Exploring the energy landscape of proteins: A characterization of the activation-relaxation technique

Abstract

Finding the global energy minimum region of a polypeptide chain, independently of the starting conformation and in a reasonable computational time, is of fundamental interest. As the energy landscape of proteins is very rugged, sampling is hindered by the vast number of minima existing on this multidimensional landscape. In this study, we use activation-relaxation technique (ART) to explore the energy landscape of a series of peptide models with 14, 26, and 28 amino acids. Peptides are modeled by a reduced off-lattice representation and a simplified OPEP-like (optimized potential for efficient peptide-structure prediction) energy model. ART defines moves directly in the energy landscape and can generate with equal efficiency events with root-mean-square deviation as small as 0.1 or as large as 4 Å. Our results show that (i) ART trajectories are reversible and provide real activated paths; (ii) ART simulations converge to the same low-energy minimum region, for a wide range of starting configurations; (iii) ART method can sample the phase space effectively, going through many hyper-basins, and can generate significant moves in a single event. Possible applications of ART method to biomolecules are discussed.