title: Accurate prediction of RNA nucleotide interactions with backbone k-tree model.
abstract: BACKGROUND
  Given the importance of non-coding RNAs to cellular regulatory functions, it would be highly desirable to have accurate computational prediction of RNA 3D structure, a task which remains challenging. Even for a short RNA sequence, the space of tertiary conformations is immense; existing methods to identify native-like conformations mostly resort to random sampling of conformations to achieve computational feasibility. However, native conformations may not be examined and prediction accuracy may be compromised due to sampling. State-of-the-art methods have yet to deliver satisfactory predictions for RNAs of length beyond 50 nucleotides.
  
  
  RESULTS
  This paper presents a method to tackle a key step in the RNA 3D structure prediction problem, the prediction of the nucleotide interactions that constitute the desired 3D structure. The research is based on a novel graph model, called a backbone k-tree, to tightly constrain the nucleotide interaction relationships considered for RNA 3D structures. It is shown that the new model makes it possible to efficiently predict the optimal set of nucleotide interactions (including the non-canonical interactions in all recently revealed families) from the query sequence along with known or predicted canonical basepairs. The preliminary results indicate that in most cases the new method can predict with a high accuracy the nucleotide interactions that constitute the 3D structure of the query sequence. It thus provides a useful tool for the accurate prediction of RNA 3D structure.
  
  
  METHODS
  The source package for BkTree is available at http://rna-informatics.uga.edu/index.php?f=software&p=BkTree.
  
  
  BACKGROUND
  lding@uga.edu or cai@cs.uga.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Computer Science.
authors.forename: Liang
authors.initials: L
authors.lastname: Ding
authors.affiliation: Department of Computer Science.
authors.forename: Xingran
authors.initials: X
authors.lastname: Xue
authors.affiliation: Department of Computer Science.
authors.forename: Sal
authors.initials: S
authors.lastname: LaMarca
authors.affiliation: Department of Computer Science.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Mohebbi
authors.affiliation: Department of Computer Science, BUITEMS, Pakistan.
authors.forename: Abdul
authors.initials: A
authors.lastname: Samad
authors.affiliation: Institute of Bioinformatics and Department of Plant Biology, University of Georgia, GA 30602, USA and.
authors.forename: Russell L
authors.initials: RL
authors.lastname: Malmberg
authors.affiliation: Department of Computer Science, Institute of Bioinformatics and.
authors.forename: Liming
authors.initials: L
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D006801:Humans; D008962:Models, Theoretical; D009690:Nucleic Acid Conformation; D059372:Nucleotide Motifs; D012313:RNA / Q000737:chemistry* / Q000378:metabolism*; D017423:Sequence Analysis, RNA / Q000379:methods*
chemical_list: D012313:RNA