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Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations
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 m...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385882/ https://www.ncbi.nlm.nih.gov/pubmed/28393861 http://dx.doi.org/10.1038/srep45812 |
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author | Bell, David R. Cheng, Sara Y. Salazar, Heber Ren, Pengyu |
author_facet | Bell, David R. Cheng, Sara Y. Salazar, Heber Ren, Pengyu |
author_sort | Bell, David R. |
collection | PubMed |
description | 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 (R(2) = 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). |
format | Online Article Text |
id | pubmed-5385882 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53858822017-04-12 Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations Bell, David R. Cheng, Sara Y. Salazar, Heber Ren, Pengyu Sci Rep Article 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 (R(2) = 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). Nature Publishing Group 2017-04-10 /pmc/articles/PMC5385882/ /pubmed/28393861 http://dx.doi.org/10.1038/srep45812 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Bell, David R. Cheng, Sara Y. Salazar, Heber Ren, Pengyu Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations |
title | Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations |
title_full | Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations |
title_fullStr | Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations |
title_full_unstemmed | Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations |
title_short | Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations |
title_sort | capturing rna folding free energy with coarse-grained molecular dynamics simulations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385882/ https://www.ncbi.nlm.nih.gov/pubmed/28393861 http://dx.doi.org/10.1038/srep45812 |
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