Solving 2D HP Protein Folding Problem by Parallel Ant Colonies

To predict protein structure based on Hydrophobic- Polar model(HP model) in two-dimensional space is called 2D HP protein folding problem. Ant Colony Optimization(ACO), which is inspired by the foraging behavior of ants, is a popular heuristic approach for solving combinatorial optimization problems. This paper presents a method of solving the 2D HP protein folding problem by parallel ACO algorithm. Each ant colony is able to search the best solution guided by the shared pheromone matrix which accumulates the good experience achieved by previous populations. The shared pheromone matrix can integrate all the search knowledge found by parallel colonies. Experimental results show that the parallel implementation performs better comparing with the other ACO solutions. Index Terms—protein folding, HP model, paralle ACO If a folding structure satisfies the three conditions, it can be considered as a legitimate configuration. We can measure the quality of a legitimate configuration by an energy function. Definition of the energy only considers the hydrophobic force. The energy of a conformation is defined as a number of topo- logical contacts between hydrophobic amino-acids which are not neighbors in the given sequence. The energy configuration is composed of all H-pairs which are adjacent in the two- dimensional space but not adjacent in the chain. Energy E of a legitimate configuration of the protein(the length of the chain is n) is formally described as follows: