Maximum expected accuracy structural neighbors of an RNA secondary structure.

Abstract

Since RNA molecules regulate genes and control alternative splicing by allostery, it is important to develop algorithms to predict RNA conformational switches. Some tools, such as paRNAss, RNAshapes and RNAbor, can be used to predict potential conformational switches; nevertheless, no existent tool can detect general (i.e., not family specific) entire riboswitches (both aptamer and expression platform) with accuracy. Thus, the development of additional algorithms to detect conformational switches seems important, especially since the difference in free energy between the two metastable secondary structures may be as large as 15-20 kcal/mol. It has recently emerged that RNA secondary structure can be more accurately predicted by computing the maximum expected accuracy (MEA) structure, rather than the minimum free energy (MFE) structure. Given an arbitrary RNA secondary structure S0 for an RNA nucleotide sequence a = a1,..., a(n), we say that another secondary structure S of a is a k-neighbor of S0, if the base pair distance between S0 and S is k. In this paper, we prove that the Boltzmann probability of all k-neighbors of the minimum free energy structure S0 can be approximated with accuracy ε and confidence 1 - p, simultaneously for all 0 ≤ k < K, by a relative frequency count over N sampled structures, provided that N>N(ε,p,K)=Φ-1(p/2K)2/4ε2, where Φ(z) is the cumulative distribution function (CDF) for the standard normal distribution. We go on to describe the algorithm RNAborMEA, which for an arbitrary initial structure S0 and for all values 0 ≤ k