In silico selection of active siRNA

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.

Small interfering RNA (siRNA)-based therapeutic applications against viruses: principles, potential, and challenges

RNA has emerged as a revolutionary and important tool in the battle against emerging infectious diseases, with roles extending beyond its applications in vaccines, in which it is used in the response to the COVID-19 pandemic. Since their development in the 1990s, RNA interference (RNAi) therapeutics have demonstrated potential in reducing the expression of disease-associated genes. Nucleic acid-based therapeutics, including RNAi therapies, that degrade viral genomes and rapidly adapt to viral mutations, have emerged as alternative treatments. RNAi is a robust technique frequently employed to selectively suppress gene expression in a sequence-specific manner. The swift adaptability of nucleic acid-based therapeutics such as RNAi therapies endows them with a significant advantage over other antiviral medications. For example, small interfering RNAs (siRNAs) are produced on the basis of sequence complementarity to target and degrade viral RNA, a novel approach to combat viral infections. The precision of siRNAs in targeting and degrading viral RNA has led to the development of siRNA-based treatments for diverse diseases. However, despite the promising therapeutic benefits of siRNAs, several problems, including impaired long-term protein expression, siRNA instability, off-target effects, immunological responses, and drug resistance, have been considerable obstacles to the use of siRNA-based antiviral therapies. This review provides an encompassing summary of the siRNA-based therapeutic approaches against viruses while also addressing the obstacles that need to be overcome for their effective application. Furthermore, we present potential solutions to mitigate major challenges.

An in-silico approach to design potential siRNAs against the ORF57 of Kaposi's sarcoma-associated herpesvirus

Kaposi's sarcoma-associated herpesvirus (KSHV) is one of the few human oncogenic viruses, which causes a variety of malignancies, including Kaposi's sarcoma, multicentric Castleman disease, and primary effusion lymphoma, particularly in human immunodeficiency virus patients. The currently available treatment options cannot always prevent the invasion and dissemination of this virus. In recent times, siRNA-based therapeutics are gaining prominence over conventional medications as siRNA can be designed to target almost any gene of interest. The ORF57 is a crucial regulatory protein for lytic gene expression of KSHV. Disruption of this gene translation will inevitably inhibit the replication of the virus in the host cell. Therefore, the ORF57 of KSHV could be a potential target for designing siRNA-based therapeutics. Considering both sequence preferences and target site accessibility, several online tools (i-SCORE Designer, Sfold web server) had been utilized to predict the siRNA guide strand against the ORF57. Subsequently, off-target filtration (BLAST), conservancy test (fuzznuc), and thermodynamics analysis (RNAcofold, RNAalifold, and RNA Structure web server) were also performed to select the most suitable siRNA sequences. Finally, two siRNAs were identified that passed all of the filtration phases and fulfilled the thermodynamic criteria. We hope that the siRNAs predicted in this study would be helpful for the development of new effective therapeutics against KSHV.

Capsule-like Safe Genetic Vectors-Cell-Penetrating Core-Shell Particles Selectively Release Functional Small RNA and Entrap Its Encoding DNA

The breakthrough of genetic therapy is set back by the lack of suitable genetic vector systems. We present the development of permeability-tunable, capsule-like, polymeric, micron-sized, core-shell particles for delivery of recombinant nucleic acids into target cells. These particles were demonstrated to effectively release rod-shaped small hairpin RNA and to selectively retain the RNA-encoding DNA template, which was designed to form a bulky tripartite structure. Thus, they can serve as delivery vectors preloaded with cargo RNA or alternatively as RNA-producing micro-bioreactors. The internalization of particles by human tissue culture cells inversely correlated with particle size and with the cell to particle ratio, although at a higher than stoichiometric excess of particles over cells, cell viability was impaired. Among primary human peripheral blood mononuclear cells, up to 50% of the monocytes displayed positive uptake of particles. Finally, these particles efficiently delivered siRNA into HEK293T cells triggering functional knockdown of the target gene lamin A/C. Particle-mediated knockdown was superior to that observed after conventional siRNA delivery via lipofection. Core-shell particles protect encapsulated nucleic acids from degradation and target cell genomes from direct contact with recombinant DNA, thus representing a promising delivery vector system that can be explored for genetic therapy and vaccination.

New Modalities for Challenging Targets in Drug Discovery

Our ever-increasing understanding of biological systems is providing a range of exciting novel biological targets, whose modulation may enable novel therapeutic options for many diseases. These targets include protein-protein and protein-nucleic acid interactions, which are, however, often refractory to classical small-molecule approaches. Other types of molecules, or modalities, are therefore required to address these targets, which has led several academic research groups and pharmaceutical companies to increasingly use the concept of so-called "new modalities". This Review defines for the first time the scope of this term, which includes novel peptidic scaffolds, oligonucleotides, hybrids, molecular conjugates, as well as new uses of classical small molecules. We provide the most representative examples of these modalities to target large binding surface areas such as those found in protein-protein interactions and for biological processes at the center of cell regulation.

In Silico Design and Experimental Validation of siRNAs Targeting Conserved Regions of Multiple Hepatitis C Virus Genotypes

RNA interference (RNAi) is a post-transcriptional gene silencing mechanism that mediates the sequence-specific degradation of targeted RNA and thus provides a tremendous opportunity for development of oligonucleotide-based drugs. Here, we report on the design and validation of small interfering RNAs (siRNAs) targeting highly conserved regions of the hepatitis C virus (HCV) genome. To aim for therapeutic applications by optimizing the RNAi efficacy and reducing potential side effects, we considered different factors such as target RNA variations, thermodynamics and accessibility of the siRNA and target RNA, and off-target effects. This aim was achieved using an in silico design and selection protocol complemented by an automated MysiRNA-Designer pipeline. The protocol included the design and filtration of siRNAs targeting highly conserved and accessible regions within the HCV internal ribosome entry site, and adjacent core sequences of the viral genome with high-ranking efficacy scores. Off-target analysis excluded siRNAs with potential binding to human mRNAs. Under this strict selection process, two siRNAs (HCV353 and HCV258) were selected based on their predicted high specificity and potency. These siRNAs were tested for antiviral efficacy in HCV genotype 1 and 2 replicon cell lines. Both in silico-designed siRNAs efficiently inhibited HCV RNA replication, even at low concentrations and for short exposure times (24h); they also exceeded the antiviral potencies of reference siRNAs targeting HCV. Furthermore, HCV353 and HCV258 siRNAs also inhibited replication of patient-derived HCV genotype 4 isolates in infected Huh-7 cells. Prolonged treatment of HCV replicon cells with HCV353 did not result in the appearance of escape mutant viruses. Taken together, these results reveal the accuracy and strength of our integrated siRNA design and selection protocols. These protocols could be used to design highly potent and specific RNAi-based therapeutic oligonucleotide interventions.

Soft computing model for optimized siRNA design by identifying off target possibilities using artificial neural network model

The ability of small interfering RNA (siRNA) to do posttranscriptional gene regulation by knocking down targeted genes is an important research topic in functional genomics, biomedical research and in cancer therapeutics. Many tools had been developed to design exogenous siRNA with high experimental inhibition. Even though considerable amount of work has been done in designing exogenous siRNA, design of effective siRNA sequences is still a challenging work because the target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. In some cases, siRNAs may tolerate mismatches with the target mRNA, but knockdown of genes other than the intended target could make serious consequences. Hence to design siRNAs, two important concepts must be considered: the ability in knocking down target genes and the off target possibility on any nontarget genes. So before doing gene silencing by siRNAs, it is essential to analyze their off target effects in addition to their inhibition efficacy against a particular target. Only a few methods have been developed by considering both efficacy and off target possibility of siRNA against a gene. In this paper we present a new design of neural network model with whole stacking energy (ΔG) that enables to identify the efficacy and off target effect of siRNAs against target genes. The tool lists all siRNAs against a particular target with their inhibition efficacy and number of matches or sequence similarity with other genes in the database. We could achieve an excellent performance of Pearson Correlation Coefficient (R=0. 74) and Area Under Curve (AUC=0.906) when the threshold of whole stacking energy is ≥-34.6 kcal/mol. To the best of the author's knowledge, this is one of the best score while considering the "combined efficacy and off target possibility" of siRNA for silencing a gene. The proposed model shall be useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in the area of bioinformatics. The software is developed as a desktop application and available at http://opsid.in/opsid/.

Bioinformatics of siRNA design

RNA interference mediated by small interfering RNAs is a powerful tool for investigation of gene functions and is increasingly used as a therapeutic agent. However, not all siRNAs are equally potent, and although simple rules for the selection of good siRNAs were proposed early on, siRNAs are still plagued with widely fluctuating efficiency. Recently, new design tools incorporating both the structural features of the targeted RNAs and the sequence features of the siRNAs substantially improved the efficacy of siRNAs. In this chapter we will present a review of sequence and structure-based algorithms behind them.

Effects of CT-Xp gene knock down in melanoma cell lines

Cancer/testis (CT) genes are encoded by genes that are normally expressed only in the human germ line but which are activated in various malignancies. CT proteins are frequently immunogenic in cancer patients and their expression is highly restricted to tumors. They are thus important targets for anticancer immunotherapy. In several different tumor types, the expression of CT-X genes is associated with advanced disease and poor outcome, indicating that their expression might contribute to tumorigenesis. CT-X genes encoding members of the MAGE protein family on Xq28 have been shown to potentially influence the tumorigenic phenotype. We used small interfering RNA (siRNA) to investigate whether CT-X mapping to the short arm of the X-chromosome might also have tumorigenic properties and therefore be potentially targeted by functional inhibitors in a therapeutic setting. siRNAs specific to GAGE, SSX and XAGE1 were used in cell proliferation, migration and cell survival assays using cell lines derived from melanoma, a tumor type known to present high frequencies of expression of CT antigens. We found that of these, those specific to GAGE and XAGE1 most significantly impeded melanoma cell migration and invasion and those specific to SSX4 and XAGE1 decreased the clonogenic survival of melanoma cells. Our results suggest that GAGE, XAGE1 and SSX4 might each have a role in tumor progression and are possible therapeutic targets for the treatment of melanoma and other malignancies.

Methods for selecting effective siRNA target sequences using a variety of statistical and analytical techniques

Short interfering RNA (siRNA) has been widely used for studying gene function in mammalian cells but varies markedly in its gene silencing efficacy. Although many design rules/guidelines for effective siRNAs based on various criteria have been reported recently, there are only a few consistencies among them. This makes it difficult to select effective siRNA sequences in mammalian genes. This chapter first reviews the recently reported siRNA design guidelines and then proposes new methods for selecting effective siRNA sequences from many possible candidates by using decision tree learning, Bayes' theorem, and average silencing probability on the basis of a large number of known effective siRNAs. These methods differ from the previous score-based siRNA design techniques and can predict the probability that a candidate siRNA sequence will be effective. Evaluation of these methods by applying them to recently reported effective and ineffective siRNA sequences for a number of genes indicates that they would be useful for many other genes. They should, therefore, be of general utility for selecting effective siRNA sequences for mammalian genes. The chapter also describes another method using a hidden Markov model to select the optimal functional siRNAs and discusses the frequencies of combinations of two successive nucleotides as an important characteristic of effective siRNA sequences.

Design of nuclease-resistant fork-like small interfering RNA (fsiRNA)

Small interfering RNAs (siRNAs) are potent inducers of RNA interference--the conservative cellular process of posttranscriptional gene silencing. The silencing activity of siRNAs depends on the thermodynamic asymmetry of the siRNA duplex. Here, we describe the design of chemically modified fork-like siRNA (fsiRNAs) containing mismatches at the 3'-end region of the sense strand and 2'-O-methyl modifications in nuclease-sensitive sites, capable of silencing of thermodynamically unfavorable targets.

MysiRNA-designer: a workflow for efficient siRNA design

The design of small interfering RNA (siRNA) is a multi factorial problem that has gained the attention of many researchers in the area of therapeutic and functional genomics. MysiRNA score was previously introduced that improves the correlation of siRNA activity prediction considering state of the art algorithms. In this paper, a new program, MysiRNA-Designer, is described which integrates several factors in an automated work-flow considering mRNA transcripts variations, siRNA and mRNA target accessibility, and both near-perfect and partial off-target matches. It also features the MysiRNA score, a highly ranked correlated siRNA efficacy prediction score for ranking the designed siRNAs, in addition to top scoring models Biopredsi, DISR, Thermocomposition21 and i-Score, and integrates them in a unique siRNA score-filtration technique. This multi-score filtration layer filters siRNA that passes the 90% thresholds calculated from experimental dataset features. MysiRNA-Designer takes an accession, finds conserved regions among its transcript space, finds accessible regions within the mRNA, designs all possible siRNAs for these regions, filters them based on multi-scores thresholds, and then performs SNP and off-target filtration. These strict selection criteria were tested against human genes in which at least one active siRNA was designed from 95.7% of total genes. In addition, when tested against an experimental dataset, MysiRNA-Designer was found capable of rejecting 98% of the false positive siRNAs, showing superiority over three state of the art siRNA design programs. MysiRNA is a freely accessible (Microsoft Windows based) desktop application that can be used to design siRNA with a high accuracy and specificity. We believe that MysiRNA-Designer has the potential to play an important role in this area.

Silencing activity of 2'-O-methyl modified anti-MDR1 siRNAs with mismatches in the central part of the duplexes

The thermodynamic properties of siRNA duplexes are important for their silencing activity. siRNAs with high thermodynamic stability of both the central part of the duplex and in the whole, usually display low silencing activity. Destabilization of the central part of the siRNA duplex could increase its silencing activity. However, mismatches located in the central part of the duplex could substantially decrease the amount of RNAi efficacy, hindering active RISC formation and function. In this study, we examined the impact of duplex destabilization by nucleotide substitutions in the central part (7-10 nt counting from the 5'-end of the antisense strand) of the nuclease-resistant siRNA on its silencing activity.

Informatics approach to the rational design of siRNA libraries

This chapter surveys the literature for state-of-the-art methods for the rational design of siRNA libraries. It identifies and presents major milestones in the field of computational modeling of siRNA's gene silencing efficacy. Commonly used features of siRNAs are summarized along with major machine learning techniques employed to build the predictive models. It has also outlined several web-enabled siRNA design tools. To face the challenge of modeling and rational design of chemically modified siRNAs, it also proposes a new cheminformatics approach for the representation and characterization of siRNA molecules. Some preliminary results with this new approach are presented to demonstrate the promising potential of this method for the modeling of siRNA's efficacy. Together with novel delivery technologies and chemical modification techniques, rational siRNA design algorithms will ultimately contribute to chemical biology research and the efficient development of siRNA therapeutics.

2'-O-methyl-modified anti-MDR1 fork-siRNA duplexes exhibiting high nuclease resistance and prolonged silencing activity

The thermodynamic asymmetry of siRNA duplexes determines their silencing activity. Favorable asymmetry can be achieved by incorporation of mismatches into the 3' part of the sense strand, providing fork-siRNAs, which exhibit higher silencing activity and higher sensitivity to nucleases. Recently, we found that selective 2'-O-methyl modifications of the nuclease-sensitive sites of siRNA significantly improve its nuclease resistance without substantial loss of silencing activity. Here, we examined the impact of nucleotide mismatches and the number and location of 2'-O-methyl modifications on the silencing activity and nuclease resistance of anti-MDR1 siRNAs. We found that both nonmodified and selectively modified fork-siRNAs with 4 mismatches at the 3' end of the sense strand suppress the expression of target gene at lower effective concentrations than the parent siRNAs with classical duplex design. The selective modification of nuclease-sensitive sites significantly improved the stability of fork-siRNAs in the presence of serum. The selectively modified fork-siRNA duplexes provided inhibitory effect over a period of 12 days posttransfection, whereas the gene silencing activity of the nonmodified analogs expired within 6 days. Thus, selective chemical modifications and structural alteration of siRNA duplexes improve their silencing properties and significantly prolong the duration of their silencing effect.

Mechanism of microRNA-target interaction: molecular dynamics simulations and thermodynamics analysis

MicroRNAs (miRNAs) are endogenously produced ∼21-nt riboregulators that associate with Argonaute (Ago) proteins to direct mRNA cleavage or repress the translation of complementary RNAs. Capturing the molecular mechanisms of miRNA interacting with its target will not only reinforce the understanding of underlying RNA interference but also fuel the design of more effective small-interfering RNA strands. To address this, in the present work the RNA-bound (Ago-miRNA, Ago-miRNA-target) and RNA-free Ago forms were analyzed by performing both molecular dynamics simulations and thermodynamic analysis. Based on the principal component analysis results of the simulation trajectories as well as the correlation analysis in fluctuations of residues, we discover that: 1) three important (PAZ, Mid and PIWI) domains exist in Argonaute which define the global dynamics of the protein; 2) the interdomain correlated movements are so crucial for the interaction of Ago-RNAs that they not only facilitate the relaxation of the interactions between residues surrounding the RNA binding channel but also induce certain conformational changes; and 3) it is just these conformational changes that expand the cavity of the active site and open putative pathways for both the substrate uptake and product release. In addition, by thermodynamic analysis we also discover that for both the guide RNA 5′-end recognition and the facilitated site-specific cleavage of the target, the presence of two metal ions (of Mg²⁺) plays a predominant role, and this conclusion is consistent with the observed enzyme catalytic cleavage activity in the ternary complex (Ago-miRNA-mRNA). Our results find that it is the set of arginine amino acids concentrated in the nucleotide-binding channel in Ago, instead of the conventionally-deemed seed base-paring, that makes greater contributions in stabilizing the binding of the nucleic acids to Ago.

One of the biggest surprises at the beginning of the ‘post-genome era’ was the discovery of numerous genes encoding microRNAs. The number of microRNA genes is estimated to be nearly 1% of that of protein-coding genes, which were found in genomes of such diverse organisms as Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, and Homo sapiens. Their products, tiny RNAs (miRNAs and siRNAs), are thought to bind to Argonaute (Ago) proteins and form effector complexes to direct mRNA cleavage or repress translation of complementary RNAs, during development, organogenesis, and very likely during many other processes. The cellular interactions between the miRNAs and their target RNAs associating with Ago are only beginning to be revealed, and details of this interaction mechanism at molecular level are still poorly understood. In this article we propose the possible mechanisms of miRNA-target interaction with special emphasis on their structural dynamic and thermodynamic aspects. The results of our model suggest the chemical and physical factors and effects that may be responsible for the miRNA-Ago assembly and miRNA-target recognition.

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

BACKGROUND

Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs.

RESULTS

An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy.

CONCLUSIONS

The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism.

RNA targeting therapeutics: molecular mechanisms of antisense oligonucleotides as a therapeutic platform

Dramatic advances in understanding of the roles RNA plays in normal health and disease have greatly expanded over the past 10 years and have made it clear that scientists are only beginning to comprehend the biology of RNAs. It is likely that RNA will become an increasingly important target for therapeutic intervention; therefore, it is important to develop strategies for therapeutically modulating RNA function. Antisense oligonucleotides are perhaps the most direct therapeutic strategy to approach RNA. Antisense oligonucleotides are designed to bind to the target RNA by well-characterized Watson-Crick base pairing, and once bound to the target RNA, modulate its function through a variety of postbinding events. This review focuses on the molecular mechanisms by which antisense oligonucleotides can be designed to modulate RNA function in mammalian cells and how synthetic oligonucleotides behave in the body.

Small RNA interference-mediated gene silencing of heparanase abolishes the invasion, metastasis and angiogenesis of gastric cancer cells

Background

Heparanase facilitates the invasion and metastasis of cancer cells, and is over-expressed in many kinds of malignancies. Our studies indicated that heparanase was frequently expressed in advanced gastric cancers. The aim of this study is to determine whether silencing of heparanase expression can abolish the malignant characteristics of gastric cancer cells.

Methods

Three heparanase-specific small interfering RNA (siRNAs) were designed, synthesized, and transfected into cultured gastric cancer cell line SGC-7901. Heparanase expression was measured by RT-PCR, real-time quantitative PCR and Western blot. Cell proliferation was detected by MTT colorimetry and colony formation assay. The in vitro invasion and metastasis of cancer cells were measured by cell adhesion assay, scratch assay and matrigel invasion assay. The angiogenesis capabilities of cancer cells were measured by tube formation of endothelial cells.

Results

Transfection of siRNA against 1496-1514 bp of encoding regions resulted in reduced expression of heparanase, which started at 24 hrs and lasted for 120 hrs post-transfection. The siRNA-mediated silencing of heparanase suppressed the cellular proliferation of SGC-7901 cells. In addition, the in vitro invasion and metastasis of cancer cells were attenuated after knock-down of heparanase. Moreover, transfection of heparanase-specific siRNA attenuated the in vitro angiogenesis of cancer cells in a dose-dependent manner.

Conclusions

These results demonstrated that gene silencing of heparanase can efficiently abolish the proliferation, invasion, metastasis and angiogenesis of human gastric cancer cells in vitro, suggesting that heparanase-specific siRNA is of potential values as a novel therapeutic agent for human gastric cancer.

Designing optimal siRNA based on target site accessibility

RNA interference, mediated by small interfering RNAs (siRNAs), is a powerful tool for investigation of gene functions and it is increasingly being used as a therapeutic agent. However, not all siRNAs are equally potent - although simple rules for the selection of good siRNAs were proposed early on, siRNAs are still plagued with widely fluctuating efficiency. Recently, new design tools that incorporate both the structural features of the targeted RNAs and the sequence features of the siRNAs have substantially improved the efficacy of siRNAs. In this chapter, we present the algorithms behind these accessibility-aided tools and show how to design efficient siRNAs with their help.

Uncovering novel gene function in Toll-like receptor signalling using siRNA

In the last number of years siRNA has emerged as a key technique in understanding gene function. While siRNA has been used in lower organisms such as Caenorhabditis elegans, its use in mammalian cells, where gene manipulation is difficult, is where its greatest benefit has been realised. The advancements made in siRNA technology now provide us with an alternative approach to relying on "knockout mice" in uncovering mammalian gene function. In addition, siRNA provides us with a complementary approach to overexpression systems in cultured mammalian cells. siRNA is a superior method of post-transcriptional gene silencing (PTGS) compared to ribozyme and anti-sense technologies both in terms of potency and specificity.

siRecords: a database of mammalian RNAi experiments and efficacies

RNAi-based gene-silencing techniques offer a fast and cost-effective way of knocking down genes’ functions in an easily regulated manner. Exciting progress has been made in recent years in the application of these techniques in basic biomedical research and therapeutic development. However, it remains a difficult task to design effective siRNA experiments with high efficacy and specificity. We present siRecords, an extensive database of mammalian RNAi experiments with consistent efficacy ratings. This database serves two purposes. First, it provides a large and diverse dataset of siRNA experiments. This dataset faithfully represents the general, diverse RNAi experimental practice, and allows more reliable siRNA design tools to be developed with the overfitting problem well curbed. Second, the database helps experimental RNAi researchers directly by providing them with the efficacy and other information about the siRNAs experiments designed and conducted previously against the genes of their interest. The current release of siRecords contains the records of 17 192 RNAi experiments targeting 5086 genes.

Identification of JAK/STAT pathway regulators--insights from RNAi screens

While many core JAK/STAT pathway components have been discovered in Drosophila via classical genetic approaches, the identification of pathway regulators has been more challenging. Recently two cell-based RNAi screens for JAK/STAT pathway regulators have been undertaken using libraries of double-stranded RNAs targeting a large proportion of the predicted Drosophila transcriptome. While both screens identified multiple regulators, only relatively few loci are common to both data sets. Here we compare the two screens and discuss these differences. Although many factors are likely to be contributory, differences in the assay design are of key importance. Low levels of stimulation favouring the identification of negative pathway regulators and high levels of stimulation favouring the identification of positively acting factors. Ultimately, the results from both screens are likely to be largely complementary and have identified a range of novel candidate regulators of JAK/STAT pathway activity as a starting point for new research directions in the future.

Chemical modification resolves the asymmetry of siRNA strand degradation in human blood serum

Small interfering (si)RNAs have recently been used to therapeutically silence genes in vivo after intravenous systemic delivery. Further progress in the development of siRNA therapeutics will in part rely on tailoring site-specific chemical modifications of siRNAs to optimize their pharmacokinetic properties. Advances are particularly needed to improve the nucleolytic stability of these double-stranded RNA drugs in vivo and suppress adverse off-target gene silencing effects. Here we demonstrate that specific chemical 2'-O-methylation, which has already been shown to ameliorate the omnipresent off-target toxicity of siRNAs, selectively protects the particularly vulnerable 5'-end of the guide strand against exonucleolytic degradation in human blood serum. Specific chemical modification thus resolves the asymmetric degradation of the guide and passenger strands, which is inherent to the thermodynamic asymmetry of the siRNA termini as required for proper utilization of the guide strand in RNA interference.