The recently proposed statistical temperature molecular dynamics ͑STMD͒ algorithm ͓Kim et al., Phys. Rev. Lett. 97, 050601 ͑2006͔͒ is used as the core of an optimization algorithm, statistical temperature annealing ͑STA͒, for finding low-lying energy minima of complex potential energy landscapes. Since STMD realizes a random walk in energy, the idea is simply to initiate repeated minimizations from configurations in the low-energy segments of STMD trajectories. STA is tested in structural optimization of various off-lattice AB and extended AB protein models in two and three dimensions with different chain lengths. New putative ground states were found for the two-and three-dimensional AB 55-mer, and for the three-dimensional extended AB 21-mer and 55-mer. The distinct folding features of the models are analyzed in terms of the statistical temperature and other representations of the structure of the potential energy landscape. It is shown that the characteristic behavior of the statistical temperature undergoes a qualitative change with the inclusion of a torsional potential in the extended AB model, as the more rigid backbone makes the potential energy landscape more funnel-like.
The statistical temperature molecular dynamics based algorithm "statistical temperature annealing" was applied to an AB model in REF .
Structure optimization and folding mechanisms of off-lattice protein models using statistical temperature molecular dynamics simulation: Statistical temperature annealing
Physical review. E, Statistical, nonlinear, and soft matter physics
Physical review. E, Statistical, nonlinear, and soft matter physics
Physics Medicine