Abstract
BackgroundDifficult problems in structural bioinformatics are often studied in simple exact models to gain insights and to derive general principles. Protein folding, for example, has long been studied in the lattice model. Recently, researchers have also begun to apply the lattice model to the study of RNA folding.ResultsWe present a novel method for predicting RNA secondary structures with pseudoknots: first simulate the folding dynamics of the RNA sequence on the 3D triangular lattice, next extract and select a set of disjoint base pairs from the best lattice conformation found by the folding simulation. Experiments on sequences from PseudoBase show that our prediction method outperforms the HotKnot algorithm of Ren, Rastegari, Condon and Hoos, a leading method for RNA pseudoknot prediction. Our method for RNA secondary structure prediction can be adapted into an efficient reconstruction method that, given an RNA sequence and an associated secondary structure, finds a conformation of the sequence on the 3D triangular lattice that realizes the base pairs in the secondary structure. We implemented a suite of computer programs for the simulation and visualization of RNA folding on the 3D triangular lattice. These programs come with detailed documentation and are accessible from the companion website of this paper at http://www.cs.usu.edu/~mjiang/rna/DeltaIS/.ConclusionFolding simulation on the 3D triangular lattice is effective method for RNA secondary structure prediction and lattice conformation reconstruction. The visualization software for the lattice conformations of RNA structures is a valuable tool for the study of RNA folding and is a great pedagogic device.
Highlights
IntroductionDifficult problems in structural bioinformatics are often studied in simple exact models to gain insights and to derive general principles
The visualization software for the lattice conformations of RNA structures is a valuable tool for the study of RNA folding and is a great pedagogic device
Difficult problems in structural bioinformatics are often studied in simple exact models to gain insights and to derive general principles
Summary
Difficult problems in structural bioinformatics are often studied in simple exact models to gain insights and to derive general principles. We present a novel method for predicting RNA secondary structures with pseudoknots: first simulate the folding dynamics of the RNA sequence on the 3D triangular lattice, extract and select a set of disjoint base pairs from the best lattice conformation found by the folding simulation. Our method for RNA secondary structure prediction can be adapted into an efficient reconstruction method that, given an RNA sequence and an associated secondary structure, finds a conformation of the sequence on the 3D triangular lattice that realizes the base pairs in the secondary structure. The structure prediction problem reduces to the simplified problem of finding a lattice conformation of the biopolymer to achieve certain desirable properties: for protein folding, to maximize the number of contacts between hydrophobic amino acids; for RNA folding, to maximize the number of hydrogen bonds between complementary bases. The simplified problem does not reflect the full reality of underlying biological process, but at (page number not for citation purposes)
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