Authors:
Saad Mneimneh
1
and
Syed Ali Ahmed
2
Affiliations:
1
Hunter College of the City University of New York, United States
;
2
The Graduate Center of the City University of New York, United States
Keyword(s):
Multiple RNA Interaction, RNA Structure, Gibbs Sampling, Metropolis-Hastings Algorithm, Clustering.
Related
Ontology
Subjects/Areas/Topics:
Algorithms and Software Tools
;
Bioinformatics
;
Biomedical Engineering
;
Biostatistics and Stochastic Models
;
Structural Bioinformatics
;
Structural Variations
;
Structure Prediction
Abstract:
The interaction of two RNA molecules involves a complex interplay between folding and binding that warranted recent developments in RNA-RNA interaction algorithms. These algorithms cannot be used to predict interaction structures when the number of RNAs is more than two. Our recent formulation of the multiple RNA interaction problem is based on a combinatorial optimization called Pegs and Rubber Bands, and has been successful in predicting structures that involve more than two RNAs. Even then, however, the optimal solution obtained does not necessarily correspond to the actual biological structure. Moreover, a structure produced by interacting RNAs may not be unique to start with. Multiple solutions (thus sub-optimal ones) are needed. We extend our previous approach to generate multiple sub-optimal solutions that was based on exhaustive enumeration. Here, a sampling approach for multiple RNA interaction is developed. Since not too many samples are needed to reveal solutions that are
sufficiently different, sampling provides a much faster alternative. By clustering the sampled solutions, we are able to obtain representatives that correspond to the biologically observed structures. Specifically, our results for the U2-U6 complex and its introns in the spliceosome of yeast, and the CopA-CopT complex in E. Coli are consistent with published biological structures.
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