Molecular simulations have been widely used in biomolecular systems such as proteins, DNA, etc. The search for stable conformations of proteins by molecular simulations is important to understand the function and stability of proteins. However, finding the stable state by conformational search is difficult, because the energy landscape of the system is characterized by many local minima separated by high energy barriers. In order to overcome this difficulty, various sampling and optimization methods for the conformation of proteins have been proposed. In this study, we propose a new conformational search method for proteins based on a genetic algorithm. We applied this method to an α-helical protein. We found that the conformations obtained from our simulations are in good agreement with the experimental results.