scholarly journals Sequence assignment for low-resolution modelling of protein crystal structures

2019 ◽  
Vol 75 (8) ◽  
pp. 753-763 ◽  
Author(s):  
Grzegorz Chojnowski ◽  
Joana Pereira ◽  
Victor S. Lamzin
Keyword(s):  
Model Building ◽  
Protein Crystal ◽  
Side Chain ◽  
Sequence Coverage ◽  
Protein Fragments ◽  
New Methods ◽  
Combined Use ◽  
Protein Models ◽  
Automated Model Building ◽  
Sequence Assignment

The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for machine-learning-based docking of main-chain fragments to the sequence and for their sequence-independent connection using a dedicated library of protein fragments. The combined use of these new methods noticeably increases sequence coverage and reduces fragmentation of the protein models automatically built with ARP/wARP.

scholarly journals Sequence assignment validation in cryo-EM models with checkMySequence

2022 ◽  
Author(s):  
Grzegorz Chojnowski
Keyword(s):  
Structural Biology ◽  
Structure Prediction ◽  
Model Building ◽  
Visual Interpretation ◽  
Interactive Tools ◽  
Map Interpretation ◽  
Map Resolution ◽  
Protein Models ◽  
Register Error ◽  
Sequence Assignment

The availability of new AI-based protein structure prediction tools radically changed the way cryo-EM maps are interpreted, but it has not eliminated the challenges of map interpretation faced by a microscopist. Models will continue to be locally rebuilt and refined using interactive tools. This inevitably results in occasional errors, among which register-shifts remain one of the most difficult to identify and correct. Here we introduce checkMySequence; a fast, fully automated and parameter-free method for detecting register-shifts in protein models built into cryo-EM maps. We show that the method can assist model building in cases where poorer map resolution hinders visual interpretation. We also show that checkMySequence could have helped avoid a widely discussed sequence register error in a model of SARS-CoV-2 RNA-dependent RNA polymerase that was originally detected thanks to a visual residue-by-residue inspection by members of the structural biology community.

scholarly journals Completion of autobuilt protein models using a database of protein fragments

2012 ◽  
Vol 68 (4) ◽  
pp. 328-335 ◽  
Author(s):  
Kevin Cowtan
Keyword(s):  
Model Building ◽  
General Purpose ◽  
Search Method ◽  
Model Completeness ◽  
Protein Fragments ◽  
Arbitrary Size ◽  
Protein Model ◽  
Protein Models

Two developments in the process of automated protein model building in the Buccaneer software are presented. A general-purpose library for protein fragments of arbitrary size is described, with a highly optimized search method allowing the use of a larger database than in previous work. The problem of assembling an autobuilt model into complete chains is discussed. This involves the assembly of disconnected chain fragments into complete molecules and the use of the database of protein fragments in improving the model completeness. Assembly of fragments into molecules is a standard step in existing model-building software, but the methods have not received detailed discussion in the literature.

scholarly journals The use of local structural similarity of distant homologues for crystallographic model building from a molecular-replacement solution

2020 ◽  
Vol 76 (3) ◽  
pp. 248-260 ◽  
Author(s):  
Grzegorz Chojnowski ◽  
Koushik Choudhury ◽  
Philipp Heuser ◽  
Egor Sobolev ◽  
Joana Pereira ◽  
...  
Keyword(s):  
Model Building ◽  
Structural Information ◽  
Structural Similarity ◽  
Molecular Replacement ◽  
Sequence Coverage ◽  
Protein Model ◽  
Model Extension ◽  
Replacement Solution ◽  
Almost All ◽  
Protein Models

The performance of automated protein model building usually decreases with resolution, mainly owing to the lower information content of the experimental data. This calls for a more elaborate use of the available structural information about macromolecules. Here, a new method is presented that uses structural homologues to improve the quality of protein models automatically constructed using ARP/wARP. The method uses local structural similarity between deposited models and the model being built, and results in longer main-chain fragments that in turn can be more reliably docked to the protein sequence. The application of the homology-based model extension method to the example of a CFA synthase at 2.7 Å resolution resulted in a more complete model with almost all of the residues correctly built and docked to the sequence. The method was also evaluated on 1493 molecular-replacement solutions at a resolution of 4.0 Å and better that were submitted to the ARP/wARP web service for model building. A significant improvement in the completeness and sequence coverage of the built models has been observed.

scholarly journals Protein identification from electron cryomicroscopy maps by automated model building and side-chain matching

2021 ◽  
Vol 77 (4) ◽  
pp. 457-462
Author(s):  
Thomas C. Terwilliger ◽  
Oleg V. Sobolev ◽  
Pavel V. Afonine ◽  
Paul D. Adams ◽  
Chi-Min Ho ◽  
...  
Keyword(s):  
Single Particle ◽  
Protein Identification ◽  
Model Building ◽  
Side Chain ◽  
Electron Cryomicroscopy ◽  
3D Structures ◽  
Atomic Models ◽  
Map Interpretation ◽  
Highly Effective ◽  
Automated Model Building

Using single-particle electron cryo-microscopy (cryo-EM), it is possible to obtain multiple reconstructions showing the 3D structures of proteins imaged as a mixture. Here, it is shown that automatic map interpretation based on such reconstructions can be used to create atomic models of proteins as well as to match the proteins to the correct sequences and thereby to identify them. This procedure was tested using two proteins previously identified from a mixture at resolutions of 3.2 Å, as well as using 91 deposited maps with resolutions between 2 and 4.5 Å. The approach is found to be highly effective for maps obtained at resolutions of 3.5 Å and better, and to have some utility at resolutions as low as 4 Å.

scholarly journals Fragon: rapid high-resolution structure determination from ideal protein fragments

2018 ◽  
Vol 74 (3) ◽  
pp. 205-214 ◽  
Author(s):  
Huw T. Jenkins
Keyword(s):  
Model Building ◽  
Molecular Replacement ◽  
Success Rates ◽  
Test Set ◽  
Protein Fragments ◽  
Desktop Computers ◽  
High Resolution Structure ◽  
Ideal Protein ◽  
Test Sets ◽  
Automated Model Building

Correctly positioning ideal protein fragments by molecular replacement presents an attractive method for obtaining preliminary phases when no template structure for molecular replacement is available. This has been exploited in several existing pipelines. This paper presents a new pipeline, namedFragon, in which fragments (ideal α-helices or β-strands) are placed usingPhaserand the phases calculated from these coordinates are then improved by the density-modification methods provided byACORN. The reliable scoring algorithm provided byACORNidentifies success. In these cases, the resulting phases are usually of sufficient quality to enable automated model building of the entire structure.Fragonwas evaluated against two test sets comprising mixed α/β folds and all-β folds at resolutions between 1.0 and 1.7 Å. Success rates of 61% for the mixed α/β test set and 30% for the all-β test set were achieved. In almost 70% of successful runs, fragment placement and density modification took less than 30 min on relatively modest four-core desktop computers. In all successful runs the best set of phases enabled automated model building withARP/wARPto complete the structure.

Towards the automatic crystal structure solution of nucleic acids: automated model building using the new CAB program

2021 ◽  
Vol 77 (12) ◽  
Author(s):  
Giovanni Luca Cascarano ◽  
Carmelo Giacovazzo
Keyword(s):  
Nucleic Acids ◽  
Prior Information ◽  
Model Building ◽  
Phase Error ◽  
Heavy Atoms ◽  
Density Maps ◽  
Structure Solution ◽  
Nucleic Acid Structures ◽  
Automated Model Building ◽  
Model Chain

CAB, a recently described automated model-building (AMB) program, has been modified to work effectively with nucleic acids. To this end, several new algorithms have been introduced and the libraries have been updated. To reduce the input average phase error, ligand heavy atoms are now located before starting the CAB interpretation of the electron-density maps. Furthermore, alternative approaches are used depending on whether the ligands belong to the target or to the model chain used in the molecular-replacement step. Robust criteria are then applied to decide whether the AMB model is acceptable or whether it must be modified to fit prior information on the target structure. In the latter case, the model chains are rearranged to fit prior information on the target chains. Here, the performance of the new AMB program CAB applied to various nucleic acid structures is discussed. Other well documented programs such as Nautilus, ARP/wARP and phenix.autobuild were also applied and the experimental results are described.

Research on the Model-Building Error for EMS Maglev Vehicles

2014 ◽  
Vol 701-702 ◽  
pp. 757-760
Author(s):  
Xiao Zhang ◽  
Jun Yong Lu ◽  
Xin Lin Long
Keyword(s):  
Model Building ◽  
Simplified Model ◽  
Modeling Error ◽  
New Methods ◽  
Calculation Results

To estimate the influences of uncertain factors on the modeling error of maglev vehicles, the single electro-magnet is taken as the object in this paper. Researches on the model-building error are carried out, including factors of the uncertainty of the inductor, the elasticity of the guideway and the coupling between Modules. Also, the model-building errors are analyzed numerically from the view of L∞ norm. And the calculation results are presented, which shows severe model-building severe error with the simplified model. The results are revelatory to comprehend the phenomena of the vehicle’s vibration, and to search after new methods of levitation control for EMS maglev vehicles.

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.

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