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Evolution can be broadly described in terms of mutations of the genotype andthe subsequent selection of the phenotype. The full enumeration of a givengenotype-phenotype (GP) map is therefore a powerful technique in examiningevolutionary landscapes. However, because the number of genotypes typicallygrows exponentially with genome length, such calculations rapidly becomeintractable. Here I apply graphics processing unit(GPU) techniques to thehydrophobic-polar (HP)model for protein folding. This GP map is a simple andwell-studied model for the complex process of protein folding. Prior studies onrelatively small 2D and 3D lattices have been exclusively carried out usingconventional central processing unit (CPU) approaches. By using GPU techniques,I was able to reproduce the pioneering calculations of Li et al.[1] with aspeed up of 580-700 fold over a CPU. I was also able to perform the largestenumeration to date of the 6x6 lattice. These novel calculations provideevidence that a popular "plum-pudding" metaphor that suggests that phenotypesare disconnected in genotype space does not describe the data. Instead a"spaghetti" metaphor of connected genotype networks may be more suitable.Furthermore, the data allows the relationships between designability andcomplexity within GP space to be explored. GPU approaches appear extremely wellsuited toGP mapping and the success of this work provides a promisingintroduction for its wider application in this field.

GPU accelerated enumeration and exploration of HP model genotype-phenotype maps for protein folding