scholarly journals Cooperative RNA Folding under Cellular Conditions Arises From Both Tertiary Structure Stabilization and Secondary Structure Destabilization

Biochemistry ◽  
2017 ◽  
Vol 56 (27) ◽  
pp. 3422-3433 ◽  
Author(s):  
Kathleen A. Leamy ◽  
Neela H. Yennawar ◽  
Philip C. Bevilacqua
2018 ◽  
Author(s):  
Osama Alaidi ◽  
Fareed Aboul-ela

ABSTRACTThe realization that non protein-coding RNA (ncRNA) is implicated in an increasing number of cellular processes, many related to human disease, makes it imperative to understand and predict RNA folding. RNA secondary structure prediction is more tractable than tertiary structure or protein structure. Yet insights into RNA structure-function relationships are complicated by coupling between RNA folding and ligand binding. Here, we introduce a simple statistical mechanical formalism to calculate perturbations to equilibrium secondary structure conformational distributions for RNA, in the presence of bound cognate ligands. For the first time, this formalism incorporates a key factor in coupling ligand binding to RNA conformation: the differential affinity of the ligand for a range of RNA-folding intermediates. We apply the approach to the SAM-I riboswitch, for which binding data is available for analogs of intermediate secondary structure conformers. Calculations of equilibrium secondary structure distributions during the transcriptional “decision window” predict subtle shifts due to the ligand, rather than an on/off switch. The results suggest how ligand perturbation can release a kinetic block to the formation of a terminator hairpin in the full-length riboswitch. Such predictions identify aspects of folding that are most affected by ligand binding, and can readily be compared with experiment.


ChemBioChem ◽  
2021 ◽  
Author(s):  
Anissa Haim ◽  
Saskia Neubacher ◽  
Tom N. Grossmann

Author(s):  
Roma Chandra

Protein structure prediction is one of the important goals in the area of bioinformatics and biotechnology. Prediction methods include structure prediction of both secondary and tertiary structures of protein. Protein secondary structure prediction infers knowledge related to presence of helixes, sheets and coils in a polypeptide chain whereas protein tertiary structure prediction infers knowledge related to three dimensional structures of proteins. Protein secondary structures represent the possible motifs or regular expressions represented as patterns that are predicted from primary protein sequence in the form of alpha helix, betastr and and coils. The secondary structure prediction is useful as it infers information related to the structure and function of unknown protein sequence. There are various secondary structure prediction methods used to predict about helixes, sheets and coils. Based on these methods there are various prediction tools under study. This study includes prediction of hemoglobin using various tools. The results produced inferred knowledge with reference to percentage of amino acids participating to produce helices, sheets and coils. PHD and DSC produced the best of the results out of all the tools used.


2018 ◽  
Author(s):  
Steven Verlinden ◽  
Niels Geudens ◽  
José Martins ◽  
Steven Ballet ◽  
Guido Verniest

2017 ◽  
Vol 13 (4) ◽  
Author(s):  
Nancy Singh ◽  
Sunil Datt Sharma ◽  
Ragothaman M. Yennamalli

AbstractIn this article, we describe the applicability of a signal processing method, specifically the modified S-transform (MST) method, on RNA sequences to identify periodicities between 2 and 11. MicroRNAs (miRNA) are associated with gene regulation and gene silencing and thus have wide applications in biological sciences. Also, the functionality of miRNA is highly associated with its secondary structures (stem, bulge and loop). Signal processing methods have been previously applied on genomic data to reveal the periodicities that determine a wide variety of biological functions, ranging from exon detection to microsatellite identification in DNA sequences. However, there has been less focus on RNA-based signal processing. Here, we show that the signal processing method can be successfully applied to miRNA sequences. We observed that these periodicities are highly correlated with the secondary structure of miRNA and such methods could possibly be used as indicators of secondary and tertiary structure formation.


Author(s):  
Bruce A. Shapiro ◽  
Wojciech Kasprzak

Genomic information (nucleic acid and amino acid sequences) completely determines the characteristics of the nucleic acid and protein molecules that express a living organism’s function. One of the greatest challenges in which computation is playing a role is the prediction of higher order structure from the one-dimensional sequence of genes. Rules for determining macromolecule folding have been continually evolving. Specifically in the case of RNA (ribonucleic acid) there are rules and computer algorithms/systems (see below) that partially predict and can help analyze the secondary and tertiary interactions of distant parts of the polymer chain. These successes are very important for determining the structural and functional characteristics of RNA in disease processes and hi the cell life cycle. It has been shown that molecules with the same function have the potential to fold into similar structures though they might differ in their primary sequences. This fact also illustrates the importance of secondary and tertiary structure in relation to function. Examples of such constancy in secondary structure exist in transfer RNAs (tRNAs), 5s RNAs, 16s RNAs, viroid RNAs, and portions of retroviruses such as HIV. The secondary and tertiary structure of tRNA Phe (Kim et al., 1974), of a hammerhead ribozyme (Pley et al., 1994), and of Tetrahymena (Cate et al., 1996a, 1996b) have been shown by their crystal structure. Currently little is known of tertiary interactions, but studies on tRNA indicate these are weaker than secondary structure interactions (Riesner and Romer, 1973; Crothers and Cole, 1978; Jaeger et al., 1989b). It is very difficult to crystallize and/or get nuclear magnetic resonance spectrum data for large RNA molecules. Therefore, a logical place to start in determining the 3D structure of RNA is computer prediction of the secondary structure. The sequence (primary structure) of an RNA molecule is relatively easy to produce. Because experimental methods for determining RNA secondary and tertiary structure (when the primary sequence folds back on itself and forms base pairs) have not kept pace with the rapid discovery of RNA molecules and their function, use of and methods for computer prediction of secondary and tertiary structures have increasingly been developed.


2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Zareh A. Grigoryan ◽  
Armen T. Karapetian

The mutual influence of the slow rearrangements of secondary structure and fast collapse of the long single-stranded RNA (ssRNA) in approximation of coarse-grained model is studied with analytic calculations. It is assumed that the characteristic time of the secondary structure rearrangement is much longer than that for the formation of the tertiary structure. A nonequilibrium phase transition of the 2nd order has been observed.


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