Hybrid Genetic Algorithm for Protein Folding Simulations in the 2D HP model

Katherina von Carlowitz

The prediction of a protein’s structure from its amino-acid sequence is one of the most important problems in computational molecular biology. In this thesis, we demonstrate a hybrid genetic algorithm that simulates protein folding under the widely studied 2-dimensional hydrophobic- hydrophilic (HP) lattice model. The protein folding problem in the HP model is to find a lowest energy conformation, which is known to be a NP-hard combinatorial problem. In comparison to similar algorithms, our algorithms performed well on standard benchmark instances. In addition, we present a graphical version of the genetic algorithm that uses secondary structures in protein folding.