Protein Folding Implementation of Stochastic and Deterministic Algorithms using the twodimensional HP Model for Computer Simulation of the Protein Folding Process

Abstract

In nature, proteins are often found to instantly fold into the configuration with the lowest amount of free energy. Due to the complexity of this process, it is today still unknown exactly how it occurs. Since proteins have crucial roles in essentially all biological processes, this is an important problem within structural biology. Computational methods can be used to simulate the problem and a large variety of algorithms have been introduced in the field. Using a widely studied abstraction of this problem, the two-dimensional HP model, this thesis studies the following combinatorial, stochastic and deterministic algorithms: Exhaustive Search, Random Walk, Monte Carlo, Ant Colony Optimization and Zipping and Assembly by Dynamic Programming. The mechanisms, efficiency and results of these algorithms are evaluated and discussed. Even this simplified version of the problem proves to be challenging and gives interesting insights into principles of the protein folding problem.