A study of RNA secondary structure prediction using different mutation operators

Ribonucleic Acid (RNA) has important structural and functional roles in the cell and plays roles in many stages of protein synthesis as well. The functions of RNA molecules are determined largely by their three-dimensional structure. SARNA-Predict has shown excellent results in predicting RNA secondary structure based on Simulated Annealing (SA). SARNA-Predict uses a permutation-based representation to the RNA secondary structure and this paper investigates the impact of the mutation operators in this algorithm. Experiments were performed using a sample of eleven sequences from four RNA classes. The results presented in this paper demonstrate that SARNA-Predict using the percentage swap translocating mutation operator can produce similar results when compared with previous research. Furthermore, the new operator has the potential of reaching a solution with a lower free energy. This supports the use of the proposed operator on RNA secondary structure prediction of other known structures.