Progress in Artificial Intelligence

, Volume 7, Issue 3, pp 225–235 | Cite as

Application of local rules and cellular automata in representing protein translation and enhancing protein folding approximation

  • Alia Madain
  • Abdel Latif Abu Dalhoum
  • Azzam Sleit
Regular Paper


It is self-evident that the coarse-grained view of transcription and protein translation is a result of certain computations. Although there is no single definition of the term “computation,” protein translation can be implemented over mathematical models of computers. Protein folding, however, is a combinatorial problem; it is still unknown whether a fast, accurate, and optimal folding algorithm exists. The discovery of near-optimal folds depends on approximation algorithms and heuristic searches. The hydrophobic–hydrophilic (HP) model is a simplified representation of some of the realities of protein structure. Despite the simplified representation, the folding problem in the HP model was proven to be NP-complete. We use simple and local rules to model translation and folding of proteins. Local rules imply that at a certain level of abstraction an entity can move from a state to another based on its state and information collected from its neighborhood. Also, the rules are simple in a sense that they do not require complicated computation. We use one-dimensional cellular automata to describe translation of mRNA into protein. Cellular automata are discrete models of computation that use local interactions to produce a global behavior of some sort. We will also discuss how local rules can improve approximation algorithms of protein folding and give an example of a CA that accept a certain family of strings to achieve half H–H contacts.


Protein translation Protein folding Cellular automata HP model 



We would like to thank Dr. Khair Eddin Sabri, Dr. Loai Alnemer, and Dr. Rawan Ghnemat for their suggestions and comments that greatly improved the content of this manuscript.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Alia Madain
    • 1
  • Abdel Latif Abu Dalhoum
    • 1
  • Azzam Sleit
    • 1
  1. 1.Department of Computer Science, King Abdulla II School for Information TechnologyThe University of JordanAmmanJordan

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