Smoothness within ruggedness: the role of neutrality in adaptation.

RNA secondary structure folding algorithms predict the existence of connected networks of RNA sequences with identical structure. On such networks, evolving populations split into subpopulations, which diffuse independently in sequence space. This demands a distinction between two mutation thresholds: one at which genotypic information is lost and one at which phenotypic information is lost. In between, diffusion enables the search of vast areas in genotype space while still preserving the dominant phenotype. By this dynamic the success of phenotypic adaptation becomes much less sensitive to the initial conditions in genotype space.

Protein evolution on partially correlated landscapes.

We extend an earlier model of protein evolution on a rugged landscape to the case in which the landscape exhibits a variable degree of correlation (i.e., smoothness). Correlation is introduced by assuming that a protein is composed of a set of independent blocks or domains and that mutation in one block affects the contribution of that block alone to the overall fitness of the protein. We study the statistical structure of such landscapes and apply our theory to the evolution by somatic hypermutation of antibody molecules composed of framework and complementarity-determining regions. We predict the expected number of replacement mutations in each region.