basic Protocol 3: Evaluation of the on- and off-target effects of siRNAs using the dual-luciferase assay Support Protocol 1: Agarose gel electrophoresis and protocol for purifying DNA from gels Support Protocol 2: Transformation and amplification of plasmids.

Aminoglycosides (AGs) are highly potent, broad-spectrum antibiotics frequently used as first-line treatments for multiple life-threatening infections. Despite their severe ototoxicity, causing irreversible hearing loss in millions of people annually, no preventive therapy has been approved. We previously reported that GABARAP and several other central autophagy proteins are essential for AG-induced hearing loss. This finding opens avenues for the rational design and development of inhibitors that selectively target proteins in this pathway, thereby mitigating AG ototoxicity. In this study, we generated a mouse model with a targeted deletion of GABARAPL1, a homolog of GABARAP, and another model deficient in both GABARAP and GABARAPL1. We found that normal hearing is unaffected by the depletion of these proteins. Remarkably, both proteins are essential for AG-induced hearing loss, with GABARAP playing a more significant role. To further explore the therapeutic potential, we designed and validated short hairpin RNAs targeting the mouse and human GABARAP gene. By inhibiting GABARAP expression in inner ear hair cells using adeno-associated virus-mediated RNA interference, we successfully prevented AG-induced hair cell death and subsequent hearing loss. Our findings underscore the critical role of GABARAP in AG ototoxicity and highlight its potential as a therapeutic target for preventing AG-induced hearing loss.

Hybridization-dependent off-target (OffT) effects, occurring when oligonucleotides bind via Watson-Crick-Franklin hybridization to unintended RNA transcripts, remain a critical safety concern for oligonucleotide therapeutics (ONTs). Despite the importance of OffT assessment of clinical trial ONT candidates, formal guidelines are lacking, with only brief mentions in Japanese regulatory documents (2020) and US Food and Drug Administration (FDA) recommendations for hepatitis B virus treatments (2022). This article presents updated industry recommendations for assessing OffTs of ONTs, building upon the 2012 Oligonucleotide Safety Working Group (OSWG) recommendations and accounting for recent technological advancements. A new OSWG subcommittee, comprising industry experts in RNase H-dependent and steric blocking antisense oligonucleotides and small interfering RNAs, has developed a comprehensive framework for OffT assessment. The proposed workflow encompasses five key steps: (1) OffT identification through in silico complementarity prediction and transcriptomics analysis, (2) focus on cell types with relevant ONT activity, (3) in vitro verification and margin assessment, (4) risk assessment based on the OffT biological role, and (5) management of unavoidable OffTs. The authors provide detailed considerations for various ONT classes, emphasizing the importance of ONT-specific factors such as chemistry, delivery systems, and tissue distribution in OffT evaluation. The article also explores the potential of machine learning models to enhance OffT prediction and discusses strategies for experimental verification and risk assessment. These updated recommendations aim to improve the safety profile of ONTs entering clinical trials and to manage unavoidable OffTs. The authors hope that these recommendations will serve as a valuable resource for ONT development and for the forthcoming finalization of the FDA draft guidance and the International Council for Harmonization S13 guidance on Nonclinical Safety Assessment of Oligonucleotide-Based Therapeutics.

Emergence of the Chikungunya virus (CHIKV) is a new threat in the world. The disastrous effect of this virus and the unavailability of specific drugs complicated the control and management of the disease. The development of a siRNA-based drug using multiple computational tools could be a way out as one of its therapeutics. Currently, very few siRNAs against CHIKV have been computationally designed and published. Here, we considered various parts of the CHIKV genome encoding different essential protein-coding genes for designing siRNAs with a view to silencing them, thereby rendering the virus inactive. Seven potential primary siRNAs were constructed, of which, five are hereafter recommended to be used as a therapeutic tool against the virus.

Current treatments for retinal disorders are anti-angiogenic agents, laser photocoagulation, and photodynamic therapies. These conventional treatments focus on reducing abnormal blood vessel formation in the retina, which, in a low-oxygen environment, can lead to harmful proliferation of endothelial cells. This results in dysfunctional, leaky blood vessels that cause retinal edema, hemorrhage, and vision loss. Age-related Macular Degeneration is a primary cause of vision loss and blindness in the elderly, impacting around 20% of those over 50 years old. This complex disease is also closely related to oxidative stress in retina. In this review, we explore the challenge of treating retinal diseases, alternatives and possibilities of enhancing the effectiveness of therapies using co-delivery systems containing both antiangiogenic and antioxidant therapeutic agents. Despite recent proposals potential, the lack of extensive clinical studies on the long-term outcomes and optimal combinations of therapies means that the full risk profile and effectiveness of combined therapy are not yet completely understood. These factors must be carefully considered and managed by healthcare providers to optimize treatment outcomes and ensure patient safety.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that lacks hormone receptor and Her2 (ERBB2) expression, leaving chemotherapy as the only treatment option. The urgent need for targeted therapy for TNBC patients has led to the investigation of small interfering RNAs (siRNAs), which can target genes in a sequence-specific manner, unlike other drugs. However, the clinical translation of siRNAs has been hindered by the lack of an effective delivery system, except in the case of liver diseases. The MYC oncogene is commonly overexpressed in TNBC compared to other breast cancer subtypes. In this study, we used siRNA to target MYC in MDA-MB-231, MDA-MB-157, MDA-MB-436 and Hs-578T cells. We designed various symmetric and asymmetric (asiRNAs), screened them for in vitro efficacy, modified them for enhanced nuclease resistance and reduced off-target effects, and conjugated them with cholesterol (ChoL) and docosanoic acid (DCA) as a delivery system. DCA was conjugated to the 3' end of asiRNA by a cleavable phosphodiester linker for in vivo delivery. Our findings demonstrated that asiRNA-VP and Mod_asiRNA10-6 efficiently downregulated MYC and its downstream targets, including RRM2, RAD51 and PARP1. Moreover, in a tumor xenograft model, asiRNA-VP-DCA effectively knocked down MYC mRNA and protein expression. Remarkably, durable knockdown persisted for at least 46 days postdosing in mouse tumor xenografts, with no visible signs of toxicity, underscoring the safety of DCA-conjugated asiRNAs. In conclusion, this study developed novel asiRNAs, design platforms, validated modification patterns, and in vivo delivery systems specifically targeting MYC in TNBC.

Human Immunodeficiency Virus (HIV) is a retrovirus with single-stranded RNA that leads to the challenging disease of acquired immunodeficiency syndrome (AIDS). Combination antiretroviral therapy (cART) can prevent the progression of the disease, but it is not capable of long-term HIV elimination. One of the significant obstacles to treating HIV-1-infected individuals is the creation of latent cell reservoirs early in the infection. Gene-based therapies that utilize RNA interference (RNAi) to silence host or viral gene expression are considered promising therapeutic approaches. It has been demonstrated that RUNX1, a T-cell-specific transcription factor, may significantly affect HIV replication and infection. According to accumulating evidence on the role of interfering RNA techniques in inhibiting gene expression and considering the role of RUNX1 in the replication of HIV-1. In this study, we aim to design shRNAs against RUNX1 that can target the replication of HIV-1.

Several computational methods, including target alignment, similarity search, and secondary structure prediction, have been employed in the design of shRNA against RUNX1.

Seven shRNA molecules with the highest efficiency were designed and validated using computational methods to silence the RUNX1 gene.

In the present study, we designed shRNA against RUNX1, which can target latent cells infected with HIV. Suppression of RUNX1 by shRNA reactivates HIV in the latent cells and subsequently potentiates the immune response toward identifying accurate virus-infected cells. This process may lead to an effective and efficient reduction of the volume of cell reservoirs infected with HIV.

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.

Small interfering RNA (siRNA) has revolutionised biomedical research and drug development through precise post-transcriptional gene silencing technology. Despite its immense potential, siRNA therapy still faces technical challenges, such as delivery efficiency, targeting specificity, and molecular stability. To address these challenges and facilitate siRNA drug development, we have developed siRNAEfficacyDB, a comprehensive database that integrates experimentally validated siRNA efficacy data. This database contains 3544 siRNA records, covering 42 target genes and 5 cell lines. It provides detailed information on siRNA sequences, target genes, inhibition efficiencies, experimental techniques, cell lines, siRNA concentrations, and incubation times. siRNAEfficacyDB offers a user-friendly web interface that makes it easy to query, browse and analyse data, enabling efficient access to siRNA-related information. In summary, siRNAEfficacyDB provides a useful data foundation for siRNA drug design and optimisation, serving as a valuable resource for advancing computer-aided siRNA design research and nucleic acid drug development. siRNAEfficacyDB is freely available at https://cellknowledge.com.cn/siRNAEfficacy for non-commercial use.

Pasteurella multocida (P. multocida) can cause infection in various animals, especially livestock and poultry, which can lead to substantial losses to the breeding industry. However, the pathogenesis of avian P. multocida remains largely unknown. In this study, the mechanisms of avian P. multocida pathogenesis were explored. Chicken macrophage HD11 cells were infected with the avian strain PmQ and the bovine strain PmCQ2. PmQ induced higher cytotoxicity and apoptosis and exerted a stronger anti-phagocytotic effect on HD11 cells than PmCQ2. RNA sequencing analysis revealed that focal adhesion (FA)-related genes were significantly downregulated in PmQ-infected HD11 cells compared with that of PmCQ2. Subsequently, phalloidin staining of the F-actin assembly revealed that PmQ more significantly inhibited the formation of FAs in HD11 than PmCQ2. Western blot analysis revealed that the levels of Zyxin and phosphorylated focal adhesion kinase (FAK) were significantly decreased in PmQ-infected cells, confirming that PmQ inhibited FAs. Consequently, PmQ inhibited the FA downstream factor Akt, which decreased NF-κB and FoxO1 phosphorylation, as evidenced by the decreased expression of downstream anti-apoptotic genes (GADD45B, BCL2L1, BCL2A1, and BIRC2) and increased expression of downstream pro-apoptotic genes (BCL6, PKL2, PKL3, and KLF2). Conversely, pharmaceutically inhibiting FA formation using latrunculin A better enhanced PmCQ2-induced than PmQ-induced apoptosis in HD11 cells. Similarly, the knockdown of Zyxin or FoxO1 by siRNA both boosted the PmCQ2-induced apoptosis rates equal to those of PmQ. These results demonstrated that PmQ inhibited Zyxin-dependent FA formation and disrupted the FAK-AKT-FoxO1/NF-κB pathway to induce apoptosis in chicken macrophages. This study thus offers insights into the pathogenesis of avian P. multocida, which could facilitate the development of new strategies against P. multocida infection.

In this study, we report the synthesis of 2'-formamidonucleoside phosphoramidite derivatives and their incorporation into siRNA strands to reduce seed-based off-target effects of small interfering RNAs (siRNAs). Formamido derivatives of all four nucleosides (A, G, C and U) were synthesized in 5-11 steps from commercial compounds. Introducing these derivatives into double-stranded RNA slightly reduced its thermodynamic stability, but X-ray crystallography and CD spectrum analysis confirmed that the RNA maintained its natural A-form structure. Although the introduction of the 2'-formamidonucleoside derivative at the 2nd position in the guide strand of the siRNA led to a slight decrease in the on-target RNAi activity, the siRNAs with different sequences incorporating 2'-formamidonucleoside with four kinds of nucleobases into any position other than 2nd position in the seed region revealed a significant suppression of off-target activity while maintaining on-target RNAi activity. This indicates that 2'-formamidonucleosides represent a promising approach for mitigating off-target effects in siRNA therapeutics.

RNA interference (RNAi) has become a widely used experimental approach for post-transcriptional regulation and is increasingly showing its potential as future targeted drugs. However, the prediction of highly efficient siRNAs (small interfering RNAs) is still hindered by dataset biases, the inadequacy of prediction methods, and the presence of off-target effects. To overcome these limitations, we propose an accurate and robust prediction method, OligoFormer, for siRNA design.

OligoFormer comprises three different modules including thermodynamic calculation, RNA-FM module, and Oligo encoder. Oligo encoder is the core module based on the transformer encoder. Taking siRNA and mRNA sequences as input, OligoFormer can obtain thermodynamic parameters, RNA-FM embedding, and Oligo embedding through these three modules, respectively. We carefully benchmarked OligoFormer against six comparable methods on siRNA efficacy datasets. OligoFormer outperforms all the other methods, with an average improvement of 9% in AUC, 6.6% in PRC, 9.8% in F1 score, and 5.1% in PCC compared to the best method among them in our inter-dataset validation. We also provide a comprehensive pipeline with prediction of siRNA efficacy and off-target effects using PITA score and TargetScan score. The ablation study shows RNA-FM module and thermodynamic parameters improved the performance and accelerated convergence of OligoFormer. The saliency maps by gradient backpropagation and base preference maps show certain base preferences in initial and terminal region of siRNAs.

The source code of OligoFormer is freely available on GitHub at: https://github.com/lulab/OligoFormer. Docker image of OligoFormer is freely available on the docker hub at https://hub.docker.com/r/yilanbai/oligoformer.

The clinical adoption of small interfering RNAs (siRNAs) has prompted the development of various computational strategies for siRNA design, from traditional data analysis to advanced machine learning techniques. However, previous studies have inadequately considered the full complexity of the siRNA silencing mechanism, neglecting critical elements such as siRNA positioning on mRNA, RNA base-pairing probabilities, and RNA-AGO2 interactions, thereby limiting the insight and accuracy of existing models. Here, we introduce siRNADiscovery, a Graph Neural Network (GNN) framework that leverages both non-empirical and empirical rule-based features of siRNA and mRNA to effectively capture the complex dynamics of gene silencing. On multiple internal datasets, siRNADiscovery achieves state-of-the-art performance. Significantly, siRNADiscovery also outperforms existing methodologies in in vitro studies and on an externally validated dataset. Additionally, we develop a new data-splitting methodology that addresses the data leakage issue, a frequently overlooked problem in previous studies, ensuring the robustness and stability of our model under various experimental settings. Through rigorous testing, siRNADiscovery has demonstrated remarkable predictive accuracy and robustness, making significant contributions to the field of gene silencing. Furthermore, our approach to redefining data-splitting standards aims to set new benchmarks for future research in the domain of predictive biological modeling for siRNA.

Here, we present a protocol for small interfering RNA (siRNA)-mediated U1 small nuclear RNA (snRNA) knockdown using fluorinated α-helical polypeptide in macrophages and mouse lungs, providing a dependable approach to silence U1 snRNA in vitro and in vivo. We describe steps for preparing P7F7/siRNA polyplexes and silencing U1 snRNA with P7F7/siRNA polyplexes in macrophages and mouse lungs. Knockdown efficiency is validated through reverse-transcription quantitative real-time PCR analysis. This protocol is applicable for studying the physiological or pathophysiological function of U1 snRNA. For complete details on the use and execution of this protocol, please refer to Zhang et al.1.

The intrinsic nature of CRISPR-Cas in conferring immunity to bacteria and archaea has been repurposed to combat pathogenic agents in mammalian and plant cells. In this regard, CRISPR-Cas13 systems have proved their remarkable potential for single-strand RNA viruses targeting. Here, different types of Cas13 orthologs were applied to knockdown foot-and-mouth disease virus (FMDV), a highly contagious disease of a wide variety of species with genetically diverse strains and is widely geographically distributed. Using programmable CRISPR RNAs capable of targeting conserved regions of the viral genome, all Cas13s from CRISPR system type VI (subtype A/B/D) could comprehensively target and repress different serotypes of FMDV virus. This approach has the potential to destroy all strains of a virus as targets the ultra-conserved regions of genome. We experimentally compared the silencing efficiency of CRISPR and RNAi by designing the most effective short hairpin RNAs according to our developed scoring system and observed comparable results. This study showed successful usage of various Cas13 enzymes for suppression of FMDV, which provides a flexible strategy to battle with other animal infectious RNA viruses, an underdeveloped field in the biotechnology scope.

Multiple sclerosis (MS), an intricate neurological disorder, continues to challenge our understanding of the pivotal interplay between the immune system and the central nervous system (CNS). This condition arises from the immune system's misdirected attack on nerve fiber protection, known as myelin sheath, alongside nerve fibers themselves. This enigmatic condition, characterized by demyelination and varied clinical manifestations, prompts exploration into its multifaceted etiology and potential therapeutic avenues. Research has revealed a potential connection between Epstein Barr virus (EBV), specifically Epstein Barr Nuclear Antigen 1 (EBNA-1), and MS. The immune response to EBNA-1 antigen triggers the production of anti-EBNA-1 molecules, including IgG that identify a similar amino acid sequence to EBNA-1 in myelin, inadvertently targeting myelin sheath and contributing to MS progression. Currently, no treatment exists for EBNA-1-induced MS apart from symptom management. Addressing this, a novel potential therapeutic avenue utilizing small interference RNAs (siRNA) has been designed. By targeting the conserved EBNA-1 gene sequences in EBV types 1 and 2, five potential siRNAs were identified in our analysis. Thorough evaluations encompassing off-target binding, thermodynamics and secondary structure elucidation, efficacy prediction, siRNA-mRNA sequence binding affinity exploration, melting temperature, and docking of siRNAs with human argonaute protein 2 (AGO2) were conducted to elucidate the siRNAs efficiency. These designed siRNA molecules harnessed promising silencing activity in the EBNA-1 gene encoding the EBNA-1 antigen protein and thus have the potential to mitigate the severity of this dangerous virus.

The clinical use of RNA interference (RNAi) molecular mechanisms has introduced a novel, growing class of RNA therapeutics capable of treating diseases by controlling target gene expression at the posttranscriptional level. With the newly approved nedosiran (Rivfloza), there are now six RNAi-based therapeutics approved by the United States Food and Drug Administration (FDA). Interestingly, five of the six FDA-approved small interfering RNA (siRNA) therapeutics [patisiran (Onpattro), lumasiran (Oxlumo), inclisiran (Leqvio), vutrisiran (Amvuttra), and nedosiran] were revealed to act on the 3'-untranslated regions of target mRNAs, instead of coding sequences, thereby following the common mechanistic action of genome-derived microRNAs (miRNA). Furthermore, three of the FDA-approved siRNA therapeutics [patisiran, givosiran (Givlaari), and nedosiran] induce target mRNA degradation or cleavage via near-complete rather than complete base-pair complementarity. These features along with previous findings confound the currently held characteristics to distinguish siRNAs and miRNAs or biosimilars, of which all converge in the RNAi regulatory pathway action. Herein, we discuss the RNAi mechanism of action and current criteria for distinguishing between miRNAs and siRNAs while summarizing the common and unique chemistry and molecular pharmacology of the six FDA-approved siRNA therapeutics. The term "RNAi" therapeutics, as used previously, provides a coherently unified nomenclature for broader RNAi forms as well as the growing number of therapeutic siRNAs and miRNAs or biosimilars that best aligns with current pharmacological nomenclature by mechanism of action. SIGNIFICANCE STATEMENT: The common and unique chemistry and molecular pharmacology of six FDA-approved siRNA therapeutics are summarized, in which nedosiran is newly approved. We point out rather a surprisingly mechanistic action as miRNAs for five siRNA therapeutics and discuss the differences and similarities between siRNAs and miRNAs that supports using a general and unified term "RNAi" therapeutics to align with current drug nomenclature criteria in pharmacology based on mechanism of action and embraces broader forms and growing number of novel RNAi therapeutics.

Recent studies have highlighted the effectiveness of using antisense oligonucleotides (ASOs) for cellular RNA regulation, including targets that are considered undruggable; however, manually designing optimal ASO sequences can be labor intensive and time consuming, which potentially limits their broader application. To address this challenge, we introduce a platform, the ASOptimizer, a deep-learning-based framework that efficiently designs ASOs at a low cost. This platform not only selects the most efficient mRNA target sites but also optimizes the chemical modifications for enhanced performance. Indoleamine 2,3-dioxygenase 1 (IDO1) promotes cancer survival by depleting tryptophan and producing kynurenine, leading to immunosuppression through the aryl-hydrocarbon receptor (Ahr) pathway within the tumor microenvironment. We used ASOptimizer to identify ASOs that target IDO1 mRNA as potential cancer therapeutics. Our methodology consists of two stages: sequence engineering and chemical engineering. During the sequence-engineering stage, we optimized and predicted ASO sequences that could target IDO1 mRNA efficiently. In the chemical-engineering stage, we further refined these ASOs to enhance their inhibitory activity while reducing their potential cytotoxicity. In conclusion, our research demonstrates the potential of ASOptimizer for identifying ASOs with improved efficacy and safety.

Cotton leaf curl disease (CLCuD), caused by the Cotton leaf curl virus, is one of the most irrepressible diseases in cotton due to high recombination in the virus. RNA interference (RNAi) is widely used as a biotechnological approach for sequence-specific gene silencing guided by small interfering RNAs (siRNAs) to generate resistance against viruses. The success of RNAi depends upon the fact that the target site of the designed siRNA must be conserved even if the genome undergoes recombination. Thus, the present study designs the most efficient siRNA against the conserved sites of the Cotton leaf curl Multan virus (CLCuMuV) and the Cotton leaf curl Multan betasatellite (CLCuMB). From an initial prediction of 9 and 7 siRNAs against CLCuMuV and CLCuMB, respectively, the final selection was made for 2 and 1 siRNA based on parameters such as no off-targets, good GC content, high validity score, and targeting coding region. The target sites of siRNA were observed to lie in the AC3 and an overlapping region of AC2-AC1 of CLCuMuV and βC1 of CLCuMB; all target sites showed a highly conserved nature in recombination analysis. Docking the designed siRNAs with the Argonaute-2 protein of Gossypium hirsutum showed stable binding. Finally, BLASTn of siRNA-target positions in genomes of other BGVs indicated the suitability of designed siRNAs against a broad range of BGVs. The designed siRNAs of the present study could help gain complete control over the virus, though experimental validation is highly required to suggest predicted siRNAs for CLCuD resistance.

The online version contains supplementary material available at 10.1007/s12088-024-01191-z.

RNA silencing is a post-transcriptional gene-silencing mechanism mediated by microRNAs (miRNAs). However, the regulatory mechanism of RNA silencing during viral infection is unclear. TAR RNA-binding protein (TRBP) is an enhancer of RNA silencing that induces miRNA maturation by interacting with the ribonuclease Dicer. TRBP interacts with a virus sensor protein, laboratory of genetics and physiology 2 (LGP2), in the early stage of viral infection of human cells. Next, it induces apoptosis by inhibiting the maturation of miRNAs, thereby upregulating the expression of apoptosis regulatory genes. In this study, we show that TRBP undergoes a functional conversion in the late stage of viral infection. Viral infection resulted in the activation of caspases that proteolytically processed TRBP into two fragments. The N-terminal fragment did not interact with Dicer but interacted with type I interferon (IFN) signaling modulators, such as protein kinase R (PKR) and LGP2, and induced ER stress. The end results were irreversible apoptosis and suppression of IFN signaling. Our results demonstrate that the processing of TRBP enhances apoptosis, reducing IFN signaling during viral infection.

In this protocol, we describe the small interfering RNA (siRNA)-mediated gene knockdown in primary mouse microglia, providing an approach to investigate functions such as phagocytosis and chemotaxis. The approach includes siRNA design, establishment of mixed glial cultures, microglia isolation, and siRNA transfection. Validation of knockdown efficacy employs quantitative immunoblot analysis. This technique empowers the investigation of specific molecular and cellular functions within the intricate microenvironment of the brain, comprising diverse cell types. For complete details on the use and execution of this protocol, please refer to Iguchi et al. (2023).1.

A large number of long non-coding RNAs (lncRNAs) are expressed in animal gonads, but their functions are poorly understood. In this study, a gonad-specific lncRNA, termed lnc4, was identified and characterized in the model fish medaka (Oryzias latipes). The expression pattern and in vitro functional analyses indicated that lnc4 was likely to be a primary transcript of miR-202 (pri-miR-202). Results of single-molecule fluorescence in situ hybridization demonstrated that the precursor miR-202 (pre-miR-202) was highly expressed in the nuclei of testicular somatic cells, including Leydig and Sertoli cells, whereas only a small amount of lnc4 molecules could be detected co-expressed with pre-miR-202 in Sertoli cells due to its low expression level. Deletion of the lnc4 locus led to a significant reduction in testis size and a dramatic decrease in the number of male germ cells, as well as a reduction in sperm viability. Moreover, lnc4 knockout resulted in enhanced synthesis and secretion of testicular somatic cells and accelerated differentiation of immature male germ cells. Taken together, functional studies of lnc4 and its mature transcript miR-202 will contribute to the understanding of the important role of non-coding RNAs in animal or human reproductive disorders.

The aim of this study is to develop a novel antiviral strategy capable of efficiently targeting a broad set of SARS-CoV-2 variants.

Since the first emergence of SARS-CoV-2, it has rapidly transformed into a global pandemic, posing an unprecedented threat to public health. SARS-CoV-2 is prone to mutation and continues to evolve, leading to the emergence of new variants capable of escaping immune protection achieved due to previous SARS-CoV-2 infections or by vaccination.

RNA interference (RNAi) is a remarkable biological mechanism that can induce gene silencing by targeting complementary mRNA and inhibiting its translation.

In this study, using the computational approach, we predicted the most efficient siRNA capable of inhibiting SARS-CoV-2 variants of concern (VoCs).

The presented siRNA was characterized and evaluated for its thermodynamic properties, offsite-target hits, and in silico validation by molecular docking and molecular dynamics simulations (MD) with Human AGO2 protein.

The study contributes to the possibility of designing and developing an effective response strategy against existing variants of concerns and preventing further.

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.

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

Ribonucleic acid (RNA) is of great interest in many different therapeutic areas including infectious diseases such as immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS). Thanks to current, advanced treatments for HIV, the diagnosis is no longer a death sentence. However, even with these treatments, latency is suggested to persist in T-lymphocyte-rich tissues including gut-associated lymphatic tissue (GALT), spleen, and bone marrow making HIV an incurable disease. Therefore, it is important to design systems that can effectively deliver therapeutics to these tissues to fight latent infection and find a functional cure. Numerous therapeutics ranging from small molecules to cell therapies have been explored as a cure for HIV but have failed to maintain therapeutic longevity. RNA interference (RNAi) provides a unique opportunity to achieve a functional cure for those who suffer from chronic HIV/AIDS by suppressing replication of the virus. However, RNA has certain imitations in delivery as it cannot be delivered without a carrier due to its negative charge and degradation from endogenous nucleases. Here, we provide a detailed analysis of explored systems for siRNA delivery for HIV/AIDS in the context of RNA therapeutic design and nanoparticle design. In addition, we suggest strategies that should be used to target specific tissues that are rich in lymphatic tissue.

Small interfering RNA (siRNA) and short hairpin RNA (shRNA) are widely used as RNA interference (RNAi) reagents. Recently, truncated shRNAs that trigger RNAi in a Dicer-independent manner have been developed. We generated a novel class of RNAi reagent, designated enforced strand bias (ESB) RNA, in which an siRNA duplex was chemically bridged between the 3' terminal overhang region of the guide strand and the 5' terminal nucleotide of the passenger strand. ESB RNA, which is chemically bridged at the 2' positions of ribose (2'-2' ESB RNA), functions in a Dicer-independent manner and was highly effective at triggering RNAi without the passenger strand-derived off-target effect. In addition, the 2'-2' ESB RNA exhibited a unique target sequence preference that differs from siRNA and silenced target sequences that could not be effectively suppressed by siRNA. Our results indicate that ESB RNA has the potential to be an effective RNAi reagent even when the target sequence is not suitable for siRNA.

One of the most notable required features of wound healing is the enhancement of angiogenesis, which aids in the acceleration of regeneration. Poor angiogenesis during diabetic wound healing is linked to a shortage of pro-angiogenic or an increase in anti-angiogenic factors. As a result, a potential treatment method is to increase angiogenesis promoters and decrease suppressors. Incorporating microRNAs (miRNAs) and small interfering RNAs (siRNAs), two forms of quite small RNA molecules, is one way to make use of RNA interference. Several different types of antagomirs and siRNAs are now in the works to counteract the negative effects of miRNAs. The purpose of this research is to locate novel antagonists for miRNAs and siRNAs that target multiple genes to promote angiogenesis and wound healing in diabetic ulcers.In this context, we used gene ontology analysis by exploring across several datasets. Following data analysis, it was processed using a systems biology approach. The feasibility of incorporating the proposed siRNAs and miRNA antagomirs into polymeric bioresponsive nanocarriers for wound delivery was further investigated by means of a molecular dynamics (MD) simulation study. Among the three nanocarriers tested (Poly (lactic-co-glycolic acid) (PLGA), Polyethylenimine (PEI), and Chitosan (CTS), MD simulations show that the integration of PLGA/hsa-mir-422a is the most stable (total energy = -1202.62 KJ/mol, Gyration radius = 2.154 nm, and solvent-accessible surface area = 408.416 nm2). With values of -25.437 KJ/mol, 0.047 nm for the Gyration radius, and 204.563 nm2 for the SASA, the integration of the second siRNA/ Chitosan took the last place. The results of the systems biology and MD simulations show that the suggested RNA may be delivered through bioresponsive nanocarriers to speed up wound healing by boosting angiogenesis.

Small interfering RNA (siRNA)-mediated mRNA degradation approach have imparted its eminence against several difficult-to-treat genetic disorders and other allied diseases. Viral outbreaks and resulting pandemics have repeatedly threatened public health and questioned human preparedness at the forefront of drug design and biomedical readiness. During the recent pandemic caused by the SARS-CoV-2, mRNA-based vaccination strategies have paved the way for a new era of RNA therapeutics. RNA Interference (RNAi) based approach using small interfering RNA may complement clinical management of the COVID-19. RNA Interference approach will primarily work by restricting the synthesis of the proteins required for viral replication, thereby hampering viral cellular entry and trafficking by targeting host as well as protein factors. Despite promising benefits, the stability of small interfering RNA in the physiological environment is of grave concern as well as site-directed targeted delivery and evasion of the immune system require immediate attention. In this regard, nanotechnology offers viable solutions for these challenges. The review highlights the potential of small interfering RNAs targeted toward specific regions of the viral genome and the features of nanoformulations necessary for the entrapment and delivery of small interfering RNAs. In silico design of small interfering RNA for different variants of SARS-CoV-2 has been discussed. Various nanoparticles as promising carriers of small interfering RNAs along with their salient properties, including surface functionalization, are summarized. This review will help tackle the real-world challenges encountered by the in vivo delivery of small interfering RNAs, ensuring a safe, stable, and readily available drug candidate for efficient management of SARS-CoV-2 in the future.

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.

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.

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.

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

Dengue and Japanese encephalitis virus (JEV) are mosquito-borne RNA viruses that can cause severe illness leading to death in the tropics and subtropics. Both of these viruses interact directly with the C-type lectin domain family 5, member A receptor (CLEC5A) on human macrophages which stimulates the release of proinflammatory cytokines. Since blockade of this interaction has been shown to suppress the secretion of cytokines, CLEC5A is considered a potential target for the development of new treatments to reduce virus-induced brain damage. Developing a vaccine against dengue is challenging because this virus can cause disease through 4 different serotypes. Therefore, the vaccine must immunize against all 4 serotypes to be effective, while unvaccinated people still contract JEV and suffer from its complications. Small interfering RNAs (siRNAs) play an important role in regulating gene expression by causing the degradation of target mRNAs. In this study, we attempted to rationally design potential siRNA molecules using various software, targeting the CLEC5A gene. In total, 3 siRNAs were found to be potential candidates for CLEC5A silencing. They showed good target accessibility, optimum guanine-cytosine (GC) content, the least chance of off-target effects, positive energy of folding, and strong interaction with Argonaute2 protein as denoted by a negative docking energy score. In addition, molecular dynamics simulation of the siRNA-Ago2-docked complexes showed the stability of the complexes over 1.5 nanoseconds. These predicted siRNAs might effectively downregulate the expression of the CLEC5A receptor and thus prove vital in the treatment of dengue and JEV infections.

Many biological systems are characterised by biological entities, as well as their relationships. These interaction networks can be modelled as graphs, with nodes representing bio-entities, such as molecules, and edges representing relations among them, such as interactions. Due to the current availability of a huge amount of biological data, it is very important to consider in silico analysis methods based on, for example, machine learning, that could take advantage of the inner graph structure of the data in order to improve the quality of the results. In this scenario, graph neural networks (GNNs) are recent computational approaches that directly deal with graph-structured data. In this paper, we present a GNN network for the analysis of siRNA-mRNA interaction networks. siRNAs, in fact, are small RNA molecules that are able to bind to target genes and silence them. These events make siRNAs key molecules as RNA interference agents in many biological interaction networks related to severe diseases such as cancer. In particular, our GNN approach allows for the prediction of the siRNA efficacy, which measures the siRNA's ability to bind and silence a gene target. Tested on benchmark datasets, our proposed method overcomes other machine learning algorithms, including the state-of-the-art predictor based on the convolutional neural network, reaching a Pearson correlation coefficient of approximately 73.6%. Finally, we proposed a case study where the efficacy of a set of siRNAs is predicted for a gene of interest. To the best of our knowledge, GNNs were used for the first time in this scenario.

RNAs provide considerable opportunities as therapeutic agent to expand the plethora of classical therapeutic targets, from extracellular and surface proteins to intracellular nucleic acids and its regulators, in a wide range of diseases. RNA versatility can be exploited to recognize cell types, perform cell therapy, and develop new vaccine classes. Therapeutic RNAs (aptamers, antisense nucleotides, siRNA, miRNA, mRNA and CRISPR-Cas9) can modulate or induce protein expression, inhibit molecular interactions, achieve genome editing as well as exon-skipping. A common RNA thread, which makes it very promising for therapeutic applications, is its structure, flexibility, and binding specificity. Moreover, RNA displays peculiar structural plasticity compared to proteins as well as to DNA. Here we summarize the recent advances and applications of therapeutic RNAs, and the experimental and computational methods to analyze their structure, by biophysical techniques (liquid-state NMR, scattering, reactivity, and computational simulations), with a focus on dynamic and flexibility aspects and to binding analysis. This will provide insights on the currently available RNA therapeutic applications and on the best techniques to evaluate its dynamics and reactivity.