92-08-040

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Abstract:

RNA Multi-Structure Landscapes

## Sebastian Bonhoeffer, John S. McCaskill, Peter F. Stadler, and Peter
Schuster

Statistical properties of RNA folding landscapes obtained by the
partition function algorithm (McCaskill, 1990) are investigated in
detail. The pair correlation of free energies as a function of the
Hamming distance is used as a measure for the ruggedness of the
landscape. The caluculation of the partition function contains
information about the entire ensemble of secondary structures as a
function of temperature and opens the door to all quantities of
thermodynamic interest in contrast with the conventional minimal free
energy approach. A metric distance of structure ensembles is introduced
and pair coorelations at the level of the structures themselves are
computed. Just as with landscapes based on most stable secondary
structure prediction, the landscapes defined on the full biophysical
{\bf GCAU} alphabet are much smoother then the landscapes restricted to
pure {\bf GC} sequences and the correlation lengths are almost constant
fractions of the chain lengths. Correlation functions for
multi-structure landscapes exhibit an increased correlation length,
especially near the melting temperature. However, the main effect on
evolution is rather an effective increase in sampling for finite
populations where each sequence explores multiple structures.
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