Comparing Cryo-EM Reconstructions and Validating Atomic Model Fit Using Difference Maps.
ABSTRACT: Cryogenic electron microscopy (cryo-EM) is a powerful technique for determining structures of multiple conformational or compositional states of macromolecular assemblies involved in cellular processes. Recent technological developments have led to a leap in the resolution of many cryo-EM data sets, making atomic model building more common for data interpretation. We present a method for calculating differences between two cryo-EM maps or a map and a fitted atomic model. The proposed approach works by scaling the maps using amplitude matching in resolution shells. To account for variability in local resolution of cryo-EM data, we include a procedure for local amplitude scaling that enables appropriate scaling of local map contrast. The approach is implemented as a user-friendly tool in the CCP-EM software package. To obtain clean and interpretable differences, we propose a protocol involving steps to process the input maps and output differences. We demonstrate the utility of the method for identifying conformational and compositional differences including ligands. We also highlight the use of difference maps for evaluating atomic model fit in cryo-EM maps.
Project description:Atomic models based on high-resolution density maps are the ultimate result of the cryo-EM structure determination process. Here, we introduce a general procedure for local sharpening of cryo-EM density maps based on prior knowledge of an atomic reference structure. The procedure optimizes contrast of cryo-EM densities by amplitude scaling against the radially averaged local falloff estimated from a windowed reference model. By testing the procedure using six cryo-EM structures of TRPV1, ?-galactosidase, ?-secretase, ribosome-EF-Tu complex, 20S proteasome and RNA polymerase III, we illustrate how local sharpening can increase interpretability of density maps in particular in cases of resolution variation and facilitates model building and atomic model refinement.
Project description:Cryo-EM now commonly generates close-to-atomic resolution as well as intermediate resolution maps from macromolecules observed in isolation and in situ. Interpreting these maps remains a challenging task owing to poor signal in the highest resolution shells and the necessity to select a threshold for density analysis. In order to facilitate this process, a statistical framework for the generation of confidence maps by multiple hypothesis testing and false discovery rate (FDR) control has been developed. In this way, three-dimensional confidence maps contain signal separated from background noise in the form of local detection rates of EM density values. It is demonstrated that confidence maps and FDR-based thresholding can be used for the interpretation of near-atomic resolution single-particle structures as well as lower resolution maps determined by subtomogram averaging. Confidence maps represent a conservative way of interpreting molecular structures owing to minimized noise. At the same time they provide a detection error with respect to background noise, which is associated with the density and is particularly beneficial for the interpretation of weaker cryo-EM densities in cases of conformational flexibility and lower occupancy of bound molecules and ions in the structure.
Project description:Recent advances in the field of electron cryomicroscopy (cryo-EM) have resulted in a rapidly increasing number of atomic models of biomacromolecules that have been solved using this technique and deposited in the Protein Data Bank and the Electron Microscopy Data Bank. Similar to macromolecular crystallography, validation tools for these models and maps are required. While some of these validation tools may be borrowed from crystallography, new methods specifically designed for cryo-EM validation are required. Here, new computational methods and tools implemented in PHENIX are discussed, including d99 to estimate resolution, phenix.auto_sharpen to improve maps and phenix.mtriage to analyze cryo-EM maps. It is suggested that cryo-EM half-maps and masks should be deposited to facilitate the evaluation and validation of cryo-EM-derived atomic models and maps. The application of these tools to deposited cryo-EM atomic models and maps is also presented.
Project description:The increasing power and popularity of cryo-electron microscopy (cryo-EM) in structural biology brought about the development of so-called hybrid methods, which permit the interpretation of cryo-EM density maps beyond their nominal resolution in terms of atomic models. The Cryo-EM Modeling Challenge 2010 is the first community effort to bring together developers of hybrid methods as well as cryo-EM experimentalists. Participating in the challenge, the molecular dynamics flexible fitting (MDFF) method was applied to a number of cryo-EM density maps. The results are described here with special emphasis on the use of symmetry-based restraints to improve the quality of atomic models derived from density maps of symmetric complexes; on a comparison of the stereochemical quality of atomic models resulting from different hybrid methods; and on application of MDFF to electron crystallography data.
Project description:We report the solution structure of Escherichia coli ?-galactosidase (?465 kDa), solved at ?3.2-Å resolution by using single-particle cryo-electron microscopy (cryo-EM). Densities for most side chains, including those of residues in the active site, and a catalytic Mg(2+) ion can be discerned in the map obtained by cryo-EM. The atomic model derived from our cryo-EM analysis closely matches the 1.7-Å crystal structure with a global rmsd of ?0.66 Å. There are significant local differences throughout the protein, with clear evidence for conformational changes resulting from contact zones in the crystal lattice. Inspection of the map reveals that although densities for residues with positively charged and neutral side chains are well resolved, systematically weaker densities are observed for residues with negatively charged side chains. We show that the weaker densities for negatively charged residues arise from their greater sensitivity to radiation damage from electron irradiation as determined by comparison of density maps obtained by using electron doses ranging from 10 to 30 e(-)/Å(2). In summary, we establish that it is feasible to use cryo-EM to determine near-atomic resolution structures of protein complexes (<500 kDa) with low symmetry, and that the residue-specific radiation damage that occurs with increasing electron dose can be monitored by using dose fractionation tools available with direct electron detector technology.
Project description:The appearance of ten high-resolution cryoelectron microscopy (cryo-EM) maps of proteins, ribosomes, and viruses was compared with the experimentally phased crystallographic electron density maps of four proteins. We found that maps calculated at a similar resolution by the two techniques are quite comparable in their appearance, although cryo-EM maps, even when sharpened, seem to be a little less detailed. An analysis of models fitted to the cryo-EM maps indicated the presence of significant problems in almost all of them, including incorrect geometry, clashes between atoms, and discrepancies between the map density and the fitted models. In particular, the treatment of the atomic displacement (B) factors was meaningless in almost all analyzed cryo-EM models. Stricter cryo-EM structure deposition standards and their better enforcement are needed.
Project description:Electron cryo-microscopy (cryo-EM) has played an increasingly important role in elucidating the structure and function of macromolecular assemblies in near native solution conditions. Typically, however, only non-atomic resolution reconstructions have been obtained for these large complexes, necessitating computational tools for integrating and extracting structural details. With recent advances in cryo-EM, maps at near-atomic resolutions have been achieved for several macromolecular assemblies from which models have been manually constructed. In this work, we describe a new interactive modeling toolkit called Gorgon targeted at intermediate to near-atomic resolution density maps (10-3.5 Å), particularly from cryo-EM. Gorgon's de novo modeling procedure couples sequence-based secondary structure prediction with feature detection and geometric modeling techniques to generate initial protein backbone models. Beyond model building, Gorgon is an extensible interactive visualization platform with a variety of computational tools for annotating a wide variety of 3D volumes. Examples from cryo-EM maps of Rotavirus and Rice Dwarf Virus are used to demonstrate its applicability to modeling protein structure.
Project description:Cryo-EM has revealed the structures of many challenging yet exciting macromolecular assemblies at near-atomic resolution (3-4.5Å), providing biological phenomena with molecular descriptions. However, at these resolutions, accurately positioning individual atoms remains challenging and error-prone. Manually refining thousands of amino acids - typical in a macromolecular assembly - is tedious and time-consuming. We present an automated method that can improve the atomic details in models that are manually built in near-atomic-resolution cryo-EM maps. Applying the method to three systems recently solved by cryo-EM, we are able to improve model geometry while maintaining the fit-to-density. Backbone placement errors are automatically detected and corrected, and the refinement shows a large radius of convergence. The results demonstrate that the method is amenable to structures with symmetry, of very large size, and containing RNA as well as covalently bound ligands. The method should streamline the cryo-EM structure determination process, providing accurate and unbiased atomic structure interpretation of such maps.
Project description:An increasing number of protein structures are determined by cryo-electron microscopy (cryo-EM) at near atomic resolution. However, tracing the main-chains and building full-atom models from EM maps of ~4-5?Å is still not trivial and remains a time-consuming task. Here, we introduce a fully automated de novo structure modeling method, MAINMAST, which builds three-dimensional models of a protein from a near-atomic resolution EM map. The method directly traces the protein's main-chain and identifies C? positions as tree-graph structures in the EM map. MAINMAST performs significantly better than existing software in building global protein structure models on data sets of 40 simulated density maps at 5?Å resolution and 30 experimentally determined maps at 2.6-4.8?Å resolution. In another benchmark of building missing fragments in protein models for EM maps, MAINMAST builds fragments of 11-161 residues long with an average RMSD of 2.68?Å.
Project description:As electron cryo-microscopy (cryo-EM) can now frequently achieve near atomic resolution, accurate interpretation of these density maps in terms of atomistic detail has become paramount in deciphering macromolecular structure and function. However, there are few software tools for modeling protein structure from cryo-EM density maps in this resolution range. Here, we present an extension of our original Pathwalking protocol, which can automatically trace a protein backbone directly from a near-atomic resolution (3-6Å) density map. The original Pathwalking approach utilized a Traveling Salesman Problem solver for backbone tracing, but manual adjustment was still required during modeling. In the new version, human intervention is minimized and we provide a more robust approach for backbone modeling. This includes iterative secondary structure identification, termini detection and the ability to model multiple subunits without prior segmentation. Overall, the new Pathwalking procedure provides a more complete and robust tool for annotating protein structure function in near-atomic resolution density maps.