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RNA Secondary Structure Prediction Using High-throughput SHAPE
Published on: May 31, 2013
Statistical mechanics of secondary structures formed by random RNA sequences
1Department of Physics, University of California at San Diego, 9500 Gilman Drive, La Jolla, California 92093-0319, USA.
Abstract:
The formation of secondary structures by a random RNA sequence is studied as a model system for the sequence-structure problem omnipresent in biopolymers. Several toy energy models are introduced to allow detailed analytical and numerical studies. First, a two-replica calculation is performed. By mapping the two-replica problem to the denaturation of a single homogeneous RNA molecule in six-dimensional embedding space, we show that sequence disorder is perturbatively irrelevant, i.e., an RNA molecule with weak sequence disorder is in a molten phase where many secondary structures with comparable total energy coexist. A numerical study of various models at high temperature reproduces behaviors characteristic of the molten phase. On the other hand, a scaling argument based on the external statistics of rare regions can be constructed to show that the low-temperature phase is unstable to sequence disorder. We performed a detailed numerical study of the low-temperature phase using the droplet theory as a guide, and characterized the statistics of large-scale, low-energy excitations of the secondary structures from the ground state structure. We find the excitation energy to grow very slowly (i.e., logarithmically) with the length scale of the excitation, suggesting the existence of a marginal glass phase. The transition between the low-temperature glass phase and the high-temperature molten phase is also characterized numerically. It is revealed by a change in the coefficient of the logarithmic excitation energy, from being disorder dominated to being entropy dominated.
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