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 Applications of molecular replacement to G protein-coupled receptors

2013 ◽  
Vol 69 (11) ◽  
pp. 2287-2292 ◽  
Author(s):  
Andrew C. Kruse ◽  
Aashish Manglik ◽  
Brian K. Kobilka ◽  
William I. Weis
Keyword(s):  
G Protein ◽  
Structural Biology ◽  
Structural Information ◽  
G Protein Coupled Receptors ◽  
Integral Membrane Proteins ◽  
Molecular Replacement ◽  
Gpcr Activation ◽  
Health And Disease ◽  
Almost All ◽  
G Protein Coupled

G protein-coupled receptors (GPCRs) are a large class of integral membrane proteins involved in regulating virtually every aspect of human physiology. Despite their profound importance in human health and disease, structural information regarding GPCRs has been extremely limited until recently. With the advent of a variety of new biochemical and crystallographic techniques, the structural biology of GPCRs has advanced rapidly, offering key molecular insights into GPCR activation and signal transduction. To date, almost all GPCR structures have been solved using molecular-replacement techniques. Here, the unique aspects of molecular replacement as applied to individual GPCRs and to signaling complexes of these important proteins are discussed.

scholarly journals Estimating local protein model quality: prospects for molecular replacement

2020 ◽  
Vol 76 (3) ◽  
pp. 285-290
Author(s):  
Björn Wallner
Keyword(s):  
Error Estimates ◽  
Added Value ◽  
Local Error ◽  
Molecular Replacement ◽  
Model Quality ◽  
Data Set ◽  
Protein Model ◽  
Protein Models ◽  
Local Protein

Model quality assessment programs estimate the quality of protein models and can be used to estimate local error in protein models. ProQ3D is the most recent and most accurate version of our software. Here, it is demonstrated that it is possible to use local error estimates to substantially increase the quality of the models for molecular replacement (MR). Adjusting the B factors using ProQ3D improved the log-likelihood gain (LLG) score by over 50% on average, resulting in significantly more successful models in MR compared with not using error estimates. On a data set of 431 homology models to address difficult MR targets, models with error estimates from ProQ3D received an LLG of >50 for almost half of the models 209/431 (48.5%), compared with 175/431 (40.6%) for the previous version, ProQ2, and only 74/431 (17.2%) for models with no error estimates, clearly demonstrating the added value of using error estimates to enable MR for more targets. ProQ3D is available from http://proq3.bioinfo.se/ both as a server and as a standalone download.

scholarly journals Cyclic Automated Model Building (CAB) Applied to Nucleic Acids

Crystals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 280
Author(s):  
Maria Cristina Burla ◽  
Benedetta Carrozzini ◽  
Giovanni Luca Cascarano ◽  
Carmelo Giacovazzo ◽  
Giampiero Polidori
Keyword(s):  
Nucleic Acid ◽  
Nucleic Acids ◽  
Model Building ◽  
State Of The Art ◽  
Molecular Replacement ◽  
Dna And Rna ◽  
Protein Model ◽  
Rna Fragments ◽  
Nucleic Acid Structures ◽  
Automated Model Building

Obtaining high-quality models for nucleic acid structures by automated model building programs (AMB) is still a challenge. The main reasons are the rather low resolution of the diffraction data and the large number of rotatable bonds in the main chains. The application of the most popular and documented AMB programs (e.g., PHENIX.AUTOBUILD, NAUTILUS and ARP/wARP) may provide a good assessment of the state of the art. Quite recently, a cyclic automated model building (CAB) package was described; it is a new AMB approach that makes the use of BUCCANEER for protein model building cyclic without modifying its basic algorithms. The applications showed that CAB improves the efficiency of BUCCANEER. The success suggested an extension of CAB to nucleic acids—in particular, to check if cyclically including NAUTILUS in CAB may improve its effectiveness. To accomplish this task, CAB algorithms designed for protein model building were modified to adapt them to the nucleic acid crystallochemistry. CAB was tested using 29 nucleic acids (DNA and RNA fragments). The phase estimates obtained via molecular replacement (MR) techniques were automatically submitted to phase refinement and then used as input for CAB. The experimental results from CAB were compared with those obtained by NAUTILUS, ARP/wARP and PHENIX.AUTOBUILD.

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 Molecular replacement: tricks and treats

2013 ◽  
Vol 69 (11) ◽  
pp. 2167-2173 ◽  
Author(s):  
Chantal Abergel
Keyword(s):  
Structural Information ◽  
Homology Modelling ◽  
Normal Mode Analysis ◽  
Mode Analysis ◽  
Crystallographic Structure ◽  
Molecular Replacement ◽  
The Core ◽  
Generating Series ◽  
Replacement Solution ◽  
Total Structure

Molecular replacement is the method of choice for X-ray crystallographic structure determination provided that suitable structural homologues are available in the PDB. Presently, there are ∼80 000 structures in the PDB (8074 were deposited in the year 2012 alone), of which ∼70% have been solved by molecular replacement. For successful molecular replacement the model must cover at least 50% of the total structure and the Cαr.m.s.d. between the core model and the structure to be solved must be less than 2 Å. Here, an approach originally implemented in theCaspRserver (http://www.igs.cnrs-mrs.fr/Caspr2/index.cgi) based on homology modelling to search for a molecular-replacement solution is discussed. How the use of as much information as possible from different sources can improve the model(s) is briefly described. The combination of structural information with distantly related sequences is crucial to optimize the multiple alignment that will define the boundaries of the core domains. PDB clusters (sequences with ≥30% identical residues) can also provide information on the eventual changes in conformation and will help to explore the relative orientations assumed by protein subdomains. Normal-mode analysis can also help in generating series of conformational models in the search for a molecular-replacement solution. Of course, finding a correct solution is only the first step and the accuracy of the identified solution is as important as the data quality to proceed through refinement. Here, some possible reasons for failure are discussed and solutions are proposed using a set of successful examples.

ValiFrag: Evaluating fragment quality during automated protein model building

2014 ◽  
Vol 70 (a1) ◽  
pp. C1443-C1443
Author(s):  
Joana Pereira ◽  
Tim Wiegels ◽  
Victor Lamzin
Keyword(s):  
Model Building ◽  
Structural Information ◽  
Data Bank ◽  
Protein Chain ◽  
Final Model ◽  
Manual Intervention ◽  
Operational Range ◽  
Model Completion ◽  
Structural Validation ◽  
Protein Models

X-ray diffraction data from flexible macromolecules and their complexes can rarely be measured to a resolution better than 3 Å. Due to a loss of detectable atomic features, the determination of low-resolution structures is beyond the current operational range of crystallographic software and requires a large amount of manual intervention. ARP/wARP [1] v7.4 generates structures that are up to 80% complete at 3.0 Å, but the completeness drops sharply as the resolution gets worse. Reduction of the model completeness is accompanied with an increase in the number of fragments built, which become shorter. Such fragments are applicable for further model building if they are correct. Though, if they are wrong they may cause the formation of incorrectly built regions in the final model. Thus, there is a need to improve fragment quality before automated model completion is applied. We exploit the vast amount of structural information deposited in the Protein Data Bank (PDB) [2], to make use of it for structural validation of built fragments. Precisely, we evaluate the conformation of each fragment. If the conformation is present in several different protein models in the PDB, it is likely to be modelled correctly in the built model and is accepted. If, on the contrary, it cannot be found in any PDB model, it is probably incorrect. Here we present the software implementation of this validation, called ValiFrag, which checks the validity of automatically built protein chain fragments by evaluating their occurrence in the PDB. Protein models from the PDB were broken into dipeptides and conformational parameters for each of these were then stored in a database. For each automatically built fragment, ValiFrag computes the probability of it to be correct according to the conformation of all possible dipeptides. It can, therefore, assess which fragments are likely to be structurally incorrect and should possibly be modified, or even removed, to improve the final model.

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.

Fused Image Quality Measure Based on Structural Similarity

2011 ◽  
Vol 255-260 ◽  
pp. 2072-2076
Author(s):  
Yi Yong Han ◽  
Jun Ju Zhang ◽  
Ben Kang Chang ◽  
Yi Hui Yuan ◽  
Hui Xu
Keyword(s):  
Image Fusion ◽  
Structural Information ◽  
Similarity Index ◽  
Structural Similarity ◽  
Reference Image ◽  
Human Visual Perception ◽  
Subjective Evaluations ◽  
Fused Image ◽  
Fusion Methods ◽  
Image Quality Measure

Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we present a new approach using structural similarity index for assessing quality in image fusion. The advantages of our measures are that they do not require a reference image and can be easily computed. Numerous simulations demonstrate that our measures are conform to subjective evaluations and can be able to assess different image fusion methods.

Crystallization and preliminary X-ray diffraction studies of human catalase

1999 ◽  
Vol 55 (9) ◽  
pp. 1614-1615 ◽  
Author(s):  
R. A. P. Nagem ◽  
E. A. L. Martins ◽  
V. M. Gonçalves ◽  
R. Aparício ◽  
I. Polikarpov
Keyword(s):  
Search Model ◽  
Molecular Replacement ◽  
X Ray Diffraction ◽  
Beef Liver ◽  
X Ray ◽  
Diffusion Technique ◽  
Cell Dimensions ◽  
Synchrotron Radiation Diffraction ◽  
Replacement Solution ◽  
Unit Cell Dimensions

The enzyme catalase (H2O2–H2O2 oxidoreductase; E.C. 11.1.6) was purified from haemolysate of human placenta and crystallized using the vapour-diffusion technique. Synchrotron-radiation diffraction data have been collected to 1.76 Å resolution. The enzyme crystallized in the space group P212121, with unit-cell dimensions a = 83.6, b = 139.4, c = 227.5 Å. A molecular-replacement solution of the structure has been obtained using beef liver catalase (PDB code 4blc) as a search model.

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