An improved hybrid global optimization method for protein tertiary structure prediction.

ABSTRACT: First principles approaches to the protein structure prediction problem must search through an enormous conformational space to identify low-energy, near-native structures. In this paper, we describe the formulation of the tertiary structure prediction problem as a nonlinear constrained minimization problem, where the goal is to minimize the energy of a protein conformation subject to constraints on torsion angles and interatomic distances. The core of the proposed algorithm is a hybrid global optimization method that combines the benefits of the αBB deterministic global optimization approach with conformational space annealing. These global optimization techniques employ a local minimization strategy that combines torsion angle dynamics and rotamer optimization to identify and improve the

SUBMITTER: McAllister SR 

PROVIDER: S-EPMC2847311 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature