With the development of computer technology, the more information is obtained from biological experiments through computer analysis, and even has helped give rise to a new kind of science called bioinformatics. The commonly used tool in bioinformatics is sequence alignment. Sequence alignment is a way of comparing the sequences to identify regions of similarity that may be a consequence of functional relationships between the sequences. The genetic code is highly similar among all organisms and can be expressed in a simple table with 64 entries. In this research, we uses cellular automata (CA) theory as the research topic instead of using traditional dotplot or dynamic programming to conduct sequence alignment. The parallel computing characteristic of cellular automata makes the future expansion model tremendously decrease the massive sequence computing costs. This research modifies the originally defined rules of cellular automata in order to make it more appropriate for amino acid sequence alignment.