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

Effective hybrid approach for protein structure prediction in a two-dimensional Hydrophobic-Polar model

Hydrophobic-polar (HP) models are widely used to predict protein folding and hydrophobic interactions. Numerous optimization algorithms have been proposed to predict protein folding using the two-dimensional (2D) HP model. However, to obtain an optimal protein structure from the 2D HP model remains challenging. In this study, an algorithm integrating particle swarm optimization (PSO) and Tabu search (TS), named PSO-TS, was proposed to predict protein structures based on the 2D HP model. TS can help PSO to avoid getting trapped in a local optima and thus to remove the limitation of PSO in predicting protein folding by the 2D HP model. In this study, a total of 28 protein sequences were used to evaluate the accuracy of PSO-TS in protein folding prediction. The proposed PSO-TS method was compared with 15 other approaches for predicting short and long protein sequences. Experimental results demonstrated that PSO-TS provides a highly accurate, reproducible, and stabile prediction ability for the protein folding by the 2D HP model.

Computational Modeling of Proteins based on Cellular Automata: A Method of HP Folding Approximation

The design of a protein folding approximation algorithm is not straightforward even when a simplified model is used. The folding problem is a combinatorial problem, where approximation and heuristic algorithms are usually used to find near optimal folds of proteins primary structures. Approximation algorithms provide guarantees on the distance to the optimal solution. The folding approximation approach proposed here depends on two-dimensional cellular automata to fold proteins presented in a well-studied simplified model called the hydrophobic-hydrophilic model. Cellular automata are discrete computational models that rely on local rules to produce some overall global behavior. One-third and one-fourth approximation algorithms choose a subset of the hydrophobic amino acids to form H-H contacts. Those algorithms start with finding a point to fold the protein sequence into two sides where one side ignores H's at even positions and the other side ignores H's at odd positions. In addition, blocks or groups of amino acids fold the same way according to a predefined normal form. We intend to improve approximation algorithms by considering all hydrophobic amino acids and folding based on the local neighborhood instead of using normal forms. The CA does not assume a fixed folding point. The proposed approach guarantees one half approximation minus the H-H endpoints. This lower bound guaranteed applies to short sequences only. This is proved as the core and the folds of the protein will have two identical sides for all short sequences.