Improved prediction of RNA tertiary structure with insights into native state dynamics

Bida, John P.; Maher, L. James

doi:10.1261/rna.027201.111

Cited by 35 publications

(32 citation statements)

References 36 publications

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“…Other studies have shown the prediction of mRNA structure for comprehending the tertiary mRNA structure and the positive or negative impacts of the resulting protein on the organism (Marashi et al, 2006;Frellsen et al, 2009;Bida and Maher, 2012;Contrant et al, 2014) as well as its use in manipulating genetic sequences, for example, to create new recombinant vaccines (Ilyinskii et al, 2009). …”

Section: Resultsmentioning

confidence: 99%

Predicted philogeny, secondary conformational structure, and epitope antigenicity of immunological sequences in poultry

et al. 2017

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ABSTRACT. Poultry production is faced with different types of stresses that are responsible for issues of animal welfare as well as for economic losses. Moreover, the immunity decreases when animals are stressed. In silico analyses are important in reducing the cost and in increasing the accuracy of scientific results. A bioinformatics tool was used to perform ontology studies on 15 different immunological sequences of poultry. The mRNA structures and sequences with maximum antigenic residues were also predicted. No homology was found between the sequences of poultry and mammals. These results helped in the prediction of new potential molecular markers. Of the 15 sequences that were analyzed, predictions could not be made for five because they were longer than 2500 nucleotides; for the remaining 10 sequences, 20 conformational 2 L.J. Lara et al. Genetics and Molecular Research 16 (2): gmr16029423structures per sequence were predicted and the most stable sequences were identified by their minimum free energy values. The highest antigenic epitopes were accepted by the maximum scores; 15 of the total 8934 epitopes that were predicted were analyzed. These results would aid future studies that use synthetic peptides or recombinants as markers or immunomodulators and would expand our understanding on how stress can modulate the immune system. These would also help in developing rapid diagnostic tools, in increasing animal welfare, biosecurity, and productivity, and also in developing of food additives and environmental enrichment for stress control, thereby, making animal production more sustainable.

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Section: Resultsmentioning

confidence: 99%

Predicted philogeny, secondary conformational structure, and epitope antigenicity of immunological sequences in poultry

et al. 2017

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“…Template based modeling uses predefined, small motifs to assemble RNA structures from their sequence. Template based models include the MC-Fold/MC-Sym pipeline47, BARNACLE48, RSIM49, 3dRNA50, RNAComposer51, Vfold52535455, RNA-MoIP56 and FARNA/FARFAR575859 available in the Rosetta package60. Similar to template based modeling, ASSEMBLE61 and RNA2D3D62 use homologous RNA structures to predict the new RNA structure (with manual refinement available).…”

Section: -D Structure Prediction Modelsmentioning

confidence: 99%

Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations

Bell

Cheng

Salazar

et al. 2017

Sci Rep

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We introduce a coarse-grained RNA model for molecular dynamics simulations, RACER (RnA CoarsE-gRained). RACER achieves accurate native structure prediction for a number of RNAs (average RMSD of 2.93 Å) and the sequence-specific variation of free energy is in excellent agreement with experimentally measured stabilities (R2 = 0.93). Using RACER, we identified hydrogen-bonding (or base pairing), base stacking, and electrostatic interactions as essential driving forces for RNA folding. Also, we found that separating pairing vs. stacking interactions allowed RACER to distinguish folded vs. unfolded states. In RACER, base pairing and stacking interactions each provide an approximate stability of 3–4 kcal/mol for an A-form helix. RACER was developed based on PDB structural statistics and experimental thermodynamic data. In contrast with previous work, RACER implements a novel effective vdW potential energy function, which led us to re-parameterize hydrogen bond and electrostatic potential energy functions. Further, RACER is validated and optimized using a simulated annealing protocol to generate potential energy vs. RMSD landscapes. Finally, RACER is tested using extensive equilibrium pulling simulations (0.86 ms total) on eleven RNA sequences (hairpins and duplexes).

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“…However, due to the many degrees of freedom, it is still difficult to fold RNA 3D structures with these all-atomistic force fields even with modern computational facilities. Consequently, the models with the all-atomistic fragments assembling have been developed based on the known fragments or secondary structures, [68][69][70][71][72][73][74][75][76] such as MC-fold/Mc-Sym pipeline [68] , FARNA/FARFAR [69,70] , RSIM [71] and RNAnbds [73,74] .…”

Section: All-atomistic Modelmentioning

confidence: 99%

“…[71] RNAnbds. The RNAnbds is designed to predict RNA 3D structures by fragment assembly based on the statistical configurations of bases according to their sequence/spatial neighbors in databases.…”

Section: Mc-fold/mc-symmentioning

confidence: 99%

RNA structure prediction: Progress and perspective

Shi¹,

Wu²,

Wang³

et al. 2014

Chinese Phys. B

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Many recent exciting discoveries have revealed the versatility of RNAs and their impo rtance in a variety of cellular functions which are strongly coupled to RNA structures. To understand the functions of RNAs, some structure prediction models have been developed in recent years. In this review, the progress in computational models for RNA structure prediction is introduced and the distinguishing features of many outstanding algorithms are discussed, emphasizing three dimensional (3D) structure prediction. A promising coarse-grained model for predicting RNA 3D structure, stability and salt effect is also introduced briefly. Finally, we discuss the major challenges in the RNA 3D structure modeling.

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Improved prediction of RNA tertiary structure with insights into native state dynamics

Cited by 35 publications

References 36 publications

Predicted philogeny, secondary conformational structure, and epitope antigenicity of immunological sequences in poultry

Predicted philogeny, secondary conformational structure, and epitope antigenicity of immunological sequences in poultry

Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations

RNA structure prediction: Progress and perspective

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