Thermodynamic criteria for high hit rate antisense oligonucleotide design

RNA Secondary Structure Analysis Using RNAstructure

RNAstructure is a user-friendly program for the prediction and analysis of RNA secondary structure. It is available as a web server, a program with a graphical user interface, or a set of command line tools. The programs are available for Microsoft Windows, macOS, or Linux. This article provides protocols for prediction of RNA secondary structure (using the web server, the graphical user interface, or the command line) and high-affinity oligonucleotide binding sites to a structured RNA target (using the graphical user interface). © 2023 Wiley Periodicals LLC. Basic Protocol 1: Predicting RNA secondary structure using the RNAstructure web server Alternate Protocol 1: Predicting secondary structure and base pair probabilities using the RNAstructure graphical user interface Alternate Protocol 2: Predicting secondary structure and base pair probabilities using the RNAstructure command line interface Basic Protocol 2: Predicting binding affinities of oligonucleotides complementary to an RNA target using OligoWalk.

Small Drugs, Huge Impact: The Extraordinary Impact of Antisense Oligonucleotides in Research and Drug Development

Antisense oligonucleotides (ASOs) are an increasingly represented class of drugs. These small sequences of nucleotides are designed to precisely target other oligonucleotides, usually RNA species, and are modified to protect them from degradation by nucleases. Their specificity is due to their sequence, so it is possible to target any RNA sequence that is already known. These molecules are very versatile and adaptable given that their sequence and chemistry can be custom manufactured. Based on the chemistry being used, their activity may significantly change and their effects on cell function and phenotypes can differ dramatically. While some will cause the target RNA to decay, others will only bind to the target and act as a steric blocker. Their incredible versatility is the key to manipulating several aspects of nucleic acid function as well as their process, and alter the transcriptome profile of a specific cell type or tissue. For example, they can be used to modify splicing or mask specific sites on a target. The entire design rather than just the sequence is essential to ensuring the specificity of the ASO to its target. Thus, it is vitally important to ensure that the complete process of drug design and testing is taken into account. ASOs' adaptability is a considerable advantage, and over the past decades has allowed multiple new drugs to be approved. This, in turn, has had a significant and positive impact on patient lives. Given current challenges presented by the COVID-19 pandemic, it is necessary to find new therapeutic strategies that would complement the vaccination efforts being used across the globe. ASOs may be a very powerful tool that can be used to target the virus RNA and provide a therapeutic paradigm. The proof of the efficacy of ASOs as an anti-viral agent is long-standing, yet no molecule currently has FDA approval. The emergence and widespread use of RNA vaccines during this health crisis might provide an ideal opportunity to develop the first anti-viral ASOs on the market. In this review, we describe the story of ASOs, the different characteristics of their chemistry, and how their characteristics translate into research and as a clinical tool.

Identifying Suitable Target Regions and Analyzing Off-Target Effects of Therapeutic Oligonucleotides

Antisense oligonucleotides (AONs) that promote degradation of complementary RNA are being developed as therapeutics. Here, we describe a simple computational workflow for identification of the regions on an RNA that are suitable for targeting with such AONs. The workflow is based on the statistical programming language R, and the calculations and data processing can be carried out on a desktop computer. Our workflow integrates well-established data resources and RNA structure-prediction tools and can be modified easily and expanded as new resources become available.

Stability prediction of canonical and non-canonical structures of nucleic acids in various molecular environments and cells

This review provides the biophysicochemical background and recent advances in stability prediction of canonical and non-canonical structures of nucleic acids in various molecular environments and cells.

Sequence characteristics define trade-offs between on-target and genome-wide off-target hybridization of oligoprobes

Off-target oligoprobe's interaction with partially complementary nucleotide sequences represents a problem for many bio-techniques. The goal of the study was to identify oligoprobe sequence characteristics that control the ratio between on-target and off-target hybridization. To understand the complex interplay between specific and genome-wide off-target (cross-hybridization) signals, we analyzed a database derived from genomic comparison hybridization experiments performed with an Affymetrix tiling array. The database included two types of probes with signals derived from (i) a combination of specific signal and cross-hybridization and (ii) genomic cross-hybridization only. All probes from the database were grouped into bins according to their sequence characteristics, where both hybridization signals were averaged separately. For selection of specific probes, we analyzed the following sequence characteristics: vulnerability to self-folding, nucleotide composition bias, numbers of G nucleotides and GGG-blocks, and occurrence of probe's k-mers in the human genome. Increases in bin ranges for these characteristics are simultaneously accompanied by a decrease in hybridization specificity-the ratio between specific and cross-hybridization signals. However, both averaged hybridization signals exhibit growing trends along with an increase of probes' binding energy, where the hybridization specific signal increases significantly faster in comparison to the cross-hybridization. The same trend is evident for the S function, which serves as a combined evaluation of probe binding energy and occurrence of probe's k-mers in the genome. Application of S allows extracting a larger number of specific probes, as compared to using only binding energy. Thus, we showed that high values of specific and cross-hybridization signals are not mutually exclusive for probes with high values of binding energy and S. In this study, the application of a new set of sequence characteristics allows detection of probes that are highly specific to their targets for array design and other bio-techniques that require selection of specific probes.

Managing the sequence-specificity of antisense oligonucleotides in drug discovery

All drugs perturb the expression of many genes in the cells that are exposed to them. These gene expression changes can be divided into effects resulting from engaging the intended target and effects resulting from engaging unintended targets. For antisense oligonucleotides, developments in bioinformatics algorithms, and the quality of sequence databases, allow oligonucleotide sequences to be analyzed computationally, in terms of the predictability of their interactions with intended and unintended RNA targets. Applying these tools enables selection of sequence-specific oligonucleotides where no- or only few unintended RNA targets are expected. To evaluate oligonucleotide sequence-specificity experimentally, we recommend a transcriptomics protocol where two or more oligonucleotides targeting the same RNA molecule, but with entirely different sequences, are evaluated together. This helps to clarify which changes in cellular RNA levels result from downstream processes of engaging the intended target, and which are likely to be related to engaging unintended targets. As required for all classes of drugs, the toxic potential of oligonucleotides must be evaluated in cell- and animal models before clinical testing. Since potential adverse effects related to unintended targeting are sequence-dependent and therefore species-specific, in vitro toxicology assays in human cells are especially relevant in oligonucleotide drug discovery.

Deformability Calculation for Estimation of the Relative Stability of Chemically Modified RNA Duplexes

Chemical modification of RNA duplexes alters their stability. We have attempted to develop a computational approach to estimate the thermal stability of chemically modified duplexes. These studies revealed that the deformability of chemically modified RNA duplexes, calculated from molecular dynamics simulations, could be used as a good indicator for estimating the effect of chemical modification on duplex thermal stability. This unit describes how deformability calculation can be applied to estimate the relative stability of chemically modified RNA duplexes. © 2017 by John Wiley & Sons, Inc.

Antisense locked nucleic acids targeting agrA inhibit quorum sensing and pathogenesis of community-associated methicillin-resistant Staphylococcus aureus

AIM

Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) is commonly associated with nonnosocomial skin and soft tissue infections due to its virulence, which is mainly controlled by the accessory gene regulator (agr) quorum sensing (QS) system. In this study (KFF)₃ K peptide-conjugated locked nucleic acids (PLNAs) targeting agrA mRNA were developed to inhibit agr activity and arrest the pathogenicity of CA-MRSA.

METHODS AND RESULTS

Two PLNAs were designed, and synthesized, after predicting the secondary structure of agrA mRNA. The influence on bacterial growth was tested using a growth curve assay. RT-qPCR, haemolysis assay, lactate dehydrogenase release assay and chemotaxis assay were used to evaluate the effects of the PLNAs on inhibiting agr QS. A mouse skin infection model was employed to test the protective effect of the PLNAs in vivo. None of the PLNAs were found to be bacteriostatic or bactericidal in vitro. However, one PLNA, PLNA34, showed strong ability to suppress expression of agrA and the effector molecule RNAIII in USA300 LAC strain. Furthermore, PLNA34 inhibited the expression of virulence genes that are upregulated by agr, including hla, psmα, psmβ and pvl. The haemolytic activity of the supernatants from PLNA34-treated bacteria was also dramatically reduced, as well as the capacity to lyse and recruit neutrophils. Moreover, PLNA34 showed high levels of protection in the CA-MRSA mouse skin infection model.

CONCLUSIONS

The anti-agrA PLNA34 can effectively inhibit the agr QS and suppress CA-MRSA pathogenicity.

SIGNIFICANCE AND IMPACT OF THE STUDY

agrA is a promising target for the development of antisense oligonucleotides to block agr QS.

Oligonucleotide therapeutics: chemistry, delivery and clinical progress

Oligonucleotide therapeutics have the potential to become a third pillar of drug development after small molecules and protein therapeutics. However, the three approved oligonucleotide drugs over the past 17 years have not proven to be highly successful in a commercial sense. These trailblazer drugs have nonetheless laid the foundations for entire classes of drug candidates to follow. This review will examine further advances in chemistry that are earlier in the pipeline of oligonucleotide drug candidates. Finally, we consider the possible effect of delivery systems that may provide extra footholds to improve the potency and specificity of oligonucleotide drugs. Our overview focuses on strategies to imbue antisense oligonucleotides with more drug-like properties and their applicability to other nucleic acid therapeutics.

The 5'-tail of antisense RNAII of pMV158 plays a critical role in binding to the target mRNA and in translation inhibition of repB

Rolling-circle replication of streptococcal plasmid pMV158 is controlled by the concerted action of two trans-acting elements, namely transcriptional repressor CopG and antisense RNAII, which inhibit expression of the repB gene encoding the replication initiator protein. The pMV158-encoded antisense RNAII exerts its activity of replication control by inhibiting translation of the essential repB gene. RNAII is the smallest and simplest among the characterized antisense RNAs involved in control of plasmid replication. Structure analysis of RNAII revealed that it folds into an 8-bp-long stem containing a 1-nt bulge and closed by a 6-nt apical loop. This hairpin is flanked by a 17-nt-long single-stranded 5′-tail and an 8-nt-long 3′-terminal U-rich stretch. Here, the 3′ and 5′ regions of the 5′-tail of RNAII are shown to play a critical role in the binding to the target mRNA and in the inhibition of repB translation, respectively. In contrast, the apical loop of the single hairpin of RNAII plays a rather secondary role and the upper stem region hardly contributes to the binding or inhibition processes. The entire 5′-tail is required for efficient inhibition of repB translation, though only the 8-nt-long region adjacent to the hairpin seems to be essential for rapid binding to the mRNA. These results show that a “kissing” interaction involving base-pairing between complementary hairpin loops in RNAII and mRNA is not critical for efficient RNA/RNA binding or repB translation inhibition. A singular binding mechanism is envisaged whereby initial pairing between complementary single-stranded regions in the antisense and sense RNAs progresses upwards into the corresponding hairpin stems to form the intermolecular duplex.

Silencing efficacy prediction: a retrospective study on target mRNA features

Post-transcriptional gene silencing is a widely used method to suppress gene expression. Unfortunately only a portion of siRNAs do successfully reduce gene expression. Target mRNA secondary structures and siRNA-mRNA thermodynamic features are believed to contribute to the silencing activity. However, there is still an open discussion as to what determines siRNA efficacy. In this retrospective study, we analysed the target accessibility comparing very high (VH) compared with low (L) efficacy siRNA sequences obtained from the siRecords Database. We determined the contribution of mRNA target local secondary structures on silencing efficacy. Both the univariable and the multivariable logistic regression evidenced no relationship between siRNA efficacy and mRNA target secondary structures. Moreover, none of the thermodynamic and sequence-base parameters taken into consideration (H-b index, ΔG°_overall, ΔG°_duplex, ΔG°_break-target and GC%) was associated with siRNA efficacy. We found that features believed to be predictive of silencing efficacy are not confirmed to be so when externally evaluated in a large heterogeneous sample. Although it was proposed that silencing efficacy could be influenced by local target accessibility we show that this could be not generalizable because of the diversity of experimental setting that may not be representative of biological systems especially in view of the many local protein factors, usually not taken into consideration, which could hamper the silencing process.

We analysed several siRNA-mRNA target features involved in silencing efficacy. We found out that features believed to be predictive of silencing efficacy are not such when transferred to a larger dataset of experiments and different experimental settings.

Reversion of antibiotic resistance by inhibiting mecA in clinical methicillin-resistant Staphylococci by antisense phosphorothioate oligonucleotide

Methicillin-resistant Staphylococci (MRS), methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant Staphylococcus epidermidis (MRSE) have become a challenging problem in nosocomial infections and are connected with high morbidity and mortality rates. This is due to the increasing incidence of resistance to virtually all β-lactams and a wide variety of antimicrobials. The spread of MRS severely limits therapeutic options and generates the need for novel antibiotics that are able to combat MRS infections. One method of inhibiting bacterial growth is by blocking the expression of conserved bacterial genes and provides potential new avenues for generating a new generation of antimicrobials. The mecA gene is highly conserved among Staphylococcal species, and this makes it an ideal target for antisense inhibition. We had identified a target sequence (854-871 nt) within the mecA mRNA coding region that is particularly sensitive to antisense inhibition. The anti-mecA PS-ODN04 oligonucleotide was encapsulated into an anionic liposome. MRSA01 and MRSE01 clinical strains treated with this antisense sequence became susceptible to existing β-lactam antibiotics, and their growth was inhibited by oxacillin in vitro and in vivo. PS-ODN04 reduced the bacterial titers in the blood of mice infected with MRSA01 and MRSE01 and significantly improved their survival rate. Our data offer a possible new strategy for treating MRS infections.

RNAstructure: Web servers for RNA secondary structure prediction and analysis

RNAstructure is a software package for RNA secondary structure prediction and analysis. This contribution describes a new set of web servers to provide its functionality. The web server offers RNA secondary structure prediction, including free energy minimization, maximum expected accuracy structure prediction and pseudoknot prediction. Bimolecular secondary structure prediction is also provided. Additionally, the server can predict secondary structures conserved in either two homologs or more than two homologs. Folding free energy changes can be predicted for a given RNA structure using nearest neighbor rules. Secondary structures can be compared using circular plots or the scoring methods, sensitivity and positive predictive value. Additionally, structure drawings can be rendered as SVG, postscript, jpeg or pdf. The web server is freely available for public use at: http://rna.urmc.rochester.edu/RNAstructureWeb.

Optimized models for design of efficient miR30-based shRNAs

Small hairpin RNAs (shRNAs) became an important research tool in cell biology. Reliable design of these molecules is essential for the needs of large functional genomics projects. To optimize the design of efficient shRNAs, we performed comparative, thermodynamic, and correlation analyses of ~18,000 miR30-based shRNAs with known functional efficiencies, derived from the Sensor Assay project (Fellmann et al., 2011). We identified features of the shRNA guide strand that significantly correlate with the silencing efficiency and performed multiple regression analysis, using 4/5 of the data for training purposes and 1/5 for cross validation. A model that included the position-dependent nucleotide preferences was predictive in the cross-validation data subset (R = 0.39). However, a model, which in addition to the nucleotide preferences included thermodynamic shRNA features such as a thermodynamic duplex stability and position-dependent thermodynamic profile (dinucleotide free energy) was performing better (R = 0.53). Software "miR_Scan" was developed based upon the optimized models. Calculated mRNA target secondary structure stability showed correlation with shRNA silencing efficiency but failed to improve the model. Correlation analysis demonstrates that our algorithm for identification of efficient miR30-based shRNA molecules performs better than approaches that were developed for design of chemically synthesized siRNAs (R(max) = 0.36).

Prediction of the stability of modified RNA duplexes based on deformability analysis: oligoribonucleotide derivatives modified with 2'-O-cyanoethyl-5-propynyl-2-thiouridine as a promising component

We describe a method to predict the stability of a modified RNA duplex. Ten unique modified RNA duplexes showed a linear relationship between the calculated and experimentally determined duplex stabilities.

Variables and strategies in development of therapeutic post-transcriptional gene silencing agents

Post-transcriptional gene silencing (PTGS) agents such as ribozymes, RNAi and antisense have substantial potential for gene therapy of human retinal degenerations. These technologies are used to knockdown a specific target RNA and its cognate protein. The disease target mRNA may be a mutant mRNA causing an autosomal dominant retinal degeneration or a normal mRNA that is overexpressed in certain diseases. All PTGS technologies depend upon the initial critical annealing event of the PTGS ligand to the target RNA. This event requires that the PTGS agent is in a conformational state able to support hybridization and that the target have a large and accessible single-stranded platform to allow rapid annealing, although such platforms are rare. We address the biocomplexity that currently limits PTGS therapeutic development with particular emphasis on biophysical variables that influence cellular performance. We address the different strategies that can be used for development of PTGS agents intended for therapeutic translation. These issues apply generally to the development of PTGS agents for retinal, ocular, or systemic diseases. This review should assist the interested reader to rapidly appreciate critical variables in PTGS development and facilitate initial design and testing of such agents against new targets of clinical interest.

Co-blockade of mecR1/blaR1 signal pathway to restore antibiotic susceptibility in clinical isolates of methicillin-resistant Staphylococcus aureus

INTRODUCTION

Methicillin-resistant Staphylococcus aureus (MRSA) is caused by the production of low-affinity penicillin-binding protein 2a and β-lactamases, which are encoded by mecA and blaZ, respectively. Expressions of the two key genes are mutually regulated by MecI and BlaI. The aim of this study was to design specific anti-mecR1 and anti-blaR1 deoxyribozymes and identify the restoration of susceptibility in MRSA isolates with mecI or blaI or no deletions by interfering with the mutual regulation of mecA and blaZ.

MATERIAL AND METHODS

Specific deoxyribozymes were designed by using the program RNA structure 4.6. RNA substrates were obtained by transcription in vitro and used to assess the target cleavage of DNAzymes. Transcription of mecR1-mecA and blaR1-blaZ was analysed by real time RT-PCR. The susceptibility of MRSA was tested.

RESULTS

Specific deoxyribozymes showed efficient catalytic activity to each own substrate mecR1 or blaR1 in vitro and caused the reduction of mecR1 and blaR1 transcription in vivo. Furthermore, simultaneous administration of two DNAzymes to knockdown mecR1 and blaR1 resulted in increased susceptibility of all MRSA strains tested in this study.

CONCLUSIONS

These results demonstrated that combined use of the two specific phosphorothioate deoxyribozymes could be a viable and promising strategy to restore the susceptibility of almost all MRSA clinical isolates.

Correcting for heat capacity and 5'-TA type terminal nearest neighbors improves prediction of DNA melting temperatures using nearest-neighbor thermodynamic models

Nearest-neighbor thermodynamic (NNT) models currently provide some of the most accurate predictions of melting thermodynamics, including melting temperature (T(m)) values, for short DNA duplexes. Inherent to all existing NNT models is the assumption that ΔH° and ΔS° for the helix-to-coil transition are temperature invariant. Here we investigate the impact that this zero-ΔC(p) assumption has on the accuracy of T(m) predictions for 128 DNA duplexes. Previous and new melting thermodynamic data are analyzed to establish an estimate of ΔC(p)(bp), the heat capacity change per base pair, of 42 ± 16 cal mol(-1) K(-1) bp(-1), as well as an optimal thermodynamic reference temperature (T(ref)) of 53 ± 5 °C. These results were used to modify the unified NNT model to properly account for the temperature dependence of ΔH° and ΔS° and thereby extend the range over which T(m) is accurately predicted. This new approach is shown to be especially useful for duplexes that melt at a T(m) greater than 70 °C. Thermodynamic data collected by differential scanning calorimetry (DSC) for 16 duplexes designed to melt over a broad temperature range were used to verify the values of ΔC(p)(bp) and T(ref) and to show that ΔC(p)(bp) is essentially constant above 37 °C. Additional DSC analysis of 12 duplex sequences containing all 10 nearest neighbors allowed for errors associated with different terminal nearest neighbors to be examined and showed that duplexes containing one or more terminal 5'-TA groups are significantly more stable than predicted by the unified NNT model. A correction to improve prediction of the hybridization thermodynamics of duplexes with terminal 5'-TA groups is provided.

Comparisons between chemical mapping and binding to isoenergetic oligonucleotide microarrays reveal unexpected patterns of binding to the Bacillus subtilis RNase P RNA specificity domain

Microarrays with isoenergetic pentamer and hexamer 2'-O-methyl oligonucleotide probes with LNA (locked nucleic acid) and 2,6-diaminopurine substitutions were used to probe the binding sites on the RNase P RNA specificity domain of Bacillus subtilis. Unexpected binding patterns were revealed. Because of their enhanced binding free energies, isoenergetic probes can break short duplexes, merge adjacent loops, and/or induce refolding. This suggests new approaches to the rational design of short oligonucleotide therapeutics but limits the utility of microarrays for providing constraints for RNA structure determination. The microarray results are compared to results from chemical mapping experiments, which do provide constraints. Results from both types of experiments indicate that the RNase P RNA folds similarly in 1 M Na(+) and 10 mM Mg(2+).

Antisense DNA parameters derived from next-nearest-neighbor analysis of experimental data

BACKGROUND

The enumeration of tetrameric and other sequence motifs that are positively or negatively correlated with in vivo antisense DNA effects has been a useful addition to the arsenal of information needed to predict effective targets for antisense DNA control of gene expression. Such retrospective information derived from in vivo cellular experiments characterizes aspects of the sequence dependence of antisense inhibition that are not predicted by nearest-neighbor (NN) thermodynamic parameters derived from in vitro experiments. However, quantitation of the antisense contributions of motifs is problematic, since individual motifs are not isolated from the effects of neighboring nucleotides, and motifs may be overlapping. These problems are circumvented by a next-nearest-neighbor (NNN) analysis of antisense DNA effects in which the overlapping nature of nearest-neighbors is taken into account.

RESULTS

Next-nearest-neighbor triplet combinations of nucleotides are the simplest that include overlapping sequence effects and therefore can encompass interactions beyond those of nearest neighbors. We used singular value decomposition (SVD) to fit experimental data from our laboratory in which phosphorothioate-modified antisense DNAs (S-DNAs) 20 nucleotides long were used to inhibit cellular protein expression in 112 experiments involving four gene targets and two cell lines. Data were fitted using a NNN model, neglecting end effects, to derive NNN inhibition parameters that could be combined to give parameters for a set of 49 sequences that represents the inhibitory effects of all possible overlapping triplet interactions in the cellular targets of these antisense S-DNAs. We also show that parameters to describe subsets of the data, such as the mRNAs being targeted and the cell lines used, can be included in such a derivation. While NNN triplet parameters provided an adequate model to fit our data, NN doublet parameters did not.

CONCLUSIONS

The methodology presented illustrates how NNN antisense inhibitory information can be derived from in vivo cellular experiments. Subsequent calculations of the antisense inhibitory parameters for any mRNA target sequence automatically take into account the effects of all possible overlapping combinations of nearest-neighbors in the sequence. This procedure is more robust than the tallying of tetrameric motifs that have positive or negative antisense effects. The specific parameters derived in this work are limited in their applicability by the relatively small database of experiments that was used in their derivation.

RNAstructure: software for RNA secondary structure prediction and analysis

Background

To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence.

Results

RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained.

Conclusion

The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

Using OligoWalk to identify efficient siRNA sequences

RNA interference (RNAi) has emerged as an important tool in science and in medicine. Small-interfering RNAs (siRNAs) can be used to knockdown gene expression of specific mRNAs. In practice, a number of factors influence whether an siRNA sequence will elicit RNAi and knockdown target gene expression. One factor that significantly influences the efficiency of an siRNA is the effect of RNA secondary structure. Self-structure in either the siRNA sequence or the target mRNA at the binding site may prevent gene silencing. This chapter provides protocols for using the OligoWalk software package to design efficient siRNAs. OligoWalk considers the effect of target and guide strand self-structures and also local sequence features in siRNA design. OligoWalk can be run either locally by compiling the software or through a convenient web interface. OligoWalk is freely available at http://rna.urmc.rochester.edu/cgi-bin/server_exe/oligowalk/oligowalk_form.cgi .

Prediction of antisense oligonucleotide efficacy using aggregate motifs

Antisense oligonucleotide technology allows the targeted reduction of mRNA expression through the in vitro application of short (approximately 20 nt) DNA molecules. Oligonucleotides are valuable both in the study of gene regulation and for having potential therapeutic effects. In theory, a base sequence complementary to a region of the transcript would hybridize to its mRNA target. Nevertheless, in practice some complementary antisense oligonucleotides are more active and more potent than others in suppressing specific gene expression. We present a novel computational approach to modeling oligonucleotide efficacy that uses aggregate motifs, which are flexible tetramotifs that expand the predictive ability of the data descriptors and the attribute space. We also demonstrate our findings on the largest dataset yet reported in the literature. It was shown that the prediction accuracy was significantly enhanced, offering more than eightfold improvement compared to the traditional methods.

Efficient suppression of tissue factor synthesis using antisense oligonucleotides selected by an enhanced strategy for evaluation of structural characteristics

Selection of optimal antisense constructs is still a problem. Among a huge number of antisense oligonucleotides (AS-ONs) only a small piece show inhibitory efficacy. We want to develop an enhanced strategy for specific selection of effective AS-ONs based on prediction of secondary structure of the target messenger RNA (mRNA) and analysis of thermodynamic properties of the mRNA/AS-ON hybrid. Numerous AS-ONs targeted on human tissue factor (TF) mRNA were investigated to evaluate the relevance of different thermodynamic and structural properties on inhibitory efficacy. Cell viability, TF protein and TF mRNA were determined after transfection of bladder cancer cell line J82. Inhibitory efficacy was related to GC content, target region within the TF mRNA and stability of the mRNA/AS-ON hybrid or affinity of the AS-ON to the target mRNA. We found effective AS-ONs targeted on translated region or 3'-untranslated region of TF RNA. We also detected a great correlation between inhibitory efficacy and GC content as well as stability of the mRNA/AS-ON hybrid.

RNA secondary structure prediction

Details for predicting secondary structure of RNA sequences using free energy minimization are given. Protocols present the use of the RNAstructure computer program (for PCs) and the mfold server (for Unix platforms). The minimum free energy structure and a set of suboptimal structures with similar free energies are predicted. Prediction of high-affinity oligonucleotide binding sites to a structured RNA target is also presented.

RNA secondary structure analysis using RNAstructure

RNAstructure is a user-friendly program for the prediction and analysis of RNA secondary structure under Microsoft Windows. This unit provides protocols for RNA secondary structure prediction and prediction of high-affinity oligonucleotide binding sites to a structured RNA target.

Fundamental differences in the equilibrium considerations for siRNA and antisense oligodeoxynucleotide design

Both siRNA and antisense oligodeoxynucleotides (ODNs) inhibit the expression of a complementary gene. In this study, fundamental differences in the considerations for RNA interference and antisense ODNs are reported. In siRNA and antisense ODN databases, positive correlations are observed between the cost to open the mRNA target self-structure and the stability of the duplex to be formed, meaning the sites along the mRNA target with highest potential to form strong duplexes with antisense strands also have the greatest tendency to be involved in pre-existing structure. Efficient siRNA have less stable siRNA-target duplex stability than inefficient siRNA, but the opposite is true for antisense ODNs. It is, therefore, more difficult to avoid target self-structure in antisense ODN design. Self-structure stabilities of oligonucleotide and target correlate to the silencing efficacy of siRNA. Oligonucleotide self-structure correlations to efficacy of antisense ODNs, conversely, are insignificant. Furthermore, self-structure in the target appears to correlate with antisense ODN efficacy, but such that more effective antisense ODNs appear to target mRNA regions with greater self-structure. Therefore, different criteria are suggested for the design of efficient siRNA and antisense ODNs and the design of antisense ODNs is more challenging.

Antisense oligonucleotides: from design to therapeutic application

1. An antisense oligonucleotide (ASO) is a short strand of deoxyribonucleotide analogue that hybridizes with the complementary mRNA in a sequence-specific manner via Watson-Crick base pairing. Formation of the ASO-mRNA heteroduplex either triggers RNase H activity, leading to mRNA degradation, induces translational arrest by steric hindrance of ribosomal activity, interferes with mRNA maturation by inhibiting splicing or destabilizes pre-mRNA in the nucleus, resulting in downregulation of target protein expression. 2. The ASO is not only a useful experimental tool in protein target identification and validation, but also a highly selective therapeutic strategy for diseases with dysregulated protein expression. 3. In the present review, we discuss various theoretical approaches to rational design of ASO, chemical modifications of ASO, ASO delivery systems and ASO-related toxicology. Finally, we survey ASO drugs in various current clinical studies.

Identification of sequence motifs significantly associated with antisense activity

Background

Predicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids. To create an effective predictive model, it is important to know what properties of an oligonucleotide sequence associate significantly with antisense activity. Also, for the model to be efficient we must know what properties do not associate significantly and can be omitted from the model. This paper will discuss the results of a randomization procedure to find motifs that associate significantly with either high or low antisense suppression activity, analysis of their properties, as well as the results of support vector machine modelling using these significant motifs as features.

Results

We discovered 155 motifs that associate significantly with high antisense suppression activity and 202 motifs that associate significantly with low suppression activity. The motifs range in length from 2 to 5 bases, contain several motifs that have been previously discovered as associating highly with antisense activity, and have thermodynamic properties consistent with previous work associating thermodynamic properties of sequences with their antisense activity. Statistical analysis revealed no correlation between a motif's position within an antisense sequence and that sequences antisense activity. Also, many significant motifs existed as subwords of other significant motifs. Support vector regression experiments indicated that the feature set of significant motifs increased correlation compared to all possible motifs as well as several subsets of the significant motifs.

Conclusion

The thermodynamic properties of the significantly associated motifs support existing data correlating the thermodynamic properties of the antisense oligonucleotide with antisense efficiency, reinforcing our hypothesis that antisense suppression is strongly associated with probe/target thermodynamics, as there are no enzymatic mediators to speed the process along like the RNA Induced Silencing Complex (RISC) in RNAi. The independence of motif position and antisense activity also allows us to bypass consideration of this feature in the modelling process, promoting model efficiency and reducing the chance of overfitting when predicting antisense activity. The increase in SVR correlation with significant features compared to nearest-neighbour features indicates that thermodynamics alone is likely not the only factor in determining antisense efficiency.

Gab2 antisense oligonucleotide blocks rat basophilic leukemic cell functions

Adapter molecule Grb2-associated binder-like protein 2 (Gab2) plays a critical role in FcepsilonRI-induced mast cell degranulation and activation. The present study aimed to investigate the pharmacological effects of an antisense oligonucleotide (ASO) targeted at Gab2 on the immune responses of rat basophilic leukemic (RBL)-2H3 cells. Gab2 ASOs were rationally designed and transfected into RBL-2H3 cells. Gab2 mRNA and protein knockdown was confirmed by real-time RT-PCR and immunoblotting, respectively. Effects of Gab2 ASO on FcepsilonRI-induced release of histamine and beta-hexosaminidase was measured by EIA and an enzymatic assay, respectively; signaling events by immunoblotting; and cytokine mRNA expression by RT-PCR. Effects of Gab2 ASO on cell adhesion and migration were performed on fibronectin-coated 96-well plate and transwells cell culture chambers, respectively. We have characterized a phosphorothioate-modified ASO targeted at Gab2 mRNA that was able to knockdown Gab2 mRNA and protein in RBL-2H3 cells. Gab2 ASO significantly blocked IgE-mediated mast cell release of beta-hexosaminidase and histamine; phosphorylation of Akt, p38 mitogen-activated protein kinase and PKCdelta; and up-regulation of cytokine mRNA levels (e.g. IL-4, -6, -9 and -13, and TNF-alpha). In addition, Gab2 ASO markedly prevented mast cell adhesion to fibronectin-coated plates and restrained random migration of RBL-2H3 cells in cell culture chambers. Our findings show that Gab2 knockdown in RBL-2H3 cells by ASO strategy can suppress many aspects of the mast cell functions and, therefore, a selective Gab2 ASO may have therapeutic potential for mast cell-dependent allergic disorders.

Rational design and rapid screening of antisense oligonucleotides for prokaryotic gene modulation

Antisense oligodeoxynucleotides (oligos) are widely used for functional studies of both prokaryotic and eukaryotic genes. However, the identification of effective target sites is a major issue in antisense applications. Here, we study a number of thermodynamic and structural parameters that may affect the potency of antisense inhibition. We develop a cell-free assay for rapid oligo screening. This assay is used for measuring the expression of Escherichia coli lacZ, the antisense target for experimental testing and validation. Based on a training set of 18 oligos, we found that structural accessibility predicted by local folding of the target mRNA is the most important predictor for antisense activity. This finding was further confirmed by a direct validation study. In this study, a set of 10 oligos was designed to target accessible sites, and another set of 10 oligos was selected to target inaccessible sites. Seven of the 10 oligos for accessible sites were found to be effective (>50% inhibition), but none of the oligos for inaccessible sites was effective. The difference in the antisense activity between the two sets of oligos was statistically significant. We also found that the predictability of antisense activity by target accessibility was greatly improved for oligos targeted to the regions upstream of the end of the active domain for β-galactosidase, the protein encoded by lacZ. The combination of the structure-based antisense design and extension of the lacZ assay to include gene fusions will be applicable to high-throughput gene functional screening, and to the identification of new drug targets in pathogenic microbes. Design tools are available through the Sfold Web server at .

The orphan receptor GPR17 identified as a new dual uracil nucleotides/cysteinyl-leukotrienes receptor

Nucleotides and cysteinyl-leukotrienes (CysLTs) are unrelated signaling molecules inducing multiple effects through separate G-protein-coupled receptors: the P2Y and the CysLT receptors. Here we show that GPR17, a Gi-coupled orphan receptor at intermediate phylogenetic position between P2Y and CysLT receptors, is specifically activated by both families of endogenous ligands, leading to both adenylyl cyclase inhibition and intracellular calcium increases. Agonist-response profile, as determined by [(35)S]GTPgammaS binding, was different from that of already known CysLT and P2Y receptors, with EC(50) values in the nanomolar and micromolar range, for CysLTs and uracil nucleotides, respectively. Both rat and human receptors are highly expressed in the organs typically undergoing ischemic damage, that is, brain, heart and kidney. In vivo inhibition of GPR17 by either CysLT/P2Y receptor antagonists or antisense technology dramatically reduced ischemic damage in a rat focal ischemia model, suggesting GPR17 as the common molecular target mediating brain damage by nucleotides and CysLTs. In conclusion, the deorphanization of GPR17 revealed a dualistic receptor for two endogenous unrelated ligand families. These findings may lead to dualistic drugs of previously unexplored therapeutic potential.

Nearest neighbor parameters for Watson-Crick complementary heteroduplexes formed between 2'-O-methyl RNA and RNA oligonucleotides

Results from optical melting studies of Watson-Crick complementary heteroduplexes formed between 2'-O-methyl RNA and RNA oligonucleotides are used to determine nearest neighbor thermodynamic parameters for predicting the stabilities of such duplexes. The results are consistent with the physical model assumed by the individual nearest neighbor-hydrogen bonding model, which contains terms for helix initiation, base pair stacking and base pair composition. The sequence dependence is similar to that for Watson-Crick complementary RNA/RNA duplexes, which suggests that the sequence dependence may also be similar to that for other backbones that favor A-form RNA conformations.

AtRTPrimer: database for Arabidopsis genome-wide homogeneous and specific RT-PCR primer-pairs

BACKGROUND

Primer design is a critical step in all types of RT-PCR methods to ensure specificity and efficiency of a target amplicon. However, most traditional primer design programs suggest primers on a single template of limited genetic complexity. To provide researchers with a sufficient number of pre-designed specific RT-PCR primer pairs for whole genes in Arabidopsis, we aimed to construct a genome-wide primer-pair database.

DESCRIPTION

We considered the homogeneous physical and chemical properties of each primer (homogeneity) of a gene, non-specific binding against all other known genes (specificity), and other possible amplicons from its corresponding genomic DNA or similar cDNAs (additional information). Then, we evaluated the reliability of our database with selected primer pairs from 15 genes using conventional and real time RT-PCR.

CONCLUSION

Approximately 97% of 28,952 genes investigated were finally registered in AtRTPrimer. Unlike other freely available primer databases for Arabidopsis thaliana, AtRTPrimer provides a large number of reliable primer pairs for each gene so that researchers can perform various types of RT-PCR experiments for their specific needs. Furthermore, by experimentally evaluating our database, we made sure that our database provides good starting primer pairs for Arabidopsis researchers to perform various types of RT-PCR experiments.

Selection of antisense oligonucleotides based on multiple predicted target mRNA structures

Background

Local structures of target mRNAs play a significant role in determining the efficacies of antisense oligonucleotides (ODNs), but some structure-based target site selection methods are limited by uncertainties in RNA secondary structure prediction. If all the predicted structures of a given mRNA within a certain energy limit could be used simultaneously, target site selection would obviously be improved in both reliability and efficiency. In this study, some key problems in ODN target selection on the basis of multiple predicted target mRNA structures are systematically discussed.

Results

Two methods were considered for merging topologically different RNA structures into integrated representations. Several parameters were derived to characterize local target site structures. Statistical analysis on a dataset with 448 ODNs against 28 different mRNAs revealed 9 features quantitatively associated with efficacy. Features of structural consistency seemed to be more highly correlated with efficacy than indices of the proportion of bases in single-stranded or double-stranded regions. The local structures of the target site 5' and 3' termini were also shown to be important in target selection. Neural network efficacy predictors using these features, defined on integrated structures as inputs, performed well in "minus-one-gene" cross-validation experiments.

Conclusion

Topologically different target mRNA structures can be merged into integrated representations and then used in computer-aided ODN design. The results of this paper imply that some features characterizing multiple predicted target site structures can be used to predict ODN efficacy.

AOBase: a database for antisense oligonucleotides selection and design

Antisense oligonucleotides (ODNs) technology is one of the important approaches for the sequence-specific knockdown of gene expression. ODNs have been used as research tools in the post-genome era, as well as new types of therapeutic agents. Since finding effective target sites within RNA is a hard work for antisense ODNs design, various experimental methods and computational approaches have been proposed. For better sharing of the experimented and published ODNs, valid and invalid ODNs reported in literatures are screened, collected and stored in AOBase. Till now, ∼700 ODNs against 46 target mRNAs are contained in AOBase. Entries can be explored via TargetSearch and AOSearch web retrieval interfaces. AOBase can not only be useful in ODNs selection for gene function exploration, but also contribute to mining rules and developing algorithms for rational ODNs design. AOBase is freely accessible via .

Computational models with thermodynamic and composition features improve siRNA design

Background

Small interfering RNAs (siRNAs) have become an important tool in cell and molecular biology. Reliable design of siRNA molecules is essential for the needs of large functional genomics projects.

Results

To improve the design of efficient siRNA molecules, we performed a comparative, thermodynamic and correlation analysis on a heterogeneous set of 653 siRNAs collected from the literature. We used this training set to select siRNA features and optimize computational models. We identified 18 parameters that correlate significantly with silencing efficiency. Some of these parameters characterize only the siRNA sequence, while others involve the whole mRNA. Most importantly, we derived an siRNA position-dependent consensus, and optimized the free-energy difference of the 5' and 3' terminal dinucleotides of the siRNA antisense strand. The position-dependent consensus is based on correlation and t-test analyses of the training set, and accounts for both significantly preferred and avoided nucleotides in all sequence positions. On the training set, the two parameters' correlation with silencing efficiency was 0.5 and 0.36, respectively. Among other features, a dinucleotide content index and the frequency of potential targets for siRNA in the mRNA added predictive power to our model (R = 0.55). We showed that our model is effective for predicting the efficiency of siRNAs at different concentrations.

We optimized a neural network model on our training set using three parameters characterizing the siRNA sequence, and predicted efficiencies for the test siRNA dataset recently published by Novartis. On this validation set, the correlation coefficient between predicted and observed efficiency was 0.75. Using the same model, we performed a transcriptome-wide analysis of optimal siRNA targets for 22,600 human mRNAs.

Conclusion

We demonstrated that the properties of the siRNAs themselves are essential for efficient RNA interference. The 5' ends of antisense strands of efficient siRNAs are U-rich and possess a content similarity to the pyrimidine-rich oligonucleotides interacting with the polypurine RNA tracks that are recognized by RNase H. The advantage of our method over similar methods is the small number of parameters. As a result, our method requires a much smaller training set to produce consistent results. Other mRNA features, though expensive to compute, can slightly improve our model.

Towards high-throughput functional target discovery in angiogenesis research

Angiogenesis is a hallmark of malignancies and other proliferative diseases, and inhibition of this process is considered to be a promising treatment strategy. Classical gene-expression analyses performed during the past decade have generated vast lists of genes associated with disease but have so far yielded only limited novel therapeutic targets for clinical applications. Recently, the focus has shifted from target identification, based on gene-expression analysis, to identification of genes, based on the function of the encoded protein. Disease-target genes can now be identified in a high-throughput fashion based on functional properties that are directly related to the disease phenotype. This new approach significantly shortens the time span for the development of therapeutic applications from the laboratory bench to the hospital bedside.

A potent inhibitor of prothrombin gene expression as a result of standardized target site selection and design of antisense oligonucleotides

The development of antisense oligonucleotides (AS-ODN) always had the limitation that because of complex mRNA secondary structures, not every designed AS-ODN inhibited the expression of its target. There have been many investigations to overcome this problem in the last few years. This produced a great deal of theoretical and empirical findings about characteristics of effective AS-ODNs in respect to their target regions but no standardized selection procedure of AS-ODN target regions within a given mRNA or standardized design of AS-ODNs against a specific target region. We present here a standardized method based on secondary structure prediction for target site selection and AS-ODN design, followed by validation of the antisense effect caused by our predicted AS-ODNs in cell culture. The combination of theoretical design and experimental selection procedure led to an AS-ODN that efficiently and specifically reduces prothrombin mRNA and antigen.

Technical improvements in the computational target search for antisense oligonucleotides

A number of theoretical and experimental approaches to design biologically active antisense oligonucleotides (AS-ON) have proven their usefulness. This includes systematic computational strategies that are based on the understanding of antisense mechanisms. Here, we investigate in detail the relationship between computational parameters of the local target search for the theoretical design of AS-ON and the hit rate, that is, the biologic efficacy of AS-ON in cell culture. The computational design of AS-ON studied in this work is based on an established algorithm to predict structurally favorable local target sites along a given target RNA against which AS-ON are directed. Briefly, a sequence segment of a certain length (window) is used to predict a group of lowest-energy RNA secondary structures. Subsequently, this window is shifted along the target sequence by a certain step width. To date, those technical parameters of the systematic structural target analysis have been chosen arbitrarily. Here, we investigate their role for the successful design of AS-ON and suggest an optimized computer-based protocol for the selection of favorable local target sequences and, hence, an improved design of active AS-ON. Further, this study provides systematic insights into the structure- function relationship of AS-ON.

The influence of locked nucleic acid residues on the thermodynamic properties of 2'-O-methyl RNA/RNA heteroduplexes

The influence of locked nucleic acid (LNA) residues on the thermodynamic properties of 2'-O-methyl RNA/RNA heteroduplexes is reported. Optical melting studies indicate that LNA incorporated into an otherwise 2'-O-methyl RNA oligonucleotide usually, but not always, enhances the stabilities of complementary duplexes formed with RNA. Several trends are apparent, including: (i) a 3' terminal U LNA and 5' terminal LNAs are less stabilizing than interior and other 3' terminal LNAs; (ii) most of the stability enhancement is achieved when LNA nucleotides are separated by at least one 2'-O-methyl nucleotide; and (iii) the effects of LNA substitutions are approximately additive when the LNA nucleotides are separated by at least one 2'-O-methyl nucleotide. An equation is proposed to approximate the stabilities of complementary duplexes formed with RNA when at least one 2'-O-methyl nucleotide separates LNA nucleotides. The sequence dependence of 2'-O-methyl RNA/RNA duplexes appears to be similar to that of RNA/RNA duplexes, and preliminary nearest-neighbor free energy increments at 37 degrees C are presented for 2'-O-methyl RNA/RNA duplexes. Internal mismatches with LNA nucleotides significantly destabilize duplexes with RNA.

Potential of DNA microarrays for developing parallel detection tools (PDTs) for microorganisms relevant to biodefense and related research needs

Development of parallel detection tools using microarrays is critically reviewed in view of the need for screening multiple microorganisms in a single test. Potential research needs with respect to probe design and specificity, validation, sample concentration, selective target enrichment and amplification, and data analysis are discussed. Data illustrating selected probe design issues for detecting multiple targets in mixed microbial systems is presented. Challenges with respect to cost, time, and ease of use compared to other methods are also summarized.

Treatments for choroidal and retinal neovascularization: a focus on oligonucleotide therapy and delivery for the regulation of gene function

Blinding eye diseases caused by neovascularization of the retinal tissue are the leading cause of blindness in Western societies. Current treatments, such as laser photocoagulation, are limited in their effectiveness at halting the progression of angiogenesis and are unable to reduce the number of vessels once they have developed. In addition, although complete blindness is often avoided, vision is often permanently impaired by the treatment itself. Several less invasive treatments are being developed and one of these is oligonucleotide gene therapy in which short stretches of nucleotides are being used as inhibitors of key, metabolic processes involved in angiogenesis. Combined with this is the development of new and improved nucleotide chemistries aimed at overcoming many of the problems associated with oligonucleotide gene therapy, such as poor longevity because of endonuclease activity. In addition, advancements in delivery systems have further enhanced the efficacy of oligonucleotide gene therapy by increasing cellular penetration and localizing delivery to specific cell types and organs.

Mechanistic insights aid computational short interfering RNA design

RNA interference is widely recognized for its utility as a functional genomics tool. In the absence of reliable target site selection tools, however, the impact of RNA interference (RNAi) may be diminished. The primary determinants of silencing are influenced by highly coordinated RNA-protein interactions that occur throughout the RNAi process, including short interfering RNA (siRNA) binding and unwinding followed by target recognition, cleavage, and subsequent product release. Recently developed strategies for identification of functional siRNAs reveal that thermodynamic and siRNA sequence-specific properties are crucial to predict functional duplexes (Khvorova et al., 2003; Reynolds et al., 2004; Schwarz et al., 2003). Additional assessments of siRNA specificity reveal that more sophisticated sequence comparison tools are also required to minimize potential off-target effects (Jackson et al., 2003; Semizarov et al., 2003). This chapter reviews the biological basis for current computational design tools and how best to utilize and assess their predictive capabilities for selecting functional and specific siRNAs.

Secondary structure prediction of interacting RNA molecules

Computational tools for prediction of the secondary structure of two or more interacting nucleic acid molecules are useful for understanding mechanisms for ribozyme function, determining the affinity of an oligonucleotide primer to its target, and designing good antisense oligonucleotides, novel ribozymes, DNA code words, or nanostructures. Here, we introduce new algorithms for prediction of the minimum free energy pseudoknot-free secondary structure of two or more nucleic acid molecules, and for prediction of alternative low-energy (sub-optimal) secondary structures for two nucleic acid molecules. We provide a comprehensive analysis of our predictions against secondary structures of interacting RNA molecules drawn from the literature. Analysis of our tools on 17 sequences of up to 200 nucleotides that do not form pseudoknots shows that they have 79% accuracy, on average, for the minimum free energy predictions. When the best of 100 sub-optimal foldings is taken, the average accuracy increases to 91%. The accuracy decreases as the sequences increase in length and as the number of pseudoknots and tertiary interactions increases. Our algorithms extend the free energy minimization algorithm of Zuker and Stiegler for secondary structure prediction, and the sub-optimal folding algorithm by Wuchty et al. Implementations of our algorithms are freely available in the package MultiRNAFold.

Profiled support vector machines for antisense oligonucleotide efficacy prediction

BACKGROUND

This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1) feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE), and (2) AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to different parts of the training data to focus the training on the most important regions.

RESULTS

In the first stage, the SVM-RFE technique was most efficient and robust in the presence of low number of samples and high input space dimension. This method yielded an optimal subset of 14 representative features, which were all related to energy and sequence motifs. The second stage evaluated the performance of the predictors (overall correlation coefficient between observed and predicted efficacy, r; mean error, ME; and root-mean-square-error, RMSE) using 8-fold and minus-one-RNA cross-validation methods. The profiled SVM produced the best results (r = 0.44, ME = 0.022, and RMSE= 0.278) and predicted high (>75% inhibition of gene expression) and low efficacy (<25%) AOs with a success rate of 83.3% and 82.9%, respectively, which is better than by previous approaches. A web server for AO prediction is available online at http://aosvm.cgb.ki.se/.

CONCLUSIONS

The SVM approach is well suited to the AO prediction problem, and yields a prediction accuracy superior to previous methods. The profiled SVM was found to perform better than the standard SVM, suggesting that it could lead to improvements in other prediction problems as well.

Sfold web server for statistical folding and rational design of nucleic acids

The Sfold web server provides user-friendly access to Sfold, a recently developed nucleic acid folding software package, via the World Wide Web (WWW). The software is based on a new statistical sampling paradigm for the prediction of RNA secondary structure. One of the main objectives of this software is to offer computational tools for the rational design of RNA-targeting nucleic acids, which include small interfering RNAs (siRNAs), antisense oligonucleotides and trans-cleaving ribozymes for gene knock-down studies. The methodology for siRNA design is based on a combination of RNA target accessibility prediction, siRNA duplex thermodynamic properties and empirical design rules. Our approach to target accessibility evaluation is an original extension of the underlying RNA folding algorithm to account for the likely existence of a population of structures for the target mRNA. In addition to the application modules Sirna, Soligo and Sribo for siRNAs, antisense oligos and ribozymes, respectively, the module Srna offers comprehensive features for statistical representation of sampled structures. Detailed output in both graphical and text formats is available for all modules. The Sfold server is available at http://sfold.wadsworth.org and http://www.bioinfo.rpi.edu/applications/sfold.