Chapter title |
A New Method to Predict Ion Effects in RNA Folding
|
---|---|
Chapter number | 1 |
Book title |
RNA Nanostructures
|
Published in |
Methods in molecular biology, July 2017
|
DOI | 10.1007/978-1-4939-7138-1_1 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7137-4, 978-1-4939-7138-1
|
Authors |
Li-Zhen Sun, Shi-Jie Chen |
Abstract |
The strong interaction between metal ions in solution and highly charged RNA molecules is critical for RNA structure formation and stabilization. Metal ions binding to RNA can induce RNA structural changes that are important for RNA cellular functions. Therefore, quantitative modeling of the ion effects is essential for RNA structure prediction and RNA-based molecular design. Recently, inspired by the increasing experimental evidence that supports the importance of ion correlation and fluctuation in ion-RNA interactions, we developed a new computational model, Monte Carlo Tightly Bound Ion (MCTBI) model. The validity of the model is shown by the improved accuracy in the predictions for ion binding properties and ion-dependent free energies for RNA structures. In this chapter, using homodimeric tetraloop-receptor docking as an illustrative example, we showcase the MCTBI method for the computational prediction of the ion effects in RNA folding. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 8 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 2 | 25% |
Professor > Associate Professor | 1 | 13% |
Student > Ph. D. Student | 1 | 13% |
Unknown | 4 | 50% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 2 | 25% |
Chemical Engineering | 1 | 13% |
Agricultural and Biological Sciences | 1 | 13% |
Unknown | 4 | 50% |