Electron Microscopy Density Maps Research Articles

Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration.

Understanding the protein structures is invaluable in various biomedical applications, such as vaccine development. Protein structure model building from experimental electron density maps is a time-consuming and labor-intensive task. To address the challenge, machine learning approaches have been proposed to automate this process. Currently, the majority of the experimental maps in the database lack atomic resolution features, making it challenging for machine learning-based methods to precisely determine protein structures from cryogenic electron microscopy density maps. On the other hand, protein structure prediction methods, such as AlphaFold2, leverage evolutionary information from protein sequences and have recently achieved groundbreaking accuracy. However, these methods often require manual refinement, which is labor intensive and time consuming. In this study, we present DeepTracer-Refine, an automated method that refines AlphaFold predicted structures by aligning them to DeepTracers modeled structure. Our method was evaluated on 39 multi-domain proteins and we improved the average residue coverage from 78.2 to 90.0% and average local Distance Difference Test score from 0.67 to 0.71. We also compared DeepTracer-Refine with Phenixs AlphaFold refinement and demonstrated that our method not only performs better when the initial AlphaFold model is less precise but also surpasses Phenix in run-time performance.

Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting.

Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledge-driven or artificial intelligence-driven and physics-guided computational methods to build, fit, and refine molecular structures. Going beyond a single stationary-structure determination scheme, it is becoming more common to interpret the experimental data with an ensemble of models that contributes to an average observation. Hence, there is a need to decide on the quality of an ensemble of protein structures on-the-fly while refining them against the density maps. We introduce such an adaptive decision-making scheme during the molecular dynamics flexible fitting (MDFF) of biomolecules. Using RADICAL-Cybertools, the new RADICAL augmented MDFF implementation (R-MDFF) is examined in high-performance computing environments for refinement of two prototypical protein systems, adenylate kinase and carbon monoxide dehydrogenase. For these test cases, use of multiple replicas in flexible fitting with adaptive decision making in R-MDFF improves the overall correlation to the density by 40% relative to the refinements of the brute-force MDFF. The improvements are particularly significant at high, 2-3 Å map resolutions. More importantly, the ensemble model captures key features of biologically relevant molecular dynamics that are inaccessible to a single-model interpretation. Finally, the pipeline is applicable to systems of growing sizes, which is demonstrated using ensemble refinement of capsid proteins from the chimpanzee adenovirus. The overhead for decision making remains low and robust to computing environments. The software is publicly available on GitHub and includes a short user guide to install R-MDFF on different computing environments, from local Linux-based workstations to high-performance computing environments.

Protein model refinement for cryo-EM maps using AlphaFold2 and the DAQ score.

As more protein structure models have been determined from cryogenic electron microscopy (cryo-EM) density maps, establishing how to evaluate the model accuracy and how to correct models in cases where they contain errors is becoming crucial to ensure the quality of the structural models deposited in the public database, the PDB. Here, a new protocol is presented for evaluating a protein model built from a cryo-EM map and applying local structure refinement in the case where the model has potential errors. Firstly, model evaluation is performed using a deep-learning-based model-local map assessment score, DAQ, that has recently been developed. The subsequent local refinement is performed by a modified AlphaFold2 procedure, in which a trimmed template model and a trimmed multiple sequence alignment are provided as input to control which structure regions to refine while leaving other more confident regions of the model intact. A benchmark study showed that this protocol, DAQ-refine, consistently improves low-quality regions of the initial models. Among 18 refined models generated for an initial structure, DAQ shows a high correlation with model quality and can identify the best accurate model for most of the tested cases. The improvements obtained by DAQ-refine were on average larger than other existing methods.

HEMNMA-3D: Cryo Electron Tomography Method Based on Normal Mode Analysis to Study Continuous Conformational Variability of Macromolecular Complexes.

Cryogenic electron tomography (cryo-ET) allows structural determination of biomolecules in their native environment (in situ). Its potential of providing information on the dynamics of macromolecular complexes in cells is still largely unexploited, due to the challenges of the data analysis. The crowded cell environment and continuous conformational changes of complexes make difficult disentangling the data heterogeneity. We present HEMNMA-3D, which is, to the best of our knowledge, the first method for analyzing cryo electron subtomograms in terms of continuous conformational changes of complexes. HEMNMA-3D uses a combination of elastic and rigid-body 3D-to-3D iterative alignments of a flexible 3D reference (atomic structure or electron microscopy density map) to match the conformation, orientation, and position of the complex in each subtomogram. The elastic matching combines molecular mechanics simulation (Normal Mode Analysis of the 3D reference) and experimental, subtomogram data analysis. The rigid-body alignment includes compensation for the missing wedge, due to the limited tilt angle of cryo-ET. The conformational parameters (amplitudes of normal modes) of the complexes in subtomograms obtained through the alignment are processed to visualize the distribution of conformations in a space of lower dimension (typically, 2D or 3D) referred to as space of conformations. This allows a visually interpretable insight into the dynamics of the complexes, by calculating 3D averages of subtomograms with similar conformations from selected (densest) regions and by recording movies of the 3D reference's displacement along selected trajectories through the densest regions. We describe HEMNMA-3D and show its validation using synthetic datasets. We apply HEMNMA-3D to an experimental dataset describing in situ nucleosome conformational variability. HEMNMA-3D software is available freely (open-source) as part of ContinuousFlex plugin of Scipion V3.0 (http://scipion.i2pc.es).

Protein Structure Modeling from Cryo-EM Map Using MAINMAST and MAINMAST-GUI Plugin.

Protein structure modeling is a fundamental step for the structural interpretation of 3D electron microscopy (EM) density map. Recently, because of the significant progress of the cryo-EM technique, protein structure modeling tools are needed for EM maps determined around 4Å resolution. At this rear atomic resolution, finding main-chain structure and assigning the amino acid sequence into EM map are still challenging problems. We have developed a de novo modeling tool named MAINMAST for EM maps at near-atomic resolution (~4.5Å). MAINMAST can trace the backbone structure of a protein from an EM density map directory. We also developed a Graphical User Interface (GUI) plugin of MAINMAST for the UCSF Chimera so that users can monitor structures at each step of a modeling procedure. In this chapter, we demonstrate two examples of the use of MAINMAST software and MAINMAST-GUI to build protein structure model from an EM density map. MAINMAST software and MAINMAST-GUI plugin are freely available for academic users at http://kiharalab.org/mainmast/index.html .

Structural Biology of Telomerase.

Telomerase is a DNA polymerase that extends the 3' ends of chromosomes by processively synthesizing multiple telomeric repeats. It is a unique ribonucleoprotein (RNP) containing a specialized telomerase reverse transcriptase (TERT) and telomerase RNA (TER) with its own template and other elements required with TERT for activity (catalytic core), as well as species-specific TER-binding proteins important for biogenesis and assembly (core RNP); other proteins bind telomerase transiently or constitutively to allow association of telomerase and other proteins with telomere ends for regulation of DNA synthesis. Here we describe how nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography of TER and protein domains helped define the structure and function of the core RNP, laying the groundwork for interpreting negative-stain and cryo electron microscopy (cryo-EM) density maps of Tetrahymena thermophila and human telomerase holoenzymes. As the resolution has improved from ∼30 Å to ∼5 Å, these studies have provided increasingly detailed information on telomerase architecture and mechanism.

ICn3D, a web-based 3D viewer for sharing 1D/2D/3D representations of biomolecular structures

Build a web-based 3D molecular structure viewer focusing on interactive structural analysis. iCn3D (I-see-in-3D) can simultaneously show 3D structure, 2D molecular contacts and 1D protein and nucleotide sequences through an integrated sequence/annotation browser. Pre-defined and arbitrary molecular features can be selected in any of the 1D/2D/3D windows as sets of residues and these selections are synchronized dynamically in all displays. Biological annotations such as protein domains, single nucleotide variations, etc. can be shown as tracks in the 1D sequence/annotation browser. These customized displays can be shared with colleagues or publishers via a simple URL. iCn3D can display structure-structure alignments obtained from NCBI's VAST+ service. It can also display the alignment of a sequence with a structure as identified by BLAST, and thus relate 3D structure to a large fraction of all known proteins. iCn3D can also display electron density maps or electron microscopy (EM) density maps, and export files for 3D printing. The following example URL exemplifies some of the 1D/2D/3D representations: https://www.ncbi.nlm.nih.gov/Structure/icn3d/full.html?mmdbid=1TUP&showanno=1&show2d=1&showsets=1. iCn3D is freely available to the public. Its source code is available at https://github.com/ncbi/icn3d. Supplementary data are available at Bioinformatics online.

Dynamic analysis of ribosome by a movie made from many three-dimensional electron-microscopy density maps.

The atomic models of the 70S ribosome including the bound molecules were built from many 3D-EM density maps. The positions and conformations of the bound molecules were determined by fitting them to the regions in the density maps which remained after fitting the 70S ribosome. Then, using these atomic models, a movie for the elongation cycle was made. For determining the sequential order in which the models appeared in the movie, the knowledge about the bound molecules and the ratchet angles were used. The movie revealed several interesting points which were not apparent from each density map, suggesting the usefulness of a movie made from many 3D-EM density maps.

Development of a new protein labeling system to map subunits and domains of macromolecular complexes for electron microscopy.

Several gene fusion technologies have been successfully applied to label particular subunits or domains within macromolecular complexes to enable positional mapping of electron microscopy (EM) density maps, but exogenous fusion of a protein domain into the target polypeptide can cause unwanted structural and functional outcomes. Fab fragments from antibodies can be used as labeling reagents during EM visualization without gene manipulation of the target protein, but this method requires a panel of high-affinity antibodies that recognize a wide variety of epitopes. Linear peptide tags and their anti-tag antibodies can be used but they have a limited mapping ability as their placement is usually limited to the terminal regions of a protein. The PA dodecapeptide epitope tag (GVAMPGAEDDVV), forms a tight β-turn in the antigen binding pocket of its antibody (NZ-1). This capability allows for insertion of the PA tag into various surface-exposed loops within a multi-domain cell adhesion receptor, αIIbβ3 integrin. We confirmed that the purified PA-tagged integrin ectodomain fragments can form a stable complex with NZ-1 Fab. Negative stain EM of the various integrin-NZ-1 complexes revealed that a majority of the particles exhibited a clear density corresponding to the NZ-1 Fab; and the positions of the bound Fab were in good agreement with the predicted location of the inserted PA tag. The high-affinity and insertion-compatibility of the PA tag system allowed us to develop a new EM labeling methodology applicable to proteins for which good antibodies are not available.

Rapid automated superposition of shapes and macromolecular models using spherical harmonics.

A rapid algorithm to superimpose macromolecular models in Fourier space is proposed and implemented (SUPALM). The method uses a normalized integrated cross-term of the scattering amplitudes as a proximity measure between two three-dimensional objects. The reciprocal-space algorithm allows for direct matching of heterogeneous objects including high- and low-resolution models represented by atomic coordinates, beads or dummy residue chains as well as electron microscopy density maps and inhomogeneous multi-phase models (e.g. of protein-nucleic acid complexes). Using spherical harmonics for the computation of the amplitudes, the method is up to an order of magnitude faster than the real-space algorithm implemented in SUPCOMB by Kozin & Svergun [J. Appl. Cryst. (2001 ▸), 34, 33-41]. The utility of the new method is demonstrated in a number of test cases and compared with the results of SUPCOMB. The spherical harmonics algorithm is best suited for low-resolution shape models, e.g. those provided by solution scattering experiments, but also facilitates a rapid cross-validation against structural models obtained by other methods.

Denoising of high-resolution single-particle electron-microscopy density maps by their approximation using three-dimensional Gaussian functions.

Cryo-electron microscopy (cryo-EM) of frozen-hydrated preparations of isolated macromolecular complexes is the method of choice to obtain the structure of complexes that cannot be easily studied by other experimental methods due to their flexibility or large size. An increasing number of macromolecular structures are currently being obtained at subnanometer resolution but the interpretation of structural details in such EM-derived maps is often difficult because of noise at these high-frequency signal components that reduces their contrast. In this paper, we show that the method for EM density-map approximation using Gaussian functions can be used for denoising of single-particle EM maps of high (typically subnanometer) resolution. We show its denoising performance using simulated and experimental EM density maps of several complexes.

StructMap: Elastic Distance Analysis of Electron Microscopy Maps for Studying Conformational Changes

Single-particle electron microscopy (EM) has been shown to be very powerful for studying structures and associated conformational changes of macromolecular complexes. In the context of analyzing conformational changes of complexes, distinct EM density maps obtained by image analysis and three-dimensional (3D) reconstruction are usually analyzed in 3D for interpretation of structural differences. However, graphic visualization of these differences based on a quantitative analysis of elastic transformations (deformations) among density maps has not been done yet due to a lack of appropriate methods. Here, we present an approach that allows such visualization. This approach is based on statistical analysis of distances among elastically aligned pairs of EM maps (one map is deformed to fit the other map), and results in visualizing EM maps as points in a lower-dimensional distance space. The distances among points in the new space can be analyzed in terms of clusters or trajectories of points related to potential conformational changes. The results of the method are shown with synthetic and experimental EM maps at different resolutions.

Versatility of Approximating Single-Particle Electron Microscopy Density Maps Using Pseudoatoms and Approximation-Accuracy Control.

Three-dimensional Gaussian functions have been shown useful in representing electron microscopy (EM) density maps for studying macromolecular structure and dynamics. Methods that require setting a desired number of Gaussian functions or a maximum number of iterations may result in suboptimal representations of the structure. An alternative is to set a desired error of approximation of the given EM map and then optimize the number of Gaussian functions to achieve this approximation error. In this article, we review different applications of such an approach that uses spherical Gaussian functions of fixed standard deviation, referred to as pseudoatoms. Some of these applications use EM-map normal mode analysis (NMA) with elastic network model (ENM) (applications such as predicting conformational changes of macromolecular complexes or exploring actual conformational changes by normal-mode-based analysis of experimental data) while some other do not use NMA (denoising of EM density maps). In applications based on NMA and ENM, the advantage of using pseudoatoms in EM-map coarse-grain models is that the ENM springs are easily assigned among neighboring grains thanks to their spherical shape and uniformed size. EM-map denoising based on the map coarse-graining was so far only shown using pseudoatoms as grains.

Free-energy landscape of reverse tRNA translocation through the ribosome analyzed by electron microscopy density maps and molecular dynamics simulations.

To understand the mechanism of reverse tRNA translocation in the ribosome, all-atom molecular dynamics simulations of the ribosome-tRNAs-mRNA-EFG complex were performed. The complex at the post-translocational state was directed towards the translocational and pre-translocational states by fitting the complex into cryo-EM density maps. Between a series of the fitting simulations, umbrella sampling simulations were performed to obtain the free-energy landscape. Multistep structural changes, such as a ratchet-like motion and rotation of the head of the small subunit were observed. The free-energy landscape showed that there were two main free-energy barriers: one between the post-translocational and intermediate states, and the other between the pre-translocational and intermediate states. The former corresponded to a clockwise rotation, which was coupled to the movement of P-tRNA over the P/E-gate made of G1338, A1339 and A790 in the small subunit. The latter corresponded to an anticlockwise rotation of the head, which was coupled to the location of the two tRNAs in the hybrid state. This indicates that the coupled motion of the head rotation and tRNA translocation plays an important role in opening and closing of the P/E-gate during the ratchet-like movement in the ribosome. Conformational change of EF-G was interpreted to be the result of the combination of the external motion by L12 around an axis passing near the sarcin-ricin loop, and internal hinge-bending motion. These motions contributed to the movement of domain IV of EF-G to maintain its interaction with A/P-tRNA.

Telomerase structure

The telomerase reverse transcriptase has an essential role in telomere maintenance and in cancer biology. Progress during the last year has revealed the three-dimensional architecture of both human and ciliate telomerase at about 25Å resolution, obtained using single particle electron microscopy (EM). The structural analysis of the two holoenzyme complexes isolated from cells shows that whilst the ciliate telomerase is monomeric, the human telomerase is dimeric and only functional as a dimer. We critically discuss the approaches taken to assign the location of protein and RNA subunits, as well as fitting the crystal structure of the catalytic protein subunit in the medium resolution EM density maps. Comparison of the two structural interpretations reveals not only a common RNA/reverse transcriptase core, but also significant differences due to different RNA subunit size and protein composition. These differences suggest that the oligomeric state and subunit composition of telomerase in evolutionary distant organism have evolved.

Three-Dimensional Organization of Troponin on Cardiac Muscle Thin Filaments in the Relaxed State

Muscle contraction is regulated by troponin-tropomyosin, which blocks and unblocks myosin binding sites on actin. To elucidate this regulatory mechanism, the three-dimensional organization of troponin and tropomyosin on the thin filament must be determined. Although tropomyosin is well defined in electron microscopy helical reconstructions of thin filaments, troponin density is mostly lost. Here, we determined troponin organization on native relaxed cardiac muscle thin filaments by applying single particle reconstruction procedures to negatively stained specimens. Multiple reference models led to the same final structure, indicating absence of model bias in the procedure. The new reconstructions clearly showed F-actin, tropomyosin, and troponin densities. At the 25 Å resolution achieved, troponin was considerably better defined than in previous reconstructions. The troponin density closely resembled the shape of troponin crystallographic structures, facilitating detailed interpretation of the electron microscopy density map. The orientation of troponin-T and the troponin core domain established troponin polarity. Density attributable to the troponin-I mobile regulatory domain was positioned where it could hold tropomyosin in its blocking position on actin, thus suggesting the underlying structural basis of thin filament regulation. Our previous understanding of thin filament regulation had been limited to known movements of tropomyosin that sterically block and unblock myosin binding sites on actin. We now show how troponin, the Ca2+ sensor, may control these movements, ultimately determining whether muscle contracts or relaxes.

1P127 Model of reverse tRNA translocation through the ribosome analyzed by electron microscopy density maps and molecular dynamics simulations(05B. Nucleic acid : Interaction & Complex formation,Poster,The 52nd Annual Meeting of the Biophysical Society of Japan(BSJ2014))

1P127 Model of reverse tRNA translocation through the ribosome analyzed by electron microscopy density maps and molecular dynamics simulations(05B. Nucleic acid : Interaction & Complex formation,Poster,The 52nd Annual Meeting of the Biophysical Society of Japan(BSJ2014))

Atomic Structure and Handedness of the Building Block of a Biological Assembly

Noncovalent supramolecular assemblies possess in general several unique subunit-subunit interfaces.The basic building block of such an assembly consists of several subunits and contains all unique interfaces. Atomic-resolution structures of monomeric subunits are typically accessed by crystallography or solution NMR and fitted into electron microscopy density maps. However, the structure of the intact building block in the assembled state remains unknown with this hybrid approach. Here, we present the solid-state NMR atomic structure of the building block of the type III secretion system needle. The building block structure consists of a homotetrameric subunit complex with three unique supramolecular interfaces. Side-chain positions at the interfaces were solved at atomic detail. The high-resolution structure reveals unambiguously the helical handedness of the assembly, determined to be right-handed for the type III secretion system needle.Additionally, the axial rise per subunit could be extracted from the tetramer structure and independently validated by mass-per-length measurements.

IMODFIT: Efficient and robust flexible fitting based on vibrational analysis in internal coordinates

Here, we employed the collective motions extracted from Normal Mode Analysis (NMA) in internal coordinates (torsional space) for the flexible fitting of atomic-resolution structures into electron microscopy (EM) density maps. The proposed methodology was validated using a benchmark of simulated cases, highlighting its robustness over the full range of EM resolutions and even over coarse-grained representations. A systematic comparison with other methods further showcased the advantages of this proposed methodology, especially at medium to lower resolutions. Using this method, computational costs and potential overfitting problems are naturally reduced by constraining the search in low-frequency NMA space, where covalent geometry is implicitly maintained. This method also effectively captures the macromolecular changes of a representative set of experimental test cases. We believe that this novel approach will extend the currently available EM hybrid methods to the atomic-level interpretation of large conformational changes and their functional implications.

Fitting multimeric protein complexes into electron microscopy maps using 3D Zernike descriptors.

A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three-dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root-mean-square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.