Partial unfolding and refolding for structure refinement: A unified approach of geometric simulations and molecular dynamics

Abstract

The most successful protein structure prediction methods to date have been template-based modeling (TBM) or homology modeling, which predicts protein structure based on experimental structures. These high accuracy predictions sometimes retain structural errors due to incorrect templates or a lack of accurate templates in the case of low sequence similarity, making these structures inadequate in drug-design studies or molecular dynamics simulations. We have developed a new physics based approach to the protein refinement problem by mimicking the mechanism of chaperons that rehabilitate misfolded proteins. The template structure is unfolded by selectively (targeted) pulling on different portions of the protein using the geometric based technique FRODA, and then refolded using hierarchically restrained replica exchange molecular dynamics simulations (hr-REMD). FRODA unfolding is used to create a diverse set of topologies for surveying near native-like structures from a template and to provide a set of persistent contacts to be employed during re-folding. We have tested our approach on 13 previous CASP targets and observed that this method of folding an ensemble of partially unfolded structures, through the hierarchical addition of contact restraints (that is, first local and then nonlocal interactions), leads to a refolding of the structure along with refinement in most cases (12/13). Although this approach yields refined models through advancement in sampling, the task of blind selection of the best refined models still needs to be solved. Overall, the method can be useful for improved sampling for low resolution models where certain of the portions of the structure are incorrectly modeled.

Keywords: CASP; molecular dynamics; protein folding; protein model refinement; replica exchange.

Figure 1

Flowchart of refinement protocol. Refinement begins with geometric unfolding, followed by seed structures and contact list generation, hr-REMD and finishing with the clustering of the simulation trajectories.

Figure 2

Overlay of native structure (PDB code: 4FCZ), CASP model structure TR661 and refined structure in wheat, blue and yellow aligned using PyMol. Left side shows large improvement in terminal helix from the model structure along with misalignments of other regions. Right side shows improvements of misaligned regions with iterative hr-REMD simulations.

Figure 3

Improvements for starting models with an RMSD of 4 Å or greater. Left side shows starting model in green, right side shows refined structure colored by root mean square fluctuations. All structures superimposed onto the native (wheat) using PyMOL. PDB codes of native structure, top to bottom: 4FTD, 2KYY, 3N6Y, 3NRL.

Figure 4

Two of our failed cases for refinement with starting models in green, refined structures colored by R.M.S, fluctuations and native structures in wheat aligned using PyMol. TR689 (Native PDB code: 4FVS) had an extremely low starting RMSD making further refinement challenging. TR754 (Native PDB code: 2LV9) contains zinc ions, an interaction that our methodology is unable to capture. TR754 was a particular challenge for all CASP 9 participants.

Figure 5

Comparison of RMSD as a function of simulation time between standard REMD (a) and hr-REMD (b) for CASP model structure T0311 (best predicted structure). hr-REMD shows a faster convergence to a lower RMSD over traditional REMD

Figure 6

Distribution of clustered structures after three different approaches using REMD for starting model TR557. All structures under 4.06 Å RMSD (i.e. original RMSD of the target) are improved. Traditional REMD is in pink (a), REMD with restraints added hierarchically in yellow (b) and hr-REMD in blue (c). Best models of each method superimposed on native structure (PDB code: 2KYY) in wheat.

Figure 7

Boxplot of RMSD to starting model vs. RMSD to native conformation of refined structures. Generally, structures that have not changed significantly from the starting model will be lower in RMSD to the experimental structure, but only to an approximation.

Figure 8

Boxplot of DFIRE values vs. RMSD to native conformation of refined structures. Lower DFIRE generally indicates a more stable model, likely closer to the native conformation, but this trend is not constant amongst all proteins.