High resolution protein structure prediction and the crystallographic phase problem

By Bin Qian, Srivatsan Raman, Rhiju Das, Philip Bradley, A. McCoy, Randy J. Read, David Baker. 2007

304 citations recorded by the source corpus.

The energy-based refinement of low-resolution protein structure models to atomic-level accuracy is a major challenge for computational structural biology. Here we describe a new approach to refining protein structure models that focuses sampling in regions most likely to contain errors while allowing the whole structure to relax in a physically realistic all-atom force field. In applications to models produced using nuclear magnetic resonance data and to comparative models based on distant structural homologues, the method can significantly improve the accuracy of the structures in terms of both the backbone conformations and the placement of core side chains. Furthermore, the resulting models satisfy a particularly stringent test: they provide significantly better solutions to the X-ray crystallographic phase problem in molecular replacement trials. Finally, we show that all-atom refinement can produce de novo protein structure predictions that reach the high accuracy required for molecular replacement without any experimental phase information and in the absence of templates suitable for molecular replacement from the Protein Data Bank. These results suggest that the combination of high-resolution structure prediction with state-of-the-art phasing tools may be unexpectedly powerful in phasing crystallographic data for which molecular replacement is hindered by the absence of sufficiently accurate previous models.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

Improvement of molecular-replacement models with Sculptor (2011, background): “Homology modelling is a very powerful technique to make improvements (Qian et al., 2007) but is computationally intensive, and for certain applications there is a need for simple quick algorithms.”
JPred4: a protein secondary structure prediction server (2015, background): “…structure alone is not as useful as a full three-dimensional model, secondary structure predictions provide important constraints for fold-recognition techniques (13–17) as well as in homology modelling (18,19), ab initio (20–24) and constraint-based tertiary structure prediction methods (25–27).”
Outcome of a Workshop on Applications of Protein Models in Biomedical Research (2009, methodology): “via molecular replacement models for proteins of distant homology or even no detectable homology to previously solved structures (Qian et al., 2007).”
A position-specific distance-dependent statistical potential for protein structure and functional study (2012, methodology): “This is consistent with what was observed on the Rosetta set.”
Improved Technologies Now Routinely Provide Protein NMR Structures Useful for Molecular Replacement (2011, methodology): “It has been pointed out previously that the phasing power of NMR structures that fail to provide good MR solutions can be significantly improved by Rosetta refinement (Qian et al., 2007; Ramelot et al., 2009).”
Practically Useful: What the Rosetta Protein Modeling Suite Can Do for You (2010, methodology): “De novo - predicted modelshave also been used toassist inphasingofX-ray diffraction data (see Figure 5) ( 26 , 41 , 42 ).”
RNA-Puzzles: a CASP-like evaluation of RNA three-dimensional structure prediction. (2012, methodology): “Globally correct solutions require global optimization, and this puzzle has motivated the group to develop iterative hybrid high-resolution/low-resolution approaches to RNA modeling, analogous to the rebuild-and-refine method used in Rosetta template-based modeling (Qian et al. 2007).”
Recent developments in phasing and structure refinement for macromolecular crystallography (2009, methodology): “At least in favorable circumstances, similar modeling techniques can generate ab initio models that are sufficiently accurate to succeed in molecular replacement calculations [25 ,26].”
Automated macromolecular model building for X-ray crystallography using ARP/wARP version 7 (2008, methodology): “Moreover, ARP/wARP is often used as a standard benchmark to evaluate the quality of electron density maps produced by new methods, as exemplified in ref”
phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta (2012, methodology): “Qian et al. [29] have shown that in some cases ab initio models created with Rosetta from sequence information alone can be sufﬁciently accurate to be useful The procedures used by DiMaio et al. [28] for combining Rosetta structure modeling and crystallographic model-building require considerable…”
Using iterative fragment assembly and progressive sequence truncation to facilitate phasing and crystal structure determination of distantly related proteins. (2016, methodology): “For example, Qian et al. (2007) used conformational variation to identify low-accuracy regions and performed a structural refinement and rebuilding process focused on the structurally variable regions to improve global model quality.”
Druggable Protein Interaction Sites Are More Predisposed to Surface Pocket Formation than the Rest of the Protein Surface (2013, unknown): “Simulations were carried out using the ‘‘relax’’ protocol [50] in”
AMPLE: a cluster-and-truncate approach to solve the crystal structures of small proteins using rapidly computed ab initio models. (2012, background): “This can be achieved since the variability between decoys in each cluster correlates with their deviation from the deposited native structure (Qian et al., 2007).”
Role of conformational sampling in computing mutation-induced changes in protein structure and stability (2010, background): “As with most other macromolecular structure prediction problems, 1 accurately predicting the structural changes associated with a point mutation requires, first, an efficient method for conformational sampling, and second, an accurate free energy function.”