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A computational proposal for designing structured RNA pools for in vitro selection of RNAs.
Kim, Namhee; Gan, Hin Hark; Schlick, Tamar.
Affiliation
  • Kim N; Department of Chemistry, New York University, New York, NY 10003, USA.
RNA ; 13(4): 478-92, 2007 Apr.
Article in En | MEDLINE | ID: mdl-17322501
Although in vitro selection technology is a versatile experimental tool for discovering novel synthetic RNA molecules, finding complex RNA molecules is difficult because most RNAs identified from random sequence pools are simple motifs, consistent with recent computational analysis of such sequence pools. Thus, enriching in vitro selection pools with complex structures could increase the probability of discovering novel RNAs. Here we develop an approach for engineering sequence pools that links RNA sequence space regions with corresponding structural distributions via a "mixing matrix" approach combined with a graph theory analysis. We define five classes of mixing matrices motivated by covariance mutations in RNA; these constructs define nucleotide transition rates and are applied to chosen starting sequences to yield specific nonrandom pools. We examine the coverage of sequence space as a function of the mixing matrix and starting sequence via clustering analysis. We show that, in contrast to random sequences, which are associated only with a local region of sequence space, our designed pools, including a structured pool for GTP aptamers, can target specific motifs. It follows that experimental synthesis of designed pools can benefit from using optimized starting sequences, mixing matrices, and pool fractions associated with each of our constructed pools as a guide. Automation of our approach could provide practical tools for pool design applications for in vitro selection of RNAs and related problems.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Selection, Genetic / RNA / Computational Biology Type of study: Prognostic_studies Language: En Journal: RNA Journal subject: BIOLOGIA MOLECULAR Year: 2007 Document type: Article Affiliation country: United States Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Selection, Genetic / RNA / Computational Biology Type of study: Prognostic_studies Language: En Journal: RNA Journal subject: BIOLOGIA MOLECULAR Year: 2007 Document type: Article Affiliation country: United States Country of publication: United States