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a probabilistic model of rna conformational space一个rna构象空间的概率模型
A Probabilistic Model of RNA Conformational Space
1. 1. 1 2 3
Jes Frellsen , Ida Moltke , Martin Thiim , Kanti V. Mardia , Jesper Ferkinghoff-Borg , Thomas
Hamelryck1*
1The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark, 2 Department of Statistics, University of Leeds, Leeds, United
Kingdom, 3 DTU Elektro, Technical University of Denmark, Lyngby, Denmark
Abstract
The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA
3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an
accurate energy function and a conformational sampling procedure. Both are only partly solved problems. Here, we focus
on the problem of conformational sampling. The current state of the art solution is based on fragment assembly methods,
which construct plausible conformations by stringing together short fragments obtained from experimental structures.
However, the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and
their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these
important limitations: a probabilistic model of RNA structure that allows efficient sampling of RNA conformations in
continuous space, and with associated probabilities. We show that the model captures several key features of RNA structure,
such as its rotameric nature and the distribution of the helix lengths. Furthermore, the model readily generates native-like 3-
D conformations for 9
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