Structure optimization in an off-lattice protein model
arXiv:cond-mat/0302545 · doi:10.1103/PhysRevE.68.037703
Abstract
We study an off-lattice protein toy model with two species of monomers interacting through modified Lennard-Jones interactions. Low energy configurations are optimized using the pruned-enriched-Rosenbluth method (PERM), hitherto employed to native state searches only for off lattice models. For 2 dimensions we found states with lower energy than previously proposed putative ground states, for all chain lengths . This indicates that PERM has the potential to produce native states also for more realistic protein models. For , where no published ground states exist, we present some putative lowest energy states for future comparison with other methods.
4 pages, 2 figures
References in corpus (8)
- Growth Algorithms for Lattice Heteropolymers at Low Temperatures
- Studies of an Off-Lattice Model for Protein Folding: Sequence Dependence and Improved Sampling at Finite Temperature
- Local Interactions and Protein Folding: A 3D Off-Lattice Approach
- Go with the Winners: a General Monte Carlo Strategy
- Multi-Self-Overlap Ensemble for protein folding: ground state search and thermodynamics
- A New Monte Carlo Algorithm for Protein Folding
- A Growth-based Optimization Algorithm for Lattice Heteropolymers
- Identification of Amino Acid Sequences with Good Folding Properties in an Off-Lattice Model
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