Parallel Simple GAs vs Parallel Fast Messy GAs for Protein Structure Prediction

We apply the parallel SGA and parallel fmGA to the minimization of an empirical energy model of the pentapeptide Met Enkephalin Figure We choose Met enkephalin for two reasons First previous re search e orts have investigated the use of various op timization techniques for the prediction of its tertiary structure via energy minimization Second the native conformation is known and its energy has been calculated using several well known empirical energy models kcal mol using the ECEPP model and kcal mol using QUANTA The dihedral angles in particular the and dihedral angles of Met Enkephalin labeled in Fig ure determine the three dimensional structure of peptides Thus these angles are taken to be the inde pendent variables both in the previous studies and in the present investigation We compare the performance of the parallel SGA and parallel fmGA with regard to several criteria The speci c quantitative comparisons include