Princeton_TIGRESS: Protein geometry refinement using simulations and support vector machines

Protein structure refinement aims to perform a set of operations given a predicted structure to improve model quality and accuracy with respect to the native in a blind fashion. Despite the numerous computational approaches to the protein refinement problem reported in the previous three CASPs, an overwhelming majority of methods degrade models rather than improve them. We initially developed a method tested using blind predictions during CASP10 which was officially ranked in 5th place among all methods in the refinement category. Here, we present Princeton_TIGRESS, which when benchmarked on all CASP 7,8,9, and 10 refinement targets, simultaneously increased GDT_TS 76% of the time with an average improvement of 0.83 GDT_TS points per structure. The method was additionally benchmarked on models produced by top performing three‐dimensional structure prediction servers during CASP10. The robustness of the Princeton_TIGRESS protocol was also tested for different random seeds. We make the Princeton_TIGRESS refinement protocol freely available as a web server at http://atlas.princeton.edu/refinement . Using this protocol, one can consistently refine a prediction to help bridge the gap between a predicted structure and the actual native structure. Proteins 2014; 82:794–814. © 2013 Wiley Periodicals, Inc.     

ZRANK: reranking protein docking predictions with an optimized energy function

Protein-protein docking requires fast and effective methods to quickly discriminate correct from incorrect predictions generated by initial-stage docking. We have developed and tested a scoring function that utilizes detailed electrostatics, van der Waals, and desolvation to rescore initial-stage docking predictions. Weights for the scoring terms were optimized for a set of test cases, and this optimized function was then tested on an independent set of nonredundant cases. This program, named ZRANK, is shown to significantly improve the success rate over the initial ZDOCK rankings across a large benchmark. The amount of test cases with No. 1 ranked hits increased from 2 to 11 and from 6 to 12 when predictions from two ZDOCK versions were considered. ZRANK can be applied either as a refinement protocol in itself or as a preprocessing stage to enrich the well-ranked hits prior to further refinement.     

Comparison of NMR and crystal structures of membrane proteins and computational refinement to improve model quality

Membrane proteins are challenging to study and restraints for structure determination are typically sparse or of low resolution because the membrane environment that surrounds them leads to a variety of experimental challenges. When membrane protein structures are determined by different techniques in different environments, a natural question is “which structure is most biologically relevant?” Towards answering this question, we compiled a dataset of membrane proteins with known structures determined by both solution NMR and X‐ray crystallography. By investigating differences between the structures, we found that RMSDs between crystal and NMR structures are below 5 Å in the membrane region, NMR ensembles have a higher convergence in the membrane region, crystal structures typically have a straighter transmembrane region, have higher stereo‐chemical correctness, and are more tightly packed. After quantifying these differences, we used high‐resolution refinement of the NMR structures to mitigate them, which paves the way for identifying and improving the structural quality of membrane proteins.     

The crystal structure of the ternary complex of staphylococcal nuclease, Ca2+, and the inhibitor pdTp, refined at 1.65 A

The structure of a complex of staphylococcal nuclease with Ca2+ and deoxythymidine 3',5'-bisphosphate (pdTp) has been refined by stereochemically restrained least-squares minimization to a crystallographic R value of 0.161 at 1.65 A resolution. The estimated root-mean-square (rms) error in the coordinates is 0.16 A. The final model comprises 1082 protein atoms, one calcium ion, the pdTp molecule, and 82 solvent water molecules; it displays an rms deviation from ideality of 0.017 A for bond distances and 1.8 degrees for bond angles. The mean distance between corresponding alpha carbons in the refined and unrefined structures is 0.6 A; we observe small but significant differences between the refined and unrefined models in the turn between residues 27 and 30, the loop between residues 44 and 50, the first helix, and the extended strand between residues 112 and 117 which forms part of the active site binding pocket. The details of the calcium liganding and solvent structure in the active site are clearly shown in the final electron density map. The structure of the catalytic site is consistent with the mechanism that has been proposed for this enzyme. However, we note that two lysines from a symmetry-related molecule in the crystal lattice may play an important role in determining the geometry of inhibitor binding, and that only one of the two required calcium ions is observed in the crystal structure; thus, caution is advised in extrapolating from the structure of the complex of enzyme and inhibitor to that of enzyme and substrate.     

Refinement of protein-protein complexes in contact map space with metadynamics simulations

Accurate protein-protein complex prediction, to atomic detail, is a challenging problem. For flexible docking cases, current state-of-the-art docking methods are limited in their ability to exhaustively search the high dimensionality of the problem space. In this study, to obtain more accurate models, an investigation into the local optimization of initial docked solutions is presented with respect to a reference crystal structure. We show how physics-based refinement of protein-protein complexes in contact map space (CMS), within a metadynamics protocol, can be performed. The method uses 5 times replicated 10 ns simulations for sampling and ranks the generated conformational snapshots with ZRANK to identify an ensemble of n snapshots for final model building. Furthermore, we investigated whether the reconstructed free energy surface (FES), or a combination of both FES and ZRANK, referred to as CS_α, can help to reduce snapshot ranking error.     

X-ray studies of water structure in 2 Zn insulin crystal

The water structure of rhombohedral 2 Zn insulin crystal which contains about 280 water molecules and 0.55-0.60 mol citrate molecules per dimer has been studied by X-ray crystallographic refinement with 1.1 A resolution data. Atomic parameters of 83 fully occupied and 258 partially occupied water molecules and 0.3 mol of citrate were obtained. Full matrix least-squares method with isotropic temperature factor was used for the refinement of partially occupied water molecules. The water molecules in this crystal exist in one of the three states: fully occupied water, partially occupied water and water continuum, and a schematic model of water structure in protein crystal was proposed. The flexibility of water molecules is described.     

Evaluation of model refinement in CASP13

Performance in the model refinement category of the 13th round of Critical Assessment of Structure Prediction (CASP13) is assessed, showing that some groups consistently improve most starting models whereas the majority of participants continue to degrade the starting model on average. Using the ranking formula developed for CASP12, it is shown that only 7 of 32 groups perform better than a “naïve predictor” who just submits the starting model. Common features in their approaches include a dependence on physics-based force fields to judge alternative conformations and the use of molecular dynamics to relax models to local minima, usually with some restraints to prevent excessively large movements. In addition to the traditional CASP metrics that focus largely on the quality of the overall fold, alternative metrics are evaluated, including comparisons of the main-chain and side-chain torsion angles, and the utility of the models for solving crystal structures by the molecular replacement method. It is proposed that the introduction of these metrics, as well as consideration of the accuracy of coordinate error estimates, would improve the discrimination between good and very good models.     

Prediction of protein oligomer structures using GALAXY in CASP13

Many proteins need to form oligomers to be functional, so oligomer structures provide important clues to biological roles of proteins. Prediction of oligomer structures therefore can be a useful tool in the absence of experimentally resolved structures. In this article, we describe the server and human methods that we used to predict oligomer structures in the CASP13 experiment. Performances of the methods on the 42 CASP13 oligomer targets consisting of 30 homo-oligomers and 12 hetero-oligomers are discussed. Our server method, Seok-assembly, generated models with interface contact similarity measure greater than 0.2 as model 1 for 11 homo-oligomer targets when proper templates existed in the database. Model refinement methods such as loop modeling and molecular dynamics (MD)-based overall refinement failed to improve model qualities when target proteins have domains not covered by templates or when chains have very small interfaces. In human predictions, additional experimental data such as low-resolution electron microscopy (EM) map were utilized. EM data could assist oligomer structure prediction by providing a global shape of the complex structure.