Free energy minimization to predict RNA secondary structures and computational RNA design

Alexander Churkin, Lina Weinbrand, Danny Barash

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Determining the RNA secondary structure from sequence data by computational predictions is a longstanding problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

Original languageEnglish
Pages (from-to)3-16
Number of pages14
JournalMethods in Molecular Biology
Volume1269
DOIs
StatePublished - 1 Jan 2015

Keywords

  • Free energy minimization methods
  • RNA bioinformatics
  • RNA folding prediction
  • RNA free energy parameters
  • RNA secondary structure prediction

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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