CAB: a cyclic automatic model-building procedure

2018 ◽  
Vol 74 (11) ◽  
pp. 1096-1104 ◽  
Author(s):  
Maria Cristina Burla ◽  
Benedetta Carrozzini ◽  
Giovanni Luca Cascarano ◽  
Giampiero Polidori ◽  
Carmelo Giacovazzo
Keyword(s):  
Electron Density ◽  
Model Building ◽  
Molecular Model ◽  
Protein Structures ◽  
Specific Property ◽  
Current Phase ◽  
Acta Cryst ◽  
Density Maps ◽  
Building Program ◽  
Automatic Model Building

The program Buccaneer, a well known fast and efficient automatic model-building program, is also a tool for phase refinement: indeed, input phases are used to calculate electron-density maps that are interpreted in terms of a molecular model, from which new phase estimates may be obtained. This specific property is shared by all other automatic model-building programs and allows their cyclic use, as is usually performed in other phase-refinement methods (for example electron-density modification techniques). Buccaneer has been included in a cyclic procedure, called CAB, aimed at increasing the rate of success of Buccaneer and the quality of the molecular models provided. CAB has been tested on 81 protein structures that were solved via molecular-replacement, anomalous dispersion and ab initio methods. The corresponding phases were submitted to a phase-refinement process that synergically combines current phase-refinement techniques and out-of-mainstream refinement methods [Burla et al. (2017), Acta Cryst. D73, 877–888]. The phases thus obtained were used as input for CAB. The experimental results were compared with those obtained by the sole use of Buccaneer: it is shown that CAB improves the Buccaneer results, both in completeness and in accuracy.

Protein phasing at non-atomic resolution by combining Patterson andVLDtechniques

2014 ◽  
Vol 70 (7) ◽  
pp. 1994-2006 ◽  
Author(s):  
Rocco Caliandro ◽  
Benedetta Carrozzini ◽  
Giovanni Luca Cascarano ◽  
Giuliana Comunale ◽  
Carmelo Giacovazzo ◽  
...  
Keyword(s):  
Model Building ◽  
Protein Structures ◽  
Experimental Information ◽  
Atomic Resolution ◽  
Data Sets ◽  
Density Maps ◽  
Combined Use ◽  
Final Electron ◽  
Automatic Model Building

Phasing proteins at non-atomic resolution is still a challenge for anyab initiomethod. A variety of algorithms [Patterson deconvolution, superposition techniques, a cross-correlation function (Cmap), theVLD(vive la difference) approach, the FF function, a nonlinear iterative peak-clipping algorithm (SNIP) for defining the background of a map and thefree lunchextrapolation method] have been combined to overcome the lack of experimental information at non-atomic resolution. The method has been applied to a large number of protein diffraction data sets with resolutions varying from atomic to 2.1 Å, with the condition that S or heavier atoms are present in the protein structure. The applications include the use ofARP/wARPto check the quality of the final electron-density maps in an objective way. The results show that resolution is still the maximum obstacle to protein phasing, but also suggest that the solution of protein structures at 2.1 Å resolution is a feasible, even if still an exceptional, task for the combined set of algorithms implemented in the phasing program. The approach described here is more efficient than the previously described procedures:e.g.the combined use of the algorithms mentioned above is frequently able to provide phases of sufficiently high quality to allow automatic model building. The method is implemented in the current version ofSIR2014.

scholarly journals Automated nucleic acid chain tracing in real time

IUCrJ ◽  
2014 ◽  
Vol 1 (6) ◽  
pp. 387-392 ◽  
Author(s):  
Kevin Cowtan
Keyword(s):  
Electron Density ◽  
Model Building ◽  
Protein Structures ◽  
Current View ◽  
Crystallographic Structure ◽  
Large Structures ◽  
Density Maps ◽  
Structure Solution ◽  
Automated Model Building ◽  
Electron Density Map

The crystallographic structure solution of nucleotides and nucleotide complexes is now commonplace. The resulting electron-density maps are often poorer than for proteins, and as a result interpretation in terms of an atomic model can require significant effort, particularly in the case of large structures. While model building can be performed automatically, as with proteins, the process is time-consuming, taking minutes to days depending on the software and the size of the structure. A method is presented for the automatic building of nucleotide chains into electron density which is fast enough to be used in interactive model-building software, with extended chain fragments built around the current view position in a fraction of a second. The speed of the method arises from the determination of the `fingerprint' of the sugar and phosphate groups in terms of conserved high-density and low-density features, coupled with a highly efficient scoring algorithm. Use cases include the rapid evaluation of an initial electron-density map, addition of nucleotide fragments to prebuilt protein structures, and in favourable cases the completion of the structure while automated model-building software is still running. The method has been incorporated into theCootsoftware package.

A Comparison of Two Algorithms for Electron-Density Map Improvement by Introduction of Atomicity: Skeletonization, and Map Sorting Followed by Refinement

1998 ◽  
Vol 54 (1) ◽  
pp. 81-85 ◽  
Author(s):  
F. M. D. Vellieux
Keyword(s):  
Electron Density ◽  
Initial Density ◽  
Acta Cryst ◽  
Density Maps ◽  
Resolution Electron ◽  
Crystallographic Symmetry ◽  
Density Map ◽  
Ornithine Transcarbamoylase ◽  
Electron Density Map ◽  
Pseudo Atom

A comparison has been made of two methods for electron-density map improvement by the introduction of atomicity, namely the iterative skeletonization procedure of the CCP4 program DM [Cowtan & Main (1993). Acta Cryst. D49, 148–157] and the pseudo-atom introduction followed by the refinement protocol in the program suite DEMON/ANGEL [Vellieux, Hunt, Roy & Read (1995). J. Appl. Cryst. 28, 347–351]. Tests carried out using the 3.0 Å resolution electron density resulting from iterative 12-fold non-crystallographic symmetry averaging and solvent flattening for the Pseudomonas aeruginosa ornithine transcarbamoylase [Villeret, Tricot, Stalon & Dideberg (1995). Proc. Natl Acad. Sci. USA, 92, 10762–10766] indicate that pseudo-atom introduction followed by refinement performs much better than iterative skeletonization: with the former method, a phase improvement of 15.3° is obtained with respect to the initial density modification phases. With iterative skeletonization a phase degradation of 0.4° is obtained. Consequently, the electron-density maps obtained using pseudo-atom phases or pseudo-atom phases combined with density-modification phases are much easier to interpret. These tests also show that for ornithine transcarbamoylase, where 12-fold non-crystallographic symmetry is present in the P1 crystals, G-function coupling leads to the simultaneous decrease of the conventional R factor and of the free R factor, a phenomenon which is not observed when non-crystallographic symmetry is absent from the crystal. The method is far less effective in such a case, and the results obtained suggest that the map sorting followed by refinement stage should be by-passed to obtain interpretable electron-density distributions.

scholarly journals σ2 R , a reciprocal-space measure of the quality of macromolecular electron-density maps

1999 ◽  
Vol 55 (6) ◽  
pp. 1174-1178 ◽  
Author(s):  
Thomas C. Terwilliger
Keyword(s):  
Standard Deviation ◽  
Ab Initio ◽  
Electron Density ◽  
Reciprocal Space ◽  
Rapid Evaluation ◽  
Reliable Measure ◽  
Similar Measure ◽  
Acta Cryst ◽  
Density Maps

It has previously been shown that the presence of distinct regions of solvent and protein in macromolecular crystals leads to a high value of the standard deviation of local r.m.s. electron density and that this can in turn be used as a reliable measure of the quality of macromolecular electron-density maps [Terwilliger & Berendzen (1999a). Acta Cryst. D55, 501–505]. Here, it is demonstrated that a similar measure, \sigma_{R}^{2}, the variance of the local roughness of the electron density, can be calculated in reciprocal space. The formulation is suitable for rapid evaluation of macromolecular crystallographic phases, for phase improvement and for ab initio phasing procedures.

Synergy among phase-refinement techniques in macromolecular crystallography

2017 ◽  
Vol 73 (11) ◽  
pp. 877-888 ◽  
Author(s):  
Maria Cristina Burla ◽  
Giovanni Luca Cascarano ◽  
Carmelo Giacovazzo ◽  
Giampiero Polidori
Keyword(s):  
Ab Initio ◽  
Electron Density ◽  
Molecular Model ◽  
Experimental Tests ◽  
Protein Chemistry ◽  
Sources Of Information ◽  
Density Maps ◽  
Structure Solution ◽  
Molecular Interpretation ◽  
The Difference

Ab initioand non-ab initiophasing methods are often unable to provide phases of sufficient quality to allow the molecular interpretation of the resulting electron-density maps. Phase extension and refinement is therefore a necessary step: its success or failure can make the difference between solution and nonsolution of the crystal structure. Today phase refinement is trusted to electron-density modification (EDM) techniques, and in practice to dual-space methods which try,viasuitable constraints in direct and in reciprocal space, to generate higher quality electron-density maps. The most popular EDM approaches, denoted here as mainstream methods, are usually part of packages which assist crystallographers in all of the structure-solution steps from initial phasing to the point where the molecular model perfectly fits the known features of protein chemistry. Other phase-refinement approaches that are based on different sources of information, denoted here as out-of-mainstream methods, are not frequently employed. This paper aims to show that mainstream and out-of-mainstream methods may be combined and may lead to dramatic advances in the present state of the art. The statement is confirmed by experimental tests using molecular-replacement, SAD–MAD andab initiotechniques.

scholarly journals Automated detection of disulfide bridges in electron density maps using linear discriminant analysis

2005 ◽  
Vol 38 (1) ◽  
pp. 121-125 ◽  
Author(s):  
Thomas R. Ioerger
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Electron Density ◽  
Model Building ◽  
Computational Method ◽  
Training Data ◽  
Decision Threshold ◽  
Disulfide Bridges ◽  
Linear Discriminant ◽  
Density Maps

The ability to recognize disulfide bridges automatically in electron density maps would be useful to both protein crystallographers and automated model-building programs. A computational method is described for recognizing disulfide bridges in uninterpreted maps based on linear discriminant analysis. For each localized spherical region in a map, a vector of rotation-invariant numeric features is calculated that captures various aspects of the local pattern of density. These features values are then input into a linear equation, with coefficients computed to optimize discrimination of a set of training examples (disulfides and non-disulfides), and compared with a decision threshold. The method is shown to be highly accurate at distinguishing disulfides from non-disulfides in both the original training data and in real (experimental) electron density maps of other proteins.

scholarly journals Rapid model building of α-helices in electron-density maps

2010 ◽  
Vol 66 (3) ◽  
pp. 268-275 ◽  
Author(s):  
Thomas C. Terwilliger
Keyword(s):  
High Resolution ◽  
Electron Density ◽  
Model Building ◽  
Main Chain ◽  
Rapid Identification ◽  
Side Chains ◽  
Low Resolution ◽  
Density Maps ◽  
Experimental Electron Density

A method for the identification of α-helices in electron-density maps at low resolution followed by interpretation at moderate to high resolution is presented. Rapid identification is achieved at low resolution, where α-helices appear as tubes of density. The positioning and direction of the α-helices is obtained at moderate to high resolution, where the positions of side chains can be seen. The method was tested on a set of 42 experimental electron-density maps at resolutions ranging from 1.5 to 3.8 Å. An average of 63% of the α-helical residues in these proteins were built and an average of 76% of the residues built matched helical residues in the refined models of the proteins. The overall average r.m.s.d. between main-chain atoms in the modeled α-helices and the nearest atom with the same name in the refined models of the proteins was 1.3 Å.

Correcting resolution bias in electron density maps of organic molecules derived by direct methods from powder data

2008 ◽  
Vol 41 (3) ◽  
pp. 592-599 ◽  
Author(s):  
Angela Altomare ◽  
Corrado Cuocci ◽  
Carmelo Giacovazzo ◽  
Anna Moliterni ◽  
Rosanna Rizzi
Keyword(s):  
Electron Density ◽  
Direct Methods ◽  
Large Set ◽  
Acta Cryst ◽  
Pattern Decomposition ◽  
Density Maps ◽  
Decomposition Procedure ◽  
Data Resolution ◽  
Current Electron ◽  
The Difference

Fourier syntheses providing electron density maps are usually affected by truncation effects due to the limited data resolution. A recent theoretical approach [Altomare, Cuocci, Giacovazzo, Kamel, Moliterni & Rizzi (2008).Acta Cryst.A64, 326–336] suggests that the resolution bias may be reduced by correcting the current electron density maps in accordance with the physics of the diffraction experiment. We have implemented the approach inEXPO2004[Altomare, Caliandro, Camalli, Cuocci, Giacovazzo, Moliterni & Rizzi (2004).J. Appl. Cryst.37, 1025–1028], a program devoted to the solution of crystal structures from powder data. The new algorithm was applied at the end of the direct methods modulus, to verify if the reduction of the resolution bias is able to improve the electron density maps and to provide additional power to direct methods. Application of this method to a large set of test structures indicates that resolution-bias correction often makes the difference between success and failure, and thus constitutes a new tool for reducing the dependence of modern crystallography on resolution effects. The chances of failure are expected to depend on the quality of the experimental data (e.g.the accuracy of the full-pattern decomposition procedure and the data resolution), on the size of the structure and on its chemical composition.

scholarly journals Homology-based loop modeling yields more complete crystallographic protein structures

IUCrJ ◽  
2018 ◽  
Vol 5 (5) ◽  
pp. 585-594 ◽  
Author(s):  
Bart van Beusekom ◽  
Krista Joosten ◽  
Maarten L. Hekkelman ◽  
Robbie P. Joosten ◽  
Anastassis Perrakis
Keyword(s):  
Protein Function ◽  
Model Building ◽  
Protein Structures ◽  
Structural Models ◽  
Data Bank ◽  
Loop Modeling ◽  
X Ray ◽  
Density Maps ◽  
Complete Protein ◽  
Automated Procedures

Inherent protein flexibility, poor or low-resolution diffraction data or poorly defined electron-density maps often inhibit the building of complete structural models during X-ray structure determination. However, recent advances in crystallographic refinement and model building often allow completion of previously missing parts. This paper presents algorithms that identify regions missing in a certain model but present in homologous structures in the Protein Data Bank (PDB), and `graft' these regions of interest. These new regions are refined and validated in a fully automated procedure. Including these developments in the PDB-REDO pipeline has enabled the building of 24 962 missing loops in the PDB. The models and the automated procedures are publicly available through the PDB-REDO databank and webserver. More complete protein structure models enable a higher quality public archive but also a better understanding of protein function, better comparison between homologous structures and more complete data mining in structural bioinformatics projects.

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