Prediction of antisense oligonucleotide binding affinity to a structured RNA target

Walton, S. Patrick; Stephanopoulos, Gregory; Yarmush, Martin L.; Roth, Charles M.

doi:10.1002/(sici)1097-0290(19991005)65:1<1::aid-bit1>3.0.co;2-f

Cited by 39 publications

(35 citation statements)

References 26 publications

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“…Another possibility is that the energy values used in RNA folding calculations, obtained from in vitro experiments, were systematically overestimated. In fact, in a few studies in which the results of RNA folding calculations can be compared directly to in vivo activities studied (46)(47)(48), a systematic two-to threefold overestimation of RNA binding energies has been reported. This may account for the discrepancies we observed, because the differences in the slopes of the dotted and solid lines in Figs.…”

Section: Discussionmentioning

confidence: 82%

Quantifying the sequence–function relation in gene silencing by bacterial small RNAs

Hao

Zhang²,

Erickson³

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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Sequence-function relations for small RNA (sRNA)-mediated gene silencing were quantified for the sRNA RyhB and some of its mRNA targets in Escherichia coli. Numerous mutants of RyhB and its targets were generated and their in vivo functions characterized at various levels of target and RyhB expression. Although a core complementary region is required for repression by RyhB, variations in the complementary sequences of the core region gave rise to a continuum of repression strengths, correlated exponentially with the computed free energy of RyhB-target duplex formation. Moreover, sequence variations in the linker region known to interact with the RNA chaperone Hfq also gave rise to a continuum of repression strengths, correlated exponentially with the computed energy cost of keeping the linker region open. These results support the applicability of the thermodynamic model in predicting sRNA-mRNA interaction and suggest that sequences at these locations may be used to fine-tune the degree of repression. Surprisingly, a truncated RyhB without the Hfq-binding region is found to repress multiple targets of the wild-type RyhB effectively, both in the presence and absence of Hfq, even though the former is required for the activity of wild-type RyhB itself. These findings challenge the commonly accepted model concerning the function of Hfq in gene silencing-both in providing stability to the sRNAs and in catalyzing the target mRNAs to take on active conformationsand raise the intriguing question of why many endogenous sRNAs subject their functions to Hfq-dependences.gene regulation | noncoding RNA | posttranscriptional control | quantitative biology | RNA interaction A significant development in gene regulation in the past decade is a growing appreciation of the complex roles that small regulatory RNA (sRNA) can play in coordinating gene activities in both prokaryotes and eukaryotes (1-3). In Escherichia coli, approximately 80 sRNA genes have been identified (3). There exists by now a basic understanding of the molecular components and mechanisms involved, at least for a major class of bacterial sRNA that acts in trans through base pairing (4-15). Recent theoretical and experimental studies have further revealed unique functional features of sRNA-mediated gene regulation (9,(16)(17)(18)(19)(20): because of the stoichiometric mode of target inactivation, sRNAmediated regulation exhibits an abrupt and sensitive response to input signals while being robust to stochastic fluctuations.How is this mode of regulation encoded in the molecular sequences of the sRNA and its targets? In the case of transcriptional regulation, a great deal is known quantitatively about the interaction between a DNA binding sequence (operator) and its cognate transcription factor (TF) and the regulatory consequences of this interaction: similarity of the operator to its "consensus sequence" determines its binding affinity to the cognate TF (21-24), and the latter in turn affects the rate of transcriptional initiation (25). Such knowledge, obtained b...

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Section: Discussionmentioning

confidence: 82%

Quantifying the sequence–function relation in gene silencing by bacterial small RNAs

Hao

Zhang²,

Erickson³

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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“…For example, a thermodynamic cycle equivalent to our calculation of DG bind predicted antisense oligonucleotides with high binding affinity for rabbit b-globin and mouse tumor necrosis factor-a mRNAs, achieving 60% accuracy and a significant correlation with experimental data (Walton et al 1999). Analogous calculations included the concentration-dependent effects of oligonucleotide dimerization, predicting oligonucleotide-target affinities consistent with results from an RNase-H mapping assay on the AT 1 receptor mRNA and from a trans-tagging assay on sickle b-globin mRNA (Mathews et al 1999).…”

Section: Discussionmentioning

confidence: 99%

“…One recurring theme is the use of RNA secondary structure prediction algorithms to calculate the free energy changes, DG bind , associated with binding an oligonucleotide to each possible target site on the mRNA substrate. Target sites with strongly negative values of DG bind are then predicted to be the most accessible sites on the substrate (Mathews et al 1999;Walton et al 1999;Busch et al 2008;Lu and Mathews 2008;Tafer et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Computational prediction of efficient splice sites for trans-splicing ribozymes

Meluzzi¹,

Olson²,

Dolan³

et al. 2012

RNA

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Group I introns have been engineered into trans-splicing ribozymes capable of replacing the 39-terminal portion of an external mRNA with their own 39-exon. Although this design makes trans-splicing ribozymes potentially useful for therapeutic application, their trans-splicing efficiency is usually too low for medical use. One factor that strongly influences trans-splicing efficiency is the position of the target splice site on the mRNA substrate. Viable splice sites are currently determined using a biochemical trans-tagging assay. Here, we propose a rapid and inexpensive alternative approach to identify efficient splice sites. This approach involves the computation of the binding free energies between ribozyme and mRNA substrate. We found that the computed binding free energies correlate well with the trans-splicing efficiency experimentally determined at 18 different splice sites on the mRNA of chloramphenicol acetyl transferase. In contrast, our results from the trans-tagging assay correlate less well with measured trans-splicing efficiency. The computed free energy components suggest that splice site efficiency depends on the following secondary structure rearrangements: hybridization of the ribozyme's internal guide sequence (IGS) with mRNA substrate (most important), unfolding of substrate proximal to the splice site, and release of the IGS from the 39-exon (least important). The proposed computational approach can also be extended to fulfill additional design requirements of efficient trans-splicing ribozymes, such as the optimization of 39-exon and extended guide sequences.

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“…Mechanistically, an oligonucleotide hybridizes with a target strand (forms antiparallel base-paired duplex), thereby affecting its natural folding and interaction with cognate partners or recruiting intracellular machinery that cleaves the RNA (Bennett and Swayze, 2010). Such interaction, however, depends on the thermodynamic and kinetic barrier of unfolding the native conformation of both the target RNA and the antisense oligonucleotide (Freier et al, 1986; Mir and Southern, 1999; Walton et al, 1999), which can be prohibitively high (Li et al, 2008). Although there are RNA-binding proteins that facilitate RNA unfolding, the antisense-based strategy is still mostly applicable to non-structured or weakly structured RNAs.…”

Section: Brief Overview Of Rna Structurementioning

confidence: 99%

RNA Structures as Mediators of Neurological Diseases and as Drug Targets

Bernat

Disney

2015

Neuron

115

107

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RNAs adopt diverse folded structures that are essential for function and thus play critical roles in cellular biology. A striking example of this is the ribosome, a complex, three-dimensionally folded macromolecular machine that orchestrates protein synthesis. Advances in RNA biochemistry, structural and molecular biology, and bioinformatics have revealed other non-coding RNAs whose functions are dictated by their structure. It is not surprising that aberrantly folded RNA structures contribute to disease. In this review, we provide a brief introduction into RNA structural biology and then describe how RNA structures function in cells and cause or contribute to neurological disease. Finally, we highlight successful applications of rational design principles to provide chemical probes and lead compounds targeting structured RNAs. Based on several examples of well-characterized RNA-driven neurological disorders, we demonstrate how designed small molecules can facilitate study of RNA dysfunction, elucidating previously unknown roles for RNA in disease, and provide lead therapeutics.

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Prediction of antisense oligonucleotide binding affinity to a structured RNA target

Cited by 39 publications

References 26 publications

Quantifying the sequence–function relation in gene silencing by bacterial small RNAs

Quantifying the sequence–function relation in gene silencing by bacterial small RNAs

Computational prediction of efficient splice sites for trans-splicing ribozymes

RNA Structures as Mediators of Neurological Diseases and as Drug Targets

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