A Self-adaptive Differential Evolution with Fragment Insertion for the Protein Structure Prediction Problem

摘要

This work presents four hybrid methods based on the Self-adaptive Differential Evolution algorithm with fragment insertion applied to the protein structure prediction problem. The protein representation is the backbone torsion angles with side chain centroid coordinates. The fragment insertion is made by the Monte Carlo algorithm. The hybrid methods were compared with recent and compatible methods from the literature, where two proposed approaches achieved competitive results. The results have shown that using parameter control and fragment insertion greatly improves the results of the prediction when compared to fragment-less methods or without parameter control. Furthermore, an extra analysis was conducted using GDT-TS and TM-Score metrics to better understand the results obtained.