Protein Stucture Prediction using Bee Colony Optimization – Københavns Universitet

Protein Stucture Prediction using Bee Colony Optimization

Protein Stucture Prediction using Bee Colony Optimization

Predicting the native structure of proteins is one of the most challening problems in computational biology. The goal is to determine the three-dimensional structure from the one-dimensional amino acid sequence. De novo prediction algorithms seek to do this by developing a representation of the proteins structure, an energy potential and some optimization algorithm that finds the structure with minimal energy.

Bee Colony Optimization is a new metaheuristic approach to optimization based on the foraging behaviour of bees. The method is a very simple swarm-algorithm that can easily be expanded or be used to prioritize parallel runs of local search methods. We have implemented the Bee Colony
Optimization metaheuristic using hill-climbing as local search to solve the protein structure prediction problem. The results show that Bee Colony Optimization generally finds better solutions than simulated annealing in the same amount of time.