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Wlodzimierz Bielecki - One of the best experts on this subject based on the ideXlab platform.
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Tiling Nussinov’s RNA Folding loop nest with a space-time approach
BMC Bioinformatics, 2019Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:Background An RNA primary structure, or sequence, is a single strand considered as a chain of nucleotides from the alphabet AUGC (adenine, uracil, guanine, cytosine). The strand can be folded onto itself, i.e., one segment of an RNA sequence might be paired with another segment of the same RNA sequence into a two-dimensional structure composed by a list of complementary base pairs, which are close together with the minimum energy. That list is called RNA’s secondary structure and is predicted by an RNA Folding algorithm. RNA secondary structure prediction is a computing-intensive task that lies at the core of search applications in bioinformatics. Results We suggest a space-time tiling approach and apply it to generate parallel cache effective tiled code for RNA Folding using Nussinov’s algorithm. Conclusions Parallel tiled code generated with a suggested space-time loop tiling approach outperforms known related codes generated automatically by means of optimizing compilers and codes produced manually. The presented approach enables us to tile all the three loops of Nussinov’s recurrence that is not possible with commonly known tiling techniques. Generated parallel tiled code is scalable regarding to the number of parallel threads – increasing the number of threads reduces code execution time. Defining speed up as the ratio of the time taken to run the original serial program on one thread to the time taken to run the tiled program on P threads, we achieve super-linear speed up (a value of speed up is greater than the number of threads used) for parallel tiled code against the original serial code up to 32 threads and super-linear speed up scalability (increasing speed up with increasing the thread number) up to 8 threads. For one thread used, speed up is about 4.2 achieved on an Intel Xeon machine used for carrying out experiments.
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tiling nussinov s RNA Folding loop nest with a space time approach
BMC Bioinformatics, 2019Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:An RNA primary structure, or sequence, is a single strand considered as a chain of nucleotides from the alphabet AUGC (adenine, uracil, guanine, cytosine). The strand can be folded onto itself, i.e., one segment of an RNA sequence might be paired with another segment of the same RNA sequence into a two-dimensional structure composed by a list of complementary base pairs, which are close together with the minimum energy. That list is called RNA’s secondary structure and is predicted by an RNA Folding algorithm. RNA secondary structure prediction is a computing-intensive task that lies at the core of search applications in bioinformatics. We suggest a space-time tiling approach and apply it to generate parallel cache effective tiled code for RNA Folding using Nussinov’s algorithm. Parallel tiled code generated with a suggested space-time loop tiling approach outperforms known related codes generated automatically by means of optimizing compilers and codes produced manually. The presented approach enables us to tile all the three loops of Nussinov’s recurrence that is not possible with commonly known tiling techniques. Generated parallel tiled code is scalable regarding to the number of parallel threads – increasing the number of threads reduces code execution time. Defining speed up as the ratio of the time taken to run the original serial program on one thread to the time taken to run the tiled program on P threads, we achieve super-linear speed up (a value of speed up is greater than the number of threads used) for parallel tiled code against the original serial code up to 32 threads and super-linear speed up scalability (increasing speed up with increasing the thread number) up to 8 threads. For one thread used, speed up is about 4.2 achieved on an Intel Xeon machine used for carrying out experiments.
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Tuning iteration space slicing based tiled multi-core code implementing Nussinov's RNA Folding.
BMC Bioinformatics, 2018Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:RNA Folding is an ongoing compute-intensive task of bioinformatics. Parallelization and improving code locality for this kind of algorithms is one of the most relevant areas in computational biology. Fortunately, RNA secondary structure approaches, such as Nussinov’s recurrence, involve mathematical operations over affine control loops whose iteration space can be represented by the polyhedral model. This allows us to apply powerful polyhedral compilation techniques based on the transitive closure of dependence graphs to generate parallel tiled code implementing Nussinov’s RNA Folding. Such techniques are within the iteration space slicing framework – the transitive dependences are applied to the statement instances of interest to produce valid tiles. The main problem at generating parallel tiled code is defining a proper tile size and tile dimension which impact parallelism degree and code locality. To choose the best tile size and tile dimension, we first construct parallel parametric tiled code (parameters are variables defining tile size). With this purpose, we first generate two nonparametric tiled codes with different fixed tile sizes but with the same code structure and then derive a general affine model, which describes all integer factors available in expressions of those codes. Using this model and known integer factors present in the mentioned expressions (they define the left-hand side of the model), we find unknown integers in this model for each integer factor available in the same fixed tiled code position and replace in this code expressions, including integer factors, with those including parameters. Then we use this parallel parametric tiled code to implement the well-known tile size selection (TSS) technique, which allows us to discover in a given search space the best tile size and tile dimension maximizing target code performance. For a given search space, the presented approach allows us to choose the best tile size and tile dimension in parallel tiled code implementing Nussinov’s RNA Folding. Experimental results, received on modern Intel multi-core processors, demonstrate that this code outperforms known closely related implementations when the length of RNA strands is bigger than 2500.
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a practical approach to tiling zuker s RNA Folding using the transitive closure of loop dependence graphs
International Conference on Information Systems, 2017Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:RNA secondary structure prediction is a computationally-intensive task that lies at the core of search applications in bioinformatics. In this paper, we consider Zuker’s RNA Folding algorithm, which is challenging to optimize because it is resource intensive and has a large number of non-uniform dependences. We describe the application of a previously published approach, proposed by us, to automatic tiling Zuker’s RNA Folding loop nest using the exact polyhedral representation of dependences exposed for this nest. First, rectangular tiles are formed within the iteration space of Zuker’s loop nest. Then tiles are corrected to honor all dependences, exposed for the original loop nest, by means of applying the exact transitive closure of a dependence graph. We implemented our approach as a part of the source-to-source TRACO compiler. The experimental results present the significant speed-up factor of tiled code on a single core of a modern processor. Related work and future algorithm improvements are discussed.
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Parallel tiled Nussinov RNA Folding loop nest generated using both dependence graph transitive closure and loop skewing
BMC Bioinformatics, 2017Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:Background RNA secondary structure prediction is a compute intensive task that lies at the core of several search algorithms in bioinformatics. Fortunately, the RNA Folding approaches, such as the Nussinov base pair maximization, involve mathematical operations over affine control loops whose iteration space can be represented by the polyhedral model. Polyhedral compilation techniques have proven to be a powerful tool for optimization of dense array codes. However, classical affine loop nest transformations used with these techniques do not optimize effectively codes of dynamic programming of RNA structure predictions. Results The purpose of this paper is to present a novel approach allowing for generation of a parallel tiled Nussinov RNA loop nest exposing significantly higher performance than that of known related code. This effect is achieved due to improving code locality and calculation parallelization. In order to improve code locality, we apply our previously published technique of automatic loop nest tiling to all the three loops of the Nussinov loop nest. This approach first forms original rectangular 3D tiles and then corrects them to establish their validity by means of applying the transitive closure of a dependence graph. To produce parallel code, we apply the loop skewing technique to a tiled Nussinov loop nest. Conclusions The technique is implemented as a part of the publicly available polyhedral source-to-source TRACO compiler. Generated code was run on modern Intel multi-core processors and coprocessors. We present the speed-up factor of generated Nussinov RNA parallel code and demonstrate that it is considerably faster than related codes in which only the two outer loops of the Nussinov loop nest are tiled.
Marek Palkowski - One of the best experts on this subject based on the ideXlab platform.
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Tiling Nussinov’s RNA Folding loop nest with a space-time approach
BMC Bioinformatics, 2019Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:Background An RNA primary structure, or sequence, is a single strand considered as a chain of nucleotides from the alphabet AUGC (adenine, uracil, guanine, cytosine). The strand can be folded onto itself, i.e., one segment of an RNA sequence might be paired with another segment of the same RNA sequence into a two-dimensional structure composed by a list of complementary base pairs, which are close together with the minimum energy. That list is called RNA’s secondary structure and is predicted by an RNA Folding algorithm. RNA secondary structure prediction is a computing-intensive task that lies at the core of search applications in bioinformatics. Results We suggest a space-time tiling approach and apply it to generate parallel cache effective tiled code for RNA Folding using Nussinov’s algorithm. Conclusions Parallel tiled code generated with a suggested space-time loop tiling approach outperforms known related codes generated automatically by means of optimizing compilers and codes produced manually. The presented approach enables us to tile all the three loops of Nussinov’s recurrence that is not possible with commonly known tiling techniques. Generated parallel tiled code is scalable regarding to the number of parallel threads – increasing the number of threads reduces code execution time. Defining speed up as the ratio of the time taken to run the original serial program on one thread to the time taken to run the tiled program on P threads, we achieve super-linear speed up (a value of speed up is greater than the number of threads used) for parallel tiled code against the original serial code up to 32 threads and super-linear speed up scalability (increasing speed up with increasing the thread number) up to 8 threads. For one thread used, speed up is about 4.2 achieved on an Intel Xeon machine used for carrying out experiments.
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tiling nussinov s RNA Folding loop nest with a space time approach
BMC Bioinformatics, 2019Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:An RNA primary structure, or sequence, is a single strand considered as a chain of nucleotides from the alphabet AUGC (adenine, uracil, guanine, cytosine). The strand can be folded onto itself, i.e., one segment of an RNA sequence might be paired with another segment of the same RNA sequence into a two-dimensional structure composed by a list of complementary base pairs, which are close together with the minimum energy. That list is called RNA’s secondary structure and is predicted by an RNA Folding algorithm. RNA secondary structure prediction is a computing-intensive task that lies at the core of search applications in bioinformatics. We suggest a space-time tiling approach and apply it to generate parallel cache effective tiled code for RNA Folding using Nussinov’s algorithm. Parallel tiled code generated with a suggested space-time loop tiling approach outperforms known related codes generated automatically by means of optimizing compilers and codes produced manually. The presented approach enables us to tile all the three loops of Nussinov’s recurrence that is not possible with commonly known tiling techniques. Generated parallel tiled code is scalable regarding to the number of parallel threads – increasing the number of threads reduces code execution time. Defining speed up as the ratio of the time taken to run the original serial program on one thread to the time taken to run the tiled program on P threads, we achieve super-linear speed up (a value of speed up is greater than the number of threads used) for parallel tiled code against the original serial code up to 32 threads and super-linear speed up scalability (increasing speed up with increasing the thread number) up to 8 threads. For one thread used, speed up is about 4.2 achieved on an Intel Xeon machine used for carrying out experiments.
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Tuning iteration space slicing based tiled multi-core code implementing Nussinov's RNA Folding.
BMC Bioinformatics, 2018Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:RNA Folding is an ongoing compute-intensive task of bioinformatics. Parallelization and improving code locality for this kind of algorithms is one of the most relevant areas in computational biology. Fortunately, RNA secondary structure approaches, such as Nussinov’s recurrence, involve mathematical operations over affine control loops whose iteration space can be represented by the polyhedral model. This allows us to apply powerful polyhedral compilation techniques based on the transitive closure of dependence graphs to generate parallel tiled code implementing Nussinov’s RNA Folding. Such techniques are within the iteration space slicing framework – the transitive dependences are applied to the statement instances of interest to produce valid tiles. The main problem at generating parallel tiled code is defining a proper tile size and tile dimension which impact parallelism degree and code locality. To choose the best tile size and tile dimension, we first construct parallel parametric tiled code (parameters are variables defining tile size). With this purpose, we first generate two nonparametric tiled codes with different fixed tile sizes but with the same code structure and then derive a general affine model, which describes all integer factors available in expressions of those codes. Using this model and known integer factors present in the mentioned expressions (they define the left-hand side of the model), we find unknown integers in this model for each integer factor available in the same fixed tiled code position and replace in this code expressions, including integer factors, with those including parameters. Then we use this parallel parametric tiled code to implement the well-known tile size selection (TSS) technique, which allows us to discover in a given search space the best tile size and tile dimension maximizing target code performance. For a given search space, the presented approach allows us to choose the best tile size and tile dimension in parallel tiled code implementing Nussinov’s RNA Folding. Experimental results, received on modern Intel multi-core processors, demonstrate that this code outperforms known closely related implementations when the length of RNA strands is bigger than 2500.
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a practical approach to tiling zuker s RNA Folding using the transitive closure of loop dependence graphs
International Conference on Information Systems, 2017Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:RNA secondary structure prediction is a computationally-intensive task that lies at the core of search applications in bioinformatics. In this paper, we consider Zuker’s RNA Folding algorithm, which is challenging to optimize because it is resource intensive and has a large number of non-uniform dependences. We describe the application of a previously published approach, proposed by us, to automatic tiling Zuker’s RNA Folding loop nest using the exact polyhedral representation of dependences exposed for this nest. First, rectangular tiles are formed within the iteration space of Zuker’s loop nest. Then tiles are corrected to honor all dependences, exposed for the original loop nest, by means of applying the exact transitive closure of a dependence graph. We implemented our approach as a part of the source-to-source TRACO compiler. The experimental results present the significant speed-up factor of tiled code on a single core of a modern processor. Related work and future algorithm improvements are discussed.
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Parallel tiled Nussinov RNA Folding loop nest generated using both dependence graph transitive closure and loop skewing
BMC Bioinformatics, 2017Co-Authors: Marek Palkowski, Wlodzimierz BieleckiAbstract:Background RNA secondary structure prediction is a compute intensive task that lies at the core of several search algorithms in bioinformatics. Fortunately, the RNA Folding approaches, such as the Nussinov base pair maximization, involve mathematical operations over affine control loops whose iteration space can be represented by the polyhedral model. Polyhedral compilation techniques have proven to be a powerful tool for optimization of dense array codes. However, classical affine loop nest transformations used with these techniques do not optimize effectively codes of dynamic programming of RNA structure predictions. Results The purpose of this paper is to present a novel approach allowing for generation of a parallel tiled Nussinov RNA loop nest exposing significantly higher performance than that of known related code. This effect is achieved due to improving code locality and calculation parallelization. In order to improve code locality, we apply our previously published technique of automatic loop nest tiling to all the three loops of the Nussinov loop nest. This approach first forms original rectangular 3D tiles and then corrects them to establish their validity by means of applying the transitive closure of a dependence graph. To produce parallel code, we apply the loop skewing technique to a tiled Nussinov loop nest. Conclusions The technique is implemented as a part of the publicly available polyhedral source-to-source TRACO compiler. Generated code was run on modern Intel multi-core processors and coprocessors. We present the speed-up factor of generated Nussinov RNA parallel code and demonstrate that it is considerably faster than related codes in which only the two outer loops of the Nussinov loop nest are tiled.
Xiaowei Zhuang - One of the best experts on this subject based on the ideXlab platform.
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stepwise protein mediated RNA Folding directs assembly of telomerase ribonucleoprotein
Nature, 2007Co-Authors: Michael D Stone, Xiaowei Zhuang, Mariana Mihalusova, Catherine M Oconnor, Ramadevi Prathapam, Kathleen CollinsAbstract:The biogenesis of telomerase, the ribonucleoprotein (RNP) assembly that stabilizes the termini of linear chromosomes, is an important process in a healthy cell and mutations that disrupt it cause disease. Mechanisms of RNP assembly are poorly understood. Michael Stone et al. have used a single-molecule approach to examine telomerase assembly in real time. The results establish an assembly mechanism featuring successive steps of protein-induced RNA Folding, ultimately moulding the telomerase complex into its functional shape. Telomerase is an essential cellular ribonucleoprotein (RNP) that solves the end replication problem and maintains chromosome stability by adding telomeric DNA to the termini of linear chromosomes1,2,3. Genetic mutations that abrogate the normal assembly of telomerase RNP cause human disease4. It is therefore of fundamental and medical importance to decipher cellular strategies for telomerase biogenesis, which will require new insights into how specific interactions occur in a precise order along the RNP assembly pathway. Here we use a single-molecule approach to dissect the individual assembly steps of telomerase. Direct observation of complex formation in real time revealed two sequential steps of protein-induced RNA Folding, establishing a hierarchical RNP assembly mechanism: interaction with the telomerase holoenzyme protein p65 induces structural rearrangement of telomerase RNA, which in turn directs the binding of the telomerase reverse transcriptase to form the functional teRNAry complex. This hierarchical assembly process is facilitated by an evolutionarily conserved structural motif within the RNA. These results identify the RNA Folding pathway during telomerase biogenesis and define the mechanism of action for an essential telomerase holoenzyme protein.
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single molecule RNA Folding
Accounts of Chemical Research, 2005Co-Authors: Gregory Bokinsky, Xiaowei ZhuangAbstract:Single-molecule experiments significantly expand our capability to characterize complex dynamics of biological processes. This relatively new approach has contributed significantly to our understanding of the RNA Folding problem. Recent single-molecule experiments, together with structural and biochemical characterizations of RNA at the ensemble level, show that RNA molecules typically fold across a highly rugged energy landscape. As a result, long-lived Folding intermediates, multiple Folding pathways, and heterogeneous conformational dynamics are commonly found for RNA enzymes. While initial results have suggested that stable secondary structures are partly responsible for the rugged energy landscape of RNA, a complete mechanistic understanding of the complex Folding behavior has not yet been obtained. A combination of single-molecule experiments, which are well suited to analyze transient and heterogeneous dynamic behaviors, with ensemble characterizations that can provide structural information at a s...
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single molecule transition state analysis of RNA Folding
Proceedings of the National Academy of Sciences of the United States of America, 2003Co-Authors: Gregory Bokinsky, Vinod K Misra, David Rueda, Maria M Rhodes, Andrew Gordus, Hazen P Babcock, Nils G Walter, Xiaowei ZhuangAbstract:How RNA molecules fold into functional structures is a problem of great significance given the expanding list of essential cellular RNA enzymes and the increasing number of applications of RNA in biotechnology and medicine. A critical step toward solving the RNA Folding problem is the characterization of the associated transition states. This is a challenging task in part because the rugged energy landscape of RNA often leads to the coexistence of multiple distinct structural transitions. Here, we exploit single-molecule fluorescence spectroscopy to follow in real time the equilibrium transitions between conformational states of a model RNA enzyme, the hairpin ribozyme. We clearly distinguish structural transitions between effectively noninterchanging sets of unfolded and folded states and characterize key factors defining the transition state of an elementary Folding reaction where the hairpin ribozyme's two helical domains dock to make several tertiary contacts. Our single-molecule experiments in conjunction with site-specific mutations and metal ion titrations show that the two RNA domains are in a contact or close-to-contact configuration in the transition state even though the native tertiary contacts are at most partially formed. Such a compact transition state without well formed tertiary contacts may be a general property of elementary RNA Folding reactions.
Daniel Herschlag - One of the best experts on this subject based on the ideXlab platform.
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the story of RNA Folding as told in epochs
Cold Spring Harbor Perspectives in Biology, 2018Co-Authors: Daniel Herschlag, Steve Bonilla, Namita BisariaAbstract:The past decades have witnessed tremendous developments in our understanding of RNA biology. At the core of these advances have been studies aimed at discerning RNA structure and at understanding the forces that influence the RNA Folding process. It is easy to take the present state of understanding for granted, but there is much to be learned by considering the path to our current understanding, which has been tortuous, with the birth and death of models, the adaptation of experimental tools originally developed for characterization of protein structure and catalysis, and the development of novel tools for probing RNA. In this review we tour the stages of RNA Folding studies, considering them as "epochs" that can be generalized across scientific disciplines. These epochs span from the discovery of catalytic RNA, through biophysical insights into the putative primordial RNA World, to characterization of structured RNAs, the building and testing of models, and, finally, to the development of models with the potential to yield generalizable predictive and quantitative models for RNA conformational, thermodynamic, and kinetic behavior. We hope that this accounting will aid others as they navigate the many fascinating questions about RNA and its roles in biology, in the past, present, and future.
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hidden structural modules in a cooperative RNA Folding transition
Cell Reports, 2018Co-Authors: Brant Gracia, Namita Bisaria, Daniel Herschlag, Hashim M Alhashimi, Rhiju Das, Rick RussellAbstract:Large-scale, cooperative rearrangements underlie the functions of RNA in RNA-protein machines and gene regulation. To understand how such rearrangements are orchestrated, we used high-throughput chemical footprinting to dissect a seemingly concerted rearrangement in P5abc RNA, a paradigm of RNA Folding studies. With mutations that systematically disrupt or restore putative structural elements, we found that this transition reflects local Folding of structural modules, with modest and incremental cooperativity that results in concerted behavior. First, two distant secondary structure changes are coupled through a bridging three-way junction and Mg2+-dependent tertiary structure. Second, long-range contacts are formed between modules, resulting in additional cooperativity. Given the sparseness of RNA tertiary contacts after secondary structure formation, we expect that modular Folding and incremental cooperativity are generally important for specifying functional structures while also providing productive kinetic paths to these structures. Additionally, we expect our approach to be useful for uncovering modularity in other complex RNAs.
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single molecule fluorescence reveals commonalities and distinctions among natural and in vitro selected RNA tertiary motifs in a multistep Folding pathway
Journal of the American Chemical Society, 2017Co-Authors: Steve Bonilla, Namita Bisaria, Charles Limouse, Hideo Mabuchi, Magdalena Gebala, Daniel HerschlagAbstract:Decades of study of the RNA Folding problem have revealed that diverse and complex structured RNAs are built from a common set of recurring structural motifs, leading to the perspective that a generalizable model of RNA Folding may be developed from understanding of the Folding properties of individual structural motifs. We used single-molecule fluorescence to dissect the kinetic and thermodynamic properties of a set of variants of a common tertiary structural motif, the tetraloop/tetraloop-receptor (TL/TLR). Our results revealed a multistep TL/TLR Folding pathway in which preorganization of the ubiquitous AA-platform submotif precedes the formation of the docking transition state and tertiary A-minor hydrogen bond interactions form after the docking transition state. Differences in ion dependences between TL/TLR variants indicated the occurrence of sequence-dependent conformational rearrangements prior to and after the formation of the docking transition state. Nevertheless, varying the junction connecti...
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quantitative tests of a reconstitution model for RNA Folding thermodynamics and kinetics
Proceedings of the National Academy of Sciences of the United States of America, 2017Co-Authors: Namita Bisaria, Max Greenfeld, Charles Limouse, Hideo Mabuchi, Daniel HerschlagAbstract:Decades of study of the architecture and function of structured RNAs have led to the perspective that RNA tertiary structure is modular, made of locally stable domains that retain their structure across RNAs. We formalize a hypothesis inspired by this modularity—that RNA Folding thermodynamics and kinetics can be quantitatively predicted from separable energetic contributions of the individual components of a complex RNA. This reconstitution hypothesis considers RNA tertiary Folding in terms of ΔGalign, the probability of aligning tertiary contact partners, and ΔGtert, the favorable energetic contribution from the formation of tertiary contacts in an aligned state. This hypothesis predicts that changes in the alignment of tertiary contacts from different connecting helices and junctions (ΔGHJH) or from changes in the electrostatic environment (ΔG+/−) will not affect the energetic perturbation from a mutation in a tertiary contact (ΔΔGtert). Consistent with these predictions, single-molecule FRET measurements of Folding of model RNAs revealed constant ΔΔGtert values for mutations in a tertiary contact embedded in different structural contexts and under different electrostatic conditions. The kinetic effects of these mutations provide further support for modular behavior of RNA elements and suggest that tertiary mutations may be used to identify rate-limiting steps and dissect Folding and assembly pathways for complex RNAs. Overall, our model and results are foundational for a predictive understanding of RNA Folding that will allow manipulation of RNA Folding thermodynamics and kinetics. Conversely, the approaches herein can identify cases where an independent, additive model cannot be applied and so require additional investigation.
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visualizing the formation of an RNA Folding intermediate through a fast highly modular secondary structure switch
Nature Communications, 2016Co-Authors: Yi Xue, Rick Russell, Daniel Herschlag, Brant Gracia, Hashim M AlhashimiAbstract:Intermediates play important roles in RNA Folding but can be difficult to characterize when short-lived or not significantly populated. By combining (15)N relaxation dispersion NMR with chemical probing, we visualized a fast (kex=k1+k-1≈423 s(-1)) secondary structural switch directed towards a low-populated (∼3%) partially folded intermediate in tertiary Folding of the P5abc subdomain of the 'Tetrahymena' group I intron ribozyme. The secondary structure switch changes the base-pairing register across the P5c hairpin, creating a native-like structure, and occurs at rates of more than two orders of magnitude faster than tertiary Folding. The switch occurs robustly in the absence of tertiary interactions, Mg(2+) or even when the hairpin is excised from the three-way junction. Fast, highly modular secondary structural switches may be quite common during RNA tertiary Folding where they may help smoothen the Folding landscape by allowing Folding to proceed efficiently via additional pathways.
Reidun Twarock - One of the best experts on this subject based on the ideXlab platform.
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Genomic RNA Folding mediates assembly of human parechovirus
Nature Communications, 2017Co-Authors: Shabih Shakeel, Sarah J Butcher, Eric C. Dykeman, Simon J. White, Joseph J.b. Cockburn, Peter G. Stockley, Reidun TwarockAbstract:The mechanism underlying packaging of genomic RNA into viral particles is not well understood for human parechoviruses. Here the authors identify short RNA motifs in the parechovirus genome that bind capsid proteins, providing approximately 60 specific interactions for virion assembly. Assembly of the major viral pathogens of the PicoRNAviridae family is poorly understood. Human parechovirus 1 is an example of such viruses that contains 60 short regions of ordered RNA density making identical contacts with the protein shell. We show here via a combination of RNA-based systematic evolution of ligands by exponential enrichment, bioinformatics analysis and reverse genetics that these RNA segments are bound to the coat proteins in a sequence-specific manner. Disruption of either the RNA coat protein recognition motif or its contact amino acid residues is deleterious for viral assembly. The data are consistent with RNA packaging signals playing essential roles in virion assembly. Their binding sites on the coat proteins are evolutionarily conserved across the Parechovirus genus, suggesting that they represent potential broad-spectrum anti-viral targets.
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genomic RNA Folding mediates assembly of human parechovirus
Nature Communications, 2017Co-Authors: Shabih Shakeel, Sarah J Butcher, Eric C. Dykeman, Simon J. White, Joseph J.b. Cockburn, Peter G. Stockley, Ari Ora, Reidun TwarockAbstract:Assembly of the major viral pathogens of the PicoRNAviridae family is poorly understood. Human parechovirus 1 is an example of such viruses that contains 60 short regions of ordered RNA density making identical contacts with the protein shell. We show here via a combination of RNA-based systematic evolution of ligands by exponential enrichment, bioinformatics analysis and reverse genetics that these RNA segments are bound to the coat proteins in a sequence-specific manner. Disruption of either the RNA coat protein recognition motif or its contact amino acid residues is deleterious for viral assembly. The data are consistent with RNA packaging signals playing essential roles in virion assembly. Their binding sites on the coat proteins are evolutionarily conserved across the Parechovirus genus, suggesting that they represent potential broad-spectrum anti-viral targets.
