A fast conformational search strategy for finding low energy structures of model proteins

We calculate thermodynamic quantities of HP lattice proteins by means of a multicanonical chain growth algorithm that connects the new variants of the Pruned-Enriched Rosenbluth Method (nPERM) and flat histogram sampling of the entire energy space. Since our method directly simulates the density of states, we obtain results for thermodynamic quantities of the system for all temperatures. In particular, this algorithm enables us to accurately simulate the usually difficult accessible low-temperature region. Therefore, it becomes possible to perform detailed analyses of the low-temperature transition between ground states and compact globules.

Section: A Lattice Model For Parallel β Helix With 42 Monomerssupporting

confidence: 90%

Thermodynamics of lattice heteropolymers

Bachmann

Janke

2004

“…11͒ and nPERMh ͑Ref. 12͒ ͑two Rosenbluth type chaingrowth-based methods͒, the core-guided ͑CG͒ search, 13 and ant colony optimization ͑ACO͒. 14 As shown in Table I, FRESS found the minimum energies for all ten sequences in less than 1 min on average.…”

Section: A Folding Hp Sequencesmentioning

confidence: 97%

Biopolymer structure simulation and optimization via fragment regrowth Monte Carlo

Zhang

Kou

2007

An efficient exploration of the configuration space of a biopolymer is essential for its structure modeling and prediction. In this study, the authors propose a new Monte Carlo method, fragment regrowth via energy-guided sequential sampling ͑FRESS͒, which incorporates the idea of multigrid Monte Carlo into the framework of configurational-bias Monte Carlo and is suitable for chain polymer simulations. As a by-product, the authors also found a novel extension of the Metropolis Monte Carlo framework applicable to all Monte Carlo computations. They tested FRESS on hydrophobic-hydrophilic ͑HP͒ protein folding models in both two and three dimensions. For the benchmark sequences, FRESS not only found all the minimum energies obtained by previous studies with substantially less computation time but also found new lower energies for all the three-dimensional HP models with sequence length longer than 80 residues.

“…Therefore, sophisticated algorithms were applied to find lowest energy states for chains of up to 136 monomers. The methods applied are based on very different algorithms, ranging from exact enumeration in two dimensions [9,10] and three dimensions on cuboid (compact) lattices [2,11], and hydrophobic core construction methods [12,13] over genetic algorithms [14,15,16,17,18], Monte Carlo simulations with different types of move sets [19,20,21,22], and generalized ensemble approaches [23] to Rosenbluth chain growth methods [24] of the 'Go with the Winners' type [25,26,27,28,29,30]. With some of these algorithms, thermodynamic quantities of lattice heteropolymers were studied as well [23,27,29,30,31].…”

Section: Introductionmentioning

confidence: 99%

Exact sequence analysis for three-dimensional hydrophobic-polar lattice proteins

Schiemann

Bachmann

Janke

2005

We have exactly enumerated all sequences and conformations of HP proteins with chains of up to 19 monomers on the simple cubic lattice. For two variants of the hydrophobic-polar (HP) model, where only two types of monomers are distinguished, we determined and statistically analyzed designing sequences, i.e., sequences that have a non-degenerate ground state. Furthermore we were interested in characteristic thermodynamic properties of HP proteins with designing sequences. In order to be able to perform these exact studies, we applied an efficient enumeration method based on contact sets.