Analysis of toy model for protein folding based on particle swarm optimization algorithm

Abstract

One of the main problems of computational approaches to protein structure prediction is the computational complexity. Many researches use simplified models to represent protein structure. Toy model is one of the simplification models. Finding the ground state is critical to the toy model of protein. This paper applies Particle Swarm Optimization (PSO) Algorithm to search the ground state of toy model for protein folding, and performs experiments both on artificial data and real protein data to evaluate the PSO-based method. The results show that on one hand, the PSO method is feasible and effective to search for ground state of toy model; on the other hand, toy model just can simulate real protein to some extent, and need further improvements. © Springer-Verlag Berlin Heidelberg 2005.