Conformational space annealing and a lattice model protein

Abstract

The conformational space annealing (CSA) method is a powerful global optimization method for sampling low-lying local minimum energy conformations of a physical system. In this work, I apply CSA to the study of a two-dimensional HP lattice model of a protein, where a conformation is defined as a self-avoiding chain on a lattice. I study the 36-residue chain with a particular sequence HPH2P2H2P3H2PHP3H2P2H2P4HPH2PHP2 presented by Li et al., for which by exhaustive enumeration of compact conformations, only one such conformation with the lowest energy was shown to exist. The CSA algorithm finds conformations with energies lower than those found by Li et al. for 100 independent runs, demonstrating that the global minimum energy conformation is not necessarily the most compact structure.