PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-8 (8)
 

Clipboard (0)
None

Select a Filter Below

Journals
Year of Publication
1.  Tools for macromolecular model building and refinement into electron cryo-microscopy reconstructions 
A description is given of new tools to facilitate model building and refinement into electron cryo-microscopy reconstructions.
The recent rapid development of single-particle electron cryo-microscopy (cryo-EM) now allows structures to be solved by this method at resolutions close to 3 Å. Here, a number of tools to facilitate the interpretation of EM reconstructions with stereochemically reasonable all-atom models are described. The BALBES database has been repurposed as a tool for identifying protein folds from density maps. Modifications to Coot, including new Jiggle Fit and morphing tools and improved handling of nucleic acids, enhance its functionality for interpreting EM maps. REFMAC has been modified for optimal fitting of atomic models into EM maps. As external structural information can enhance the reliability of the derived atomic models, stabilize refinement and reduce overfitting, ProSMART has been extended to generate interatomic distance restraints from nucleic acid reference structures, and a new tool, LIBG, has been developed to generate nucleic acid base-pair and parallel-plane restraints. Furthermore, restraint generation has been integrated with visualization and editing in Coot, and these restraints have been applied to both real-space refinement in Coot and reciprocal-space refinement in REFMAC.
doi:10.1107/S1399004714021683
PMCID: PMC4304694  PMID: 25615868
model building; refinement;  electron cryo-microscopy reconstructions; LIBG
2.  Structure of the Yeast Mitochondrial Large Ribosomal Subunit 
Science (New York, N.Y.)  2014;343(6178):1485-1489.
Mitochondria have specialized ribosomes that have diverged from their bacterial and cytoplasmic counterparts. We have solved the structure of the yeast mitoribosomal large subunit using single-particle electron cryo-microscopy. The resolution of 3.2 Ångstroms enabled a nearly complete atomic model to be built de novo and refined, including 39 proteins, 13 of which are unique to mitochondria, as well as expansion segments of mitoribosomal RNA. The structure reveals a new exit tunnel path and architecture, unique elements of the E site and a putative membrane docking site.
doi:10.1126/science.1249410
PMCID: PMC4046073  PMID: 24675956
3.  Handling ligands with Coot  
Coot is a molecular-graphics program designed to assist in the building of protein and other macromolecular models. The current state of ligand tools is presented.
Coot is a molecular-graphics application primarily aimed to assist in model building and validation of biological macromolecules. Recently, tools have been added to work with small molecules. The newly incorporated tools for the manipulation and validation of ligands include interaction with PRODRG, subgraph isomorphism-based tools, representation of ligand chemistry, ligand fitting and analysis, and are described here.
doi:10.1107/S0907444912000200
PMCID: PMC3322601  PMID: 22505262
Coot; ligands
4.  A New Generation of Crystallographic Validation Tools for the Protein Data Bank 
Structure(London, England:1993)  2011;19(10):1395-1412.
Summary
This report presents the conclusions of the X-ray Validation Task Force of the worldwide Protein Data Bank (PDB). The PDB has expanded massively since current criteria for validation of deposited structures were adopted, allowing a much more sophisticated understanding of all the components of macromolecular crystals. The size of the PDB creates new opportunities to validate structures by comparison with the existing database, and the now-mandatory deposition of structure factors creates new opportunities to validate the underlying diffraction data. These developments highlighted the need for a new assessment of validation criteria. The Task Force recommends that a small set of validation data be presented in an easily understood format, relative to both the full PDB and the applicable resolution class, with greater detail available to interested users. Most importantly, we recommend that referees and editors judging the quality of structural experiments have access to a concise summary of well-established quality indicators.
Highlights
► Validation criteria used by the PDB for X-ray crystal structures have been reassessed ► Key scores should be presented prominently in an easily understood format ► A concise validation report should be available to referees of papers on crystal structures
doi:10.1016/j.str.2011.08.006
PMCID: PMC3195755  PMID: 22000512
5.  From crystal to structure with CCP4 
An introduction to the proceedings of the CCP4 study weekend is given.
doi:10.1107/S0907444911007578
PMCID: PMC3069737  PMID: 21460440
CCP4
6.  Overview of the CCP4 suite and current developments 
An overview of the CCP4 software suite for macromolecular crystallography is given.
The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallo­graphy is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package.
doi:10.1107/S0907444910045749
PMCID: PMC3069738  PMID: 21460441
CCP4; macromolecular crystallography; software; collaboration; automation; macromolecular structure determination
7.  Autofix for backward-fit sidechains: using MolProbity and real-space refinement to put misfits in their place 
Misfit sidechains in protein crystal structures are a stumbling block in using those structures to direct further scientific inference. Problems due to surface disorder and poor electron density are very difficult to address, but a large class of systematic errors are quite common even in well-ordered regions, resulting in sidechains fit backwards into local density in predictable ways. The MolProbity web site is effective at diagnosing such errors, and can perform reliable automated correction of a few special cases such as 180° flips of Asn or Gln sidechain amides, using all-atom contacts and H-bond networks. However, most at-risk residues involve tetrahedral geometry, and their valid correction requires rigorous evaluation of sidechain movement and sometimes backbone shift. The current work extends the benefits of robust automated correction to more sidechain types. The Autofix method identifies candidate systematic, flipped-over errors in Leu, Thr, Val, and Arg using MolProbity quality statistics, proposes a corrected position using real-space refinement with rotamer selection in Coot, and accepts or rejects the correction based on improvement in MolProbity criteria and on χ angle change. Criteria are chosen conservatively, after examining many individual results, to ensure valid correction. To test this method, Autofix was run and analyzed for 945 representative PDB files and on the 50S ribosomal subunit of file 1YHQ. Over 40% of Leu, Val, and Thr outliers and 15% of Arg outliers were successfully corrected, resulting in a total of 3,679 corrected sidechains, or 4 per structure on average. Summary Sentences: A common class of misfit sidechains in protein crystal structures is due to systematic errors that place the sidechain backwards into the local electron density. A fully automated method called “Autofix” identifies such errors for Leu, Val, Thr, and Arg and corrects over one third of them, using MolProbity validation criteria and Coot real-space refinement of rotamers.
Electronic supplementary material
The online version of this article (doi:10.1007/s10969-008-9045-8) contains supplementary material, which is available to authorized users.
doi:10.1007/s10969-008-9045-8
PMCID: PMC2704614  PMID: 19002604
Automation; Structure improvement; Crystallography; Sidechain rotamers; Protein/RNA interactions
8.  A knowledge-driven approach for crystallographic protein model completion 
A novel method that uses the conformational distribution of Cα atoms in known structures is used to build short missing regions (‘loops’) in protein models. An initial tree of possible loop paths is pruned according to structural and electron-density criteria and the most likely loop conformation(s) are selected and built.
One of the most cumbersome and time-demanding tasks in completing a protein model is building short missing regions or ‘loops’. A method is presented that uses structural and electron-density information to build the most likely conformations of such loops. Using the distribution of angles and dihedral angles in pentapeptides as the driving parameters, a set of possible conformations for the Cα backbone of loops was generated. The most likely candidate is then selected in a hierarchical manner: new and stronger restraints are added while the loop is built. The weight of the electron-density correlation relative to geometrical considerations is gradually increased until the most likely loop is selected on map correlation alone. To conclude, the loop is refined against the electron density in real space. This is started by using structural information to trace a set of models for the Cα backbone of the loop. Only in later steps of the algorithm is the electron-density correlation used as a criterion to select the loop(s). Thus, this method is more robust in low-density regions than an approach using density as a primary criterion. The algorithm is implemented in a loop-building program, Loopy, which can be used either alone or as part of an automatic building cycle. Loopy can build loops of up to 14 residues in length within a couple of minutes. The average root-mean-square deviation of the Cα atoms in the loops built during validation was less than 0.4 Å. When implemented in the context of automated model building in ARP/wARP, Loopy can increase the completeness of the built models.
doi:10.1107/S0907444908001558
PMCID: PMC2467521  PMID: 18391408
model building; loop modelling; Loopy

Results 1-8 (8)