ACO-METAHEURISTIC FOR 3D-HP PROTEIN FOLDING OPTIMIZATION

Protein Folding is a broad research field in computational Biology, Molecular Biology and Bioinformatics. Protein Folding Optimization is one of the NP-hard problems. Bio-inspired metaheuristics plays a major role in solving the protein folding optimization which can mimic the insect's problem solving abilities like foraging, nest building and mating. In this paper Ant Colony Optimization (ACO) - Metaheuristic was applied to solve 3D-HP protein folding optimization. The 3D structure of a protein is also called as final native structure, which is responsible for functioning of a particular protein. Misfolded or unfolded protein is responsible for several neurodegenerative diseases. The instances for 3D-HP protein folding were taken from the HP benchmarks. The energy minimization is the major objective function to obtain the best 3D structure of protein. Various energy functions are used in this work to obtain different energy values.