Ab initio folding simulation of the Trp-cage mini-protein approaches NMR resolution.

Here, we report a 100 ns molecular dynamics simulation of the folding process of a recently designed autonomous-folding mini-protein designated as tc5b with a new AMBER force field parameter set developed based on condensed-phase quantum mechanical calculations and a Generalized Born continuum solvent model. Starting from its fully extended conformation, our simulation has produced a final structure resembling that of NMR native structure to within 1A main-chain root mean square deviation. Remarkably, the simulated structure stayed in the native state for most part of the simulation after it reached the state. Of greater significance is that our simulation has not only reached the correct main-chain conformation, but also a very high degree of accuracy in side-chain packing conformation. This feat has traditionally been a challenge for ab initio simulation studies. In addition to characterization of the trajectory, comparison of our results to experimental data is also presented. Analysis of the trajectory suggests that the rate-limiting step of folding of this mini-protein is the packing of the Trp side-chain.

Distinguish protein decoys by using a scoring function based on a new AMBER force field, short molecular dynamics simulations, and the generalized born solvent model.

Recent works have shown the ability of physics-based potentials (e.g., CHARMM and OPLS-AA) and energy minimization to differentiate the native protein structures from large ensemble of non-native structures. In this study, we extended previous work by other authors and developed an energy scoring function using a new set of AMBER parameters (also recently developed in our laboratory) in conjunction with molecular dynamics and the Generalized Born solvent model. We evaluated the performance of our new scoring function by examining its ability to distinguish between the native and decoy protein structures. Here we present a systematic comparison of our results with those obtained with use of other physics-based potentials by previous authors. A total of 7 decoy sets, 117 protein sequences, and more than 41,000 structures were evaluated. The results of our study showed that our new scoring function represents a significant improvement over previously published physics-based scoring functions.

A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations.

Molecular mechanics models have been applied extensively to study the dynamics of proteins and nucleic acids. Here we report the development of a third-generation point-charge all-atom force field for proteins. Following the earlier approach of Cornell et al., the charge set was obtained by fitting to the electrostatic potentials of dipeptides calculated using B3LYP/cc-pVTZ//HF/6-31G** quantum mechanical methods. The main-chain torsion parameters were obtained by fitting to the energy profiles of Ace-Ala-Nme and Ace-Gly-Nme di-peptides calculated using MP2/cc-pVTZ//HF/6-31G** quantum mechanical methods. All other parameters were taken from the existing AMBER data base. The major departure from previous force fields is that all quantum mechanical calculations were done in the condensed phase with continuum solvent models and an effective dielectric constant of epsilon = 4. We anticipate that this force field parameter set will address certain critical short comings of previous force fields in condensed-phase simulations of proteins. Initial tests on peptides demonstrated a high-degree of similarity between the calculated and the statistically measured Ramanchandran maps for both Ace-Gly-Nme and Ace-Ala-Nme di-peptides. Some highlights of our results include (1) well-preserved balance between the extended and helical region distributions, and (2) favorable type-II poly-proline helical region in agreement with recent experiments. Backward compatibility between the new and Cornell et al. charge sets, as judged by overall agreement between dipole moments, allows a smooth transition to the new force field in the area of ligand-binding calculations. Test simulations on a large set of proteins are also discussed.