Structural Biochemistry/Nucleic Acid/RNA/RNA Secondary Structure

Basis of RNA -RNA bases: A,G,C,U -Base Pairs: A-U, G-C -non-canonical pairs: G-U -Stability: G-C > A-U > G-U -Single Stranded: strand folds upon it to form base pairs; can have a diverse form of secondary structure Secondary Structure Structure Rules Base pairing stabilize the structure Unpaired sections-loops destabilize the structure When a base in one position changes, the base it pairs to must also change to maintain the same structure-covariation Representations -Most base pairs are non-crossing base pairs: -any two pairs (i, j) and (i’, j’) -> i < i’ <j’ < j or i’ < i < j < j’ Circular Representation -Base pairs of a secondary structure represented by a circle -Arc drawn for each base pairing in the structure Combinatorics -The number of RNA secondary structures for the sequence: (Recurrence Relation) S(0)=S(1)=S(2)=1 S(n+1)=S(n)+ƩS(j-1)S(n-j), (n≥2) -There are approximately 1.3 billion RNA structures of length n is 27 Types of regions 1) Hairpin Loop - 4 or more bases long for each loop 2) Bulge Loop - bases on one side cannot form base pairs 3) Interior Loop - bases on both sides cannot form base pairs 4) Multi Loop (Junctions) – 2 or more double stranded regions converge to form a closed structure Structure Prediction Methods 1) Maximize Base Pairs -Determine set of maximal base pairs -Align bases based on ability to pair up to determine the optical structure -Nussinov Algorithm: 4 ways to get the optimal structure between i and j -Find strucuter with the most base pairs: A-U and G-C 2) Minimize Energy -Determine maximum of scores for 4 structures at a particular position -Stacks are the dominant stabilizing force -Energy minimization algorithm predicts the secondary structure by minimizing the free energy -Require estimation of energy terms contributing to secondary structure -Dynamic programming approach: 1) Initialization 2) Recursion 3) Traceback -Does not require prior sequence alighnment -Energy associated with any position is only influenced by local sequence and structure References How Do RNA Folding Algorithms Work? S.R. Eddy. Nature Biotechnology, 22:1457-1458, 2004. <http://en.wikipedia.org/wiki/Biomolecular_structure>