Structure formation of biopolymers is complex, their evolution may be simple.

Evolutionary strategies depend on the ability of evolving entities to conserve acquired features and to quickly adapt to new requirements as well. We use computer simulations of simplified exact biopolymers models to investigate the influence of mutations on structure formation. Our computations on large ensembles of random RNA secondary structures show that the sequence to structure mapping is ideally suited for evolutionary optimisation under point mutations: from any random structure it is not far to any target and yet most mutations will preserve the structure. The aim of this paper is to discuss the analogies as well as some recently developed methods to apply our approach to proteins: there we use Dill's HP - model of lattice proteins and apply a novel fast and efficient folding rule. There are remarkable similarities as both landscapes are rugged and structure formation largely depends on local interactions such that it is possible to accomplish a characterisation of the mapping similar to the RNA case.