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ecs 129 Forewords Introduction Nucleic Acids Proteins: Amino Acids Proteins: Secondary and Tertiary Structures Sequence Comparison Protein Structure Classification RNA Structure Prediction Lecture Notes Summary Supporting Papers Quiz Protein Structure Prediction Protein Protein Interaction Docking Databases Review Quick links pakoehl@ucdavis.edu

Patrice Koehl's teaching web site > ecs 129 > RNA Structure Prediction > Summary Personal tools Log in Summary RNA structure predictions: Summary Many RNAs fold into structures that are important for regulatory, catalytic, or structural roles in cells. RNA structures are dominated by base-pairing interactions, mostly Watson Crick pairs between A and U, and G and C. A reliable approach for RNA structure prediction is comparative sequence analysis, in which co-varying nucleotides are identified in a multiple sequence alignment of RNAs with similar structures. Covarying residues are likely to form base pairs in the RNA structures; they co-vary to maintain the complementarity. RNA secondary structures are defined as sections of the RNA structures in which base pairs are nested (i.e. if base i pairs with j, base i+1 can only pair with a base between i+2 and j-1) RNA secondary structures can be predicted using dynamic programming. This is implemented in programs like Mfold. The complexity of such algorithm in N*N*N, where N is the length of the RNA Tertiary interactions in RNA cover base-pairs that are not nested. These are observed in pseudo-knots, kissing hairpins, and hairpin-bulge interactions. Tertiary interactions cannot be predicted by dynamic programming. Methods exist to predict tertiary structures, but they are of high complexity (at least N**6)

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