Improving an all-atom force field

Free-energy-driven folding and thermodynamics of the 67-residue protein GS-alpha3W--a large-scale Monte Carlo study

Utilizing the computational power of a few thousand processors on a BlueGene/P, we have explored the folding mechanism of the 67-residue protein GS-alpha(3)W. Results from our large-scale simulation indicate a diffusion-collision mechanism for folding. However, the lower-than-expected frequency of native-like configurations at physiological temperatures indicates shortcomings of our energy function. Our results suggest that computational studies of large proteins call for redevelopment and reparametrization of force fields that in turn require extensive simulations only possible with the newly available supercomputers with computing powers reaching the petaflop range.

Caching of a chameleon segment facilitates folding of a protein with end-to-end beta-sheet

We report results from all-atom simulations of a 49-residue C-terminal fragment of TOP7 in implicit solvent. Using parallel tempering simulations with high statistics, we probe the thermodynamic properties of the protein over a large range of temperatures and evaluate its free energy landscape at room temperature. Our results confirm that the protein folds by a caching mechanism that relies on a chameleon segment. This mechanism differs from the one seen in high-temperature unfolding simulations. Finally, we discuss a possible mechanism for dimerization of the protein.

Use of decoys to optimize an all-atom force field including hydration

A novel method of parameter optimization is proposed. It makes use of large sets of decoys generated for six nonhomologous proteins with different architecture. Parameter optimization is achieved by creating a free energy gap between sets of nativelike and nonnative conformations. The method is applied to optimize the parameters of a physics-based scoring function consisting of the all-atom ECEPP05 force field coupled with an implicit solvent model (a solvent-accessible surface area model). The optimized force field is able to discriminate near-native from nonnative conformations of the six training proteins when used either for local energy minimization or for short Monte Carlo simulated annealing runs after local energy minimization. The resulting force field is validated with an independent set of six nonhomologous proteins, and appears to be transferable to proteins not included in the optimization; i.e., for five out of the six test proteins, decoys with 1.7- to 4.0-A all-heavy-atom root mean-square deviations emerge as those with the lowest energy. In addition, we examined the set of misfolded structures created by Park and Levitt using a four-state reduced model. The results from these additional calculations confirm the good discriminative ability of the optimized force field obtained with our decoy sets.

Folding pathways and rates for the three-stranded beta-sheet peptide Beta3s using discrete path sampling

The discrete path sampling method was used to investigate the folding of a three-stranded antiparallel beta-sheet peptide, Beta3s, described by an empirical potential and implicit solvent model. After application of a coarse-graining scheme that groups together sets of minima in local equilibrium, the calculated folding time was in reasonable agreement with other simulations and consistent with the experimental upper bound. The folding mechanism exhibited by the most significant discrete paths involves early formation of the C-terminal hairpin followed by docking of the N-terminal strand.

Simulation of Top7-CFr: a transient helix extension guides folding

Protein structures often feature beta-sheets in which adjacent beta-strands have large sequence separation. How the folding process orchestrates the formation and correct arrangement of these strands is not comprehensively understood. Particularly challenging are proteins in which beta-strands at the N and C termini are neighbors in a beta-sheet. The N-terminal beta-strand is synthesized early on, but it can not bind to the C terminus before the chain is fully synthesized. During this time, there is a danger that the beta-strand at the N terminus interacts with nearby molecules, leading to potentially harmful aggregates of incompletely folded proteins. Simulations of the C-terminal fragment of Top7 show that this risk of misfolding and aggregation can be avoided by a "caching" mechanism that relies on the "chameleon" behavior of certain segments.

Understanding protein folding: small proteins in silico

Recent improvements in methodology and increased computer power now allow atomistic computer simulations of protein folding. We briefly review several advanced Monte Carlo algorithms that have contributed to this development. Details of folding simulations of three designed mini proteins are shown. Adding global translations and rotations has allowed us to handle multiple chains and to simulate the aggregation of six beta-amyloid fragments. In a different line of research we have developed several algorithms to predict local features from sequence. In an outlook we sketch how such biasing could extend the application spectrum of Monte Carlo simulations to structure prediction of larger proteins.