Protein Folding In The Two-Dimensional Hydrophobic Polar Model Based On Cellular Automata And Local Rules

Cellular Automata are discrete computational models that rely on local rules. The main focus of this paper is to build a model of proteins based on simple and local rules of a cellular automaton. Research in this direction depend mainly on combining cellular automata with other paradigms. Many schemes in literature rely on different evolutionary algorithms to support the use of cellular automata and some depend on combining protein parameters with parameters extracted from a cellular automaton image. The aim here is to keep the simplicity of cellular automata as much as possible. It is not known yet if a set of local rules that can solve the protein folding problem does exist. So far, research depend on some sort of searching or a global view of the sequence in order to find a reasonable confirmation. This paper discusses what simple rules can be like. The proposed cellular automaton rules and states depend on a well-known simple exact model and the basic principles governing protein folding. In the proposed cellular automaton, the cell state can be a hydrophobic amino acid, a polar amino acid, an empty cell, or a control cell. The argument of local rules is supported by graphical examples of applying the proposed rules.