Modeling RNA Folding Pathways and Intermediates Using Time-Resolved Hydroxyl Radical Footprinting Data
The analysis of time-resolved hydroxyl radical (•OH) footprinting data can reveal the complex and rugged folding landscape of an RNA molecule. This analysis requires the identification and subsequent optimization of a kinetic model and its parameters. The number of possible kinetic models increases factorially with the complexity of the molecule, complicating the modeling process. We detail here a computational approach that allows complex models involving up to five kinetic intermediates to be run on a desktop computer. Our approach involves an initial “model-free” analysis of the data, which reduces the computational complexity of the subsequent kinetic parameter optimization. Our method is able to systematically identify the best fitting kinetic model and reveals the underlying folding mechanism of an RNA.
KeywordsKinetic Model Progress Curve State Curve Counterion Concentration Folding Reaction
We thank Michael Brenowitz and Joerg Schlatterer for their insightful discussions and comments during the preparation of this chapter. This work is supported by the US National Institutes of Health, NIGMS R00 079953 grant to A.L. Source code, and example data sets can be downloaded from https://simtk.org/home/KinFold.