The availability of an accurate model for RNA tertiary folding can greatly aid in our understanding of RNA functions and in RNA-targeted drug discovery. However, unlike the protein folding problem which has been extensively studied for decades, modeling of tertiary RNA folding is a relatively new field of endeavor. Our current graph-theoretic thermodynamic model has allowed us to make better predictions than other existing models on RNA secondary structure melting curves. In this proposal, we aim to move beyond the secondary structure model to study tertiary RNA folding. A key advantage of our approach is the completeness and certainty in our conformational sampling. Incomplete conformational sampling may result in unacceptable loss of accuracy. Our thermodynamic and kinetic models will be developed in parallel in this project. The thermodynamic model, in which user can supply energy parameters, will enable us to extract parameters for RNA tertiary interactions from experimental melting curves. Since the first submission of this proposal, we have generated new results indicating that we can accurately capture tertiary folds and off-lattice conformations to give reliable partition functions. The kinetic model will be developed using a master equation approach, which we have successfully used to treat RNA hairpin folding kinetics. Our long-term goal is to move beyond hairpin to treat large complex RNAs. Our immediate goal is to remove two key """"""""roadblocks"""""""" on the road toward our long-term goal: to search for transition states from rate equations, and to reduce the rate equations by conformational clustering. Experimental tests will focus on a series of rationally designed RNA systems. A key point is that the experiments will be performed under exactly the same salt condition used in theoretical predictions.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM063732-05
Application #
7188625
Study Section
Molecular and Cellular Biophysics Study Section (BBCA)
Program Officer
Preusch, Peter C
Project Start
2003-03-01
Project End
2010-02-28
Budget Start
2007-03-01
Budget End
2010-02-28
Support Year
5
Fiscal Year
2007
Total Cost
$206,229
Indirect Cost
Name
University of Missouri-Columbia
Department
Physics
Type
Schools of Arts and Sciences
DUNS #
153890272
City
Columbia
State
MO
Country
United States
Zip Code
65211
Hakim, Chady H; Wasala, Nalinda B; Nelson, Christopher E et al. (2018) AAV CRISPR editing rescues cardiac and muscle function for 18 months in dystrophic mice. JCI Insight 3:
Hurst, Travis; Xu, Xiaojun; Zhao, Peinan et al. (2018) Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis. J Phys Chem B 122:4771-4783
Zhang, Dong; Chen, Shi-Jie (2018) IsRNA: An Iterative Simulated Reference State Approach to Modeling Correlated Interactions in RNA Folding. J Chem Theory Comput 14:2230-2239
Sun, Ting-Ting; Zhao, Chenhan; Chen, Shi-Jie (2018) Predicting Cotranscriptional Folding Kinetics For Riboswitch. J Phys Chem B 122:7484-7496
Zhang, Xinyue; Zhang, Dong; Zhao, Chenhan et al. (2017) Nanopore electric snapshots of an RNA tertiary folding pathway. Nat Commun 8:1458
Sun, Li-Zhen; Kranawetter, Clayton; Heng, Xiao et al. (2017) Predicting Ion Effects in an RNA Conformational Equilibrium. J Phys Chem B 121:8026-8036
Sun, Li-Zhen; Chen, Shi-Jie (2017) A New Method to Predict Ion Effects in RNA Folding. Methods Mol Biol 1632:1-17
Xu, Xiaojun; Duan, Dongsheng; Chen, Shi-Jie (2017) CRISPR-Cas9 cleavage efficiency correlates strongly with target-sgRNA folding stability: from physical mechanism to off-target assessment. Sci Rep 7:143
Zhao, Chenhan; Xu, Xiaojun; Chen, Shi-Jie (2017) Predicting RNA Structure with Vfold. Methods Mol Biol 1654:3-15
Sun, Li-Zhen; Zhang, Dong; Chen, Shi-Jie (2017) Theory and Modeling of RNA Structure and Interactions with Metal Ions and Small Molecules. Annu Rev Biophys 46:227-246

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