A domain-based model for predicting large and complex pseudoknotted structures

Song Cao, Shi Jie Chen

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Pseudoknotted structures play important structural and functional roles in RNA cellular functions at the level of transcription, splicing and translation. However, the problem of computational prediction for large pseudoknotted folds remains. Here we develop a domain-based method for predicting complex and large pseudoknotted structures from RNA sequences. The model is based on the observation that large RNAs can be separated into different structural domains. The basic idea is to first identify the domains and then predict the structures for each domain. Assembly of the domain structures gives the full structure. The use of the domain-based approach leads to a reduction of computational time by a factor of about ∼N2 for an N-nt sequence. As applications of the model, we predict structures for a variety of RNA systems, such as regions in human telomerase RNA (hTR), internal ribosome entry site (IRES) and HIV genome. The lengths of these sequences range from 200-nt to 400-nt. The results show good agreements with the experiments.

Original languageEnglish
Pages (from-to)201-212
Number of pages12
JournalRNA Biology
Volume9
Issue number2
DOIs
StatePublished - Feb 2012
Externally publishedYes

Keywords

  • Hepatitis delta virus (HDV)
  • Human immunodeficiency virus (HIV)
  • Human telomerase RNA (hTR)
  • Internal ribosome entry site (IRES)
  • Large RNAs
  • Pseudoknots
  • Structural predictions

Fingerprint Dive into the research topics of 'A domain-based model for predicting large and complex pseudoknotted structures'. Together they form a unique fingerprint.

  • Cite this