Abstract
The protein folding problem studies the way in which a protein - a chain of amino acids - will 'fold' into its natural state. Predicting the way in which various proteins fold can be fundamental in developing treatments of diseases such as Alzeihmers and Systic Fibrosis. Classical solutions to calculating the final conformation of a protein structure are resource-intensive. The Hydrophobic-Hydrophilic (HP) method is one way of simplifying the problem. We introduce a novel method of solving the HP protein folding problem in both two and three dimensions using ant colony optimizations and a distributed programming paradigm. Tests across a small number of processors indicate that the multiple colony distributed ACO (MACO) approach is scalable and outperforms single colony implementations.
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