Increasing the Radius of Convergence of Molecular Replacement by Density and Energy Guided Protein Structure Optimization

By Frank DiMaio, T. C. Terwilliger, Randy J. Read, A. Wlodawer, G. Oberdorfer, U. Wagner, E. Valkov, A. Alon, D. Fass, H. Axelrod and 5 more. 2011

229 citations recorded by the source corpus.

Molecular replacement procedures, which search for placements of a starting model within the crystallographic unit cell that best account for the measured diffraction amplitudes, followed by automatic chain tracing methods, have allowed the rapid solution of large numbers of protein crystal structures. Despite extensive work, molecular replacement or the subsequent rebuilding usually fail with more divergent starting models based on remote homologues with less than 30% sequence identity. Here we show that this limitation can be substantially reduced by combining algorithms for protein structure modelling with those developed for crystallographic structure determination. An approach integrating Rosetta structure modelling with Autobuild chain tracing yielded high-resolution structures for 8 of 13 X-ray diffraction data sets that could not be solved in the laboratories of expert crystallographers and that remained unsolved after application of an extensive array of alternative approaches. We estimate that the new method should allow rapid structure determination without experimental phase information for over half the cases where current methods fail, given diffraction data sets of better than 3.2 Å resolution, four or fewer copies in the asymmetric unit, and the availability of structures of homologous proteins with >20% sequence identity.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix (2019, methodology): “D75, 861–877 (i) MR-Rosetta (phenix.mr_rosetta) uses homology modeling in the Rosetta program to improve a model before and/or after MR (DiMaio et al., 2011; Terwilliger et al., 2012).”
Local Error Estimates Dramatically Improve the Utility of Homology Models for Solving Crystal Structures by Molecular Replacement (2015, methodology): “This has become an active area of research and several pipelines have been developed for ready use, e.g., mr_rosetta (DiMaio et al., 2011) in the PHENIX package (Adams et al., 2010).”
Large-scale determination of previously unsolved protein structures using evolutionary information (2015, background): “This additional information, in combination with a reasonably accurate energy function, has enabled the determination of high-resolution structures for much larger proteins ( Raman et al., 2009 ; DiMaio et al., 2011 ; Lange et al., 2012 ).”
One contact for every twelve residues allows robust and accurate topology-level protein structure modeling (2013, neutral): “1–3 Recent advances in molecular modeling using experimental data such as NMR chemical shifts4–7 and sparse restraints,8–13 electron density from diffraction data,14 and cryoEM15,16 have shown that even very sparse information can significantly improve modeling.”
RNA Structure Refinement using the ERRASER-Phenix pipeline (2013, methodology): “…in ab initio RNA structure prediction (6-8) and successful applications of the Rosetta modeling suite in crystallographic and electron microscopy density fitting problems (9, 10), we recently developed the ERRASER method and coupled it with Phenix diffraction-based refinement (11) into a pipeline.”
Using iterative fragment assembly and progressive sequence truncation to facilitate phasing and crystal structure determination of distantly related proteins. (2016, methodology): “A similar idea has already been implemented by other laboratories via the integration of electron-density information with Rosetta modeling (DiMaio et al., 2011; Terwilliger et al., 2012).”
Improved estimates of coordinate error for molecular replacement (2013, methodology): “Nonetheless, these solutions could be used as candidates in the recently developed MR-Rosetta procedure (DiMaio et al., 2011), which has been shown to yield a 50% success rate for further model building based on MR solutions with poor TFZ scores.”
Phaser.MRage: automated molecular replacement (2013, methodology): “In addition, advances in automatic model building, especially the integration of structure modelling in, for example, phenix.mr_rosetta (DiMaio et al., 2011) and AMPLE (Bibby et al., 2012), have increased the radius of convergence for refinement and led to successful structure determination from…”
Model morphing and sequence assignment after molecular replacement (2013, methodology): “…was the structure of a succinyl-diaminopimelate desuccinylase from the -proteobacterium Neisseria meningitidis (PDB entry 1vgy; Badger et al., 2005; Berman et al., 2000) that had been edited and placed in the correct position in the unit cell of the structure to be determined (DiMaio et al., 2011).”
phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta (2012, unknown): “To make the use of these procedures more accessible to a broader range of structural biologists, we developed software in the Phenix crystallographic computing environment [32] that provides simultaneous access to Rosetta structure modeling and Phenix crystallographic model-building [28].”
Application of DEN refinement and automated model building to a difficult case of molecular-replacement phasing: the structure of a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum (2012, methodology): “…to test the performance of real-space refinement of the molecularreplacement solution in conjunction with the Rosetta empirical energy function (DiMaio et al., 2011; case 10 in Table 1 in this reference), but the refinement was not completed owing to poor or disordered density in numerous…”
Protein model discrimination using mutational sensitivity derived from deep sequencing. (2012, methodology): “The figure is prepared in PyMOL (The PyMOL Molecular Graphics System, version 1.2r2, DeLano Scientific, LLC). less than about 100 residues, the models with the lowest energy are typically close to the actual native structure (DiMaio et al., 2011; Kuhlman et al., 2003; Rohl et al., 2004).”
Immunogenicity and structures of a rationally designed prefusion MERS-CoV spike antigen (2017, methodology): “Using this structure as input, MRROSETTA (81) was able to produce a model containing 282 residues.”