Protein Tertiary Structure Prediction Using Artificial Bee Colony Algorithm

Protein Tertiary Structure Prediction Using Artificial Bee Colony Algorithm

ABSTRACT

Proteins are essential for the biological processes in the human body. They can only perform their functions when they fold into their tertiary structure. Protein structure can be determined experimentally and computationally. Experimental methods are time consuming and high-priced and it is not always feasible to identify the protein structure experimentally. In order to predict the protein structure using computational methods, the problem is formulated as an optimization problem and the goal is to find the lowest free energy conformation. In this paper, artificial bee colony algorithm (ABC) is a swarm intelligence based optimization algorithm inspired by the behaviour of honey bee foraging. This algorithm is adapted to search the protein conformational search space to find the lowest free energy conformation. Interestingly, the algorithm was able to find the lowest free energy conformation for a test protein (i.e. Met enkephaline) using ECEPP/2 force fields