Fitness Landscape of a Biopolymer Participating in a Multi-step Reaction

Abstract A biopolymer such as an enzyme participates in a multi-step reaction. When we take such a biopolymer as a target of evolutionary molecular engineering, the problem of frustration or interference among partial-fitness landscapes for elementary reaction steps arises. We examined the effect of the frustration on a fitness landscape for the whole reaction. From the results of a previous paper we assumed that each partial-fitness landscape is of the Mt. Fuji-type, based on the mutational additivity. Computer simulation for two-step or three-step reactions showed that the fitness landscape for a whole reaction was of the rough Mt. Fuji-type, in which optima were located near the top. However, there were fitter double-point mutants around each local optimum. This conclusion was supported by the result of the mathematical analysis of a simplified landscape for an L -step reaction: even if there are local optima on the fitness landscape, several fitter sequences exist at the Hamming distance of L from every local optimum in almost all cases. Fitness distributions around the global optimum also showed that the fitness landscape can be approximated to a Mt. Fuji-type landscape.