title: Growth algorithm for finding low energy configurations of simple lattice proteins.
abstract: PERM and its new variant nPERMis have been developed to optimize the energy function of protein folding based on HP simple lattice model and were found to outperform all other previous fully blind general purpose algorithms. Using the concept of core-guiding and life-forecasting, we propose a new version of nPERMis, called nPERMh. A major difference with respect to nPERMis is that criteria for further growth of new residue are based on the species of current growing monomer and its position in the HP sequence. Seventeen sequences of length ranging from 46 to 124 residues were tested by nPERMh on the cubic lattice and our algorithm proved very efficient. It should be pointed out that our new version of nPERMis is exclusively designed for conformational search. We hope that similar methods will ultimately be useful for finding native states of more realistic protein models.
authors.affiliation: School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430074, China.
authors.forename: Wenqi
authors.initials: W
authors.lastname: Huang
authors.forename: Zhipeng
authors.initials: Z
authors.lastname: Lü
authors.forename: He
authors.initials: H
authors.lastname: Shi