Talk abstracts

Talk on Friday 02:15-02:30pm submitted by Hongying Sun

RNA folding nearest neighbor parameter derivation and RNA secondary structure prediction

Hongying Sun (Department of Biochemistry and Biophysics, University of Rochester), Jeffrey Zuber (Department of Biochemistry and Biophysics, University of Rochester), David H. Mathews (Department of Biochemistry and Biophysics, University of Rochester)

Abstract:
The folding stability of RNA secondary structure can be estimated using a nearest neighbor model, and this model is in widespread use to predict RNA secondary structures. Nearest neighbor parameters for predicting RNA folding free energy change at 37°C are based on a database of optical melting measurements on small model systems. This work revises and expands the nearest neighbor model by including the latest experimental results on the melting stability of small model systems. A statistical model called AIC was applied to determine and select nearest neighbor parameters that are significantly important to the stability of loops and to prevent overfitting. Surprisingly, we found that the AU helix-end penalty was removed by AIC model selection for hairpin loops, indicating that the AU end penalty should not be applied to hairpin loops. We also found that the stability of hairpin loops is independent of first mismatch sequence, which was assumed to be important in the previous 2004 model. We did a benchmark on a set of 3856 RNA sequences with known structures by implementing both 2004 and the new nearest neighbor parameters in the RNAstructure software package for RNA secondary structure prediction. Secondary structure prediction identified 1% more of the known pairs using the new model compared to 2004 model, and this improvement is statistically significant. Therefore, the new hairpin loop model predicts RNA secondary structure more accurately. We are implementing the complete new set of nearest neighbor parameters and hypothesize that this will improve the accuracy of RNA secondary structure prediction significantly.

References:
1. Chen JL, Dishler AL, Kennedy SD, et al. Testing the Nearest Neighbor Model for Canonical RNA Base Pairs: Revision of GU Parameters. Biochemistry. 2012;51(16):3508-3522. doi:10.1021/bi3002709.
2. Bellaousov S, Mathews DH. 2010. ProbKnot: Fast prediction of RNA secondary structure including pseudoknots. RNA 16: 1870-1880.
3. Mathews DH. 2004. Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization.
RNA 10: 1178-1190.
4. Mathews DH, Disney MD, Childs JL, Schroeder SJ, Zuker M, Turner DH. 2004. Incorporating chemical modification constraints into a dynamic program-
ming algorithm for prediction of RNA secondary structure. Proc Natl Acad Sci USA 101: 7287-7292.

Keywords: RNA Folding, RNA Secondary Structure Prediction, Nearest Neighbor Model