Energy landscape of k-point mutants of an RNA molecule
Speaker: J. Waldispuhl, BC/ MIT and P. Clote, BC ,
Date: October 31 2005
Time: 11:30AM to 1:00PM
Location: 32-G575
Host: Bonnie Berger, MIT
Contact: Kathleen Dickey, 617 253 3037, kvdickey@mit.edu
Relevant URL: http://www-math.mit.edu/compbiosem/****IN 10 MINUTES****
A k-point mutant of a given RNA sequence s = s_1,...,s_n is an RNA sequence
s' = s'_1,...,s'_n obtained by mutating exactly k-positions in s; i.e. Hamming
distance between s and s' equals k. To understand the effect of pointwise
mutation in RNA, we consider the distribution of energies of all secondary
structures of k-point mutants of a given RNA sequence.
Here we describe a novel algorithm to compute the mean and standard deviation
of energies of all secondary structures of k-point mutants of a given RNA
sequence. We then focus on the tail of the energy distribution, and compute,
using the algorithm AMSAG, the k-superoptimal structure; i.e. the secondary
structure of a mutant having least free energy over all secondary structures of all
k'-point mutants of a given RNA sequence, for k' <= k. Evidence is presented that
the k-superoptimal secondary structure is often closer, as measured
by base pair distance, and two additional distance measures, to the secondary
structure derived by comparative sequence analysis than is the Zuker
minimum free energy structure of the original (wild-type or unmutated) RNA.
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