cryo-EM Map Research Articles

Deep learning-based local quality estimation for protein structure models from cryo-EM maps

In the recent decade, an increasing number of cryo-electron microscopy (cryo-EM) maps were determined to model the tertiary structures of biomolecules. Although the resolution of determined cryo-EM maps is improving in general, there are still many cases where amino acids of a protein were assigned to the map with different confidence levels, including those with relatively high ambiguity. A common error, particularly when side-chain density is not well defined and there are poorly ordered loops between secondary structures, is for the sequence of the model to become out of register.

Curiosity: a tool for exploring density features in crystallographic and cryoEM maps

A key component of macromolecular structure determination from crystallographic or cryoEM density maps is the discovery and repair of modeling errors. In the case of chemically and physically unreasonable arrangements of atoms, we are informed by the clashscore, Ramachandran plots, bond distance/angle/torsion/chirality/planarity outliers, and so forth. Some tools for identifying chemically unlikely but biologically important structural motifs such as Hoogsteen base pairing have also been developed.

A comprehensive landscape of 60S ribosome biogenesis factors.

SUMMARYEukaryotic ribosome biogenesis is facilitated and regulated by numerous ribosome biogenesis factors (RBFs). High-resolution cryoelectron microscopy (cryo-EM) maps have defined the molecular interactions of RBFs during maturation, but many transient and dynamic interactions, particularly during early assembly, remain uncharacterized. Using quantitative proteomics and crosslinking coupled to mass spectrometry (XL-MS) data from an extensive set of pre-ribosomal particles, we derive a comprehensive and time-resolved interaction map of RBF engagement during 60S maturation. We localize 22 previously unmapped RBFs to specific biogenesis intermediates and validate our results by mapping the catalytic activity of the methyltransferases Bmt2 and Rcm1 to their predicted nucleolar 60S intermediates. Our analysis reveals the interaction sites for the RBFs Noc2 and Ecm1 and elucidates the interaction map and timing of 60S engagement by the DEAD-box ATPases Dbp9 and Dbp10. Our data provide a powerful resource for future studies of 60S ribosome biogenesis.

Enhancement of Cryo-EM maps by a multiscale tubular filter.

We present an approach to enhance cryo-electron microscopy (cryo-EM) postprocessed maps based on a multiscale tubular filter. The method determines a tubularness measure locally by the analysis of the eigenvalues of the Hessian matrix. This information is used to enhance elongated local structures and to attenuate blob-like and plate-like structures. The approach, thus, introduces a priori information in the reconstructions to improve their interpretability and analysis at high-resolution. The proposed method has been tested with simulated and real cryo-EM maps including recent reconstructions of the SARS-CoV-2. Our results show that our methods can improve obtained reconstructions.

Atomic structure of Lanreotide nanotubes revealed by cryo-EM

Functional and versatile nano- and microassemblies formed by biological molecules are found at all levels of life, from cell organelles to full organisms. Understanding the chemical and physicochemical determinants guiding the formation of these assemblies is crucial not only to understand the biological processes they carry out but also to mimic nature. Among the synthetic peptides forming well-defined nanostructures, the octapeptide Lanreotide has been considered one of the best characterized, in terms of both the atomic structure and its self-assembly process. In the present work, we determined the atomic structure of Lanreotide nanotubes at 2.5-Å resolution by cryoelectron microscopy (cryo-EM). Surprisingly, the asymmetric unit in the nanotube contains eight copies of the peptide, forming two tetramers. There are thus eight different environments for the peptide, and eight different conformations in the nanotube. The structure built from the cryo-EM map is strikingly different from the molecular model, largely based on X-ray fiber diffraction, proposed 20 y ago. Comparison of the nanotube with a crystal structure at 0.83-Å resolution of a Lanreotide derivative highlights the polymorphism for this peptide family. This work shows once again that higher-order assemblies formed by even well-characterized small peptides are very difficult to predict.

Refinement of AlphaFold2 models against experimental and hybrid cryo-EM density maps

Abstract Recent breakthroughs in deep learning-based protein structure prediction show that it is possible to obtain highly accurate models for a wide range of difficult protein targets for which only the amino acid sequence is known. The availability of accurately predicted models from sequences can potentially revolutionise many modelling approaches in structural biology, including the interpretation of cryo-EM density maps. Although atomic structures can be readily solved from cryo-EM maps of better than 4 Å resolution, it is still challenging to determine accurate models from lower-resolution density maps. Here, we report on the benefits of models predicted by AlphaFold2 (the best-performing structure prediction method at CASP14) on cryo-EM refinement using the Phenix refinement suite for AlphaFold2 models. To study the robustness of model refinement at a lower resolution of interest, we introduced hybrid maps (i.e. experimental cryo-EM maps) filtered to lower resolutions by real-space convolution. The AlphaFold2 models were refined to attain good accuracies above 0.8 TM scores for 9 of the 13 cryo-EM maps. TM scores improved for AlphaFold2 models refined against all 13 cryo-EM maps of better than 4.5 Å resolution, 8 hybrid maps of 6 Å resolution, and 3 hybrid maps of 8 Å resolution. The results show that it is possible (at least with the Phenix protocol) to extend the refinement success below 4.5 Å resolution. We even found isolated cases in which resolution lowering was slightly beneficial for refinement, suggesting that high-resolution cryo-EM maps might sometimes trap AlphaFold2 models in local optima.

Image processing tools for the validation of CryoEM maps.

The number of maps deposited in public databases (Electron Microscopy Data Bank, EMDB) determined by cryo-electron microscopy has quickly grown in recent years. With this rapid growth, it is critical to guarantee their quality. So far, map validation has primarily focused on the agreement between maps and models. From the image processing perspective, the validation has been mostly restricted to using two half-maps and the measurement of their internal consistency. In this article, we suggest that map validation can be taken much further from the point of view of image processing if 2D classes, particles, angles, coordinates, defoci, and micrographs are also provided. We present a progressive validation scheme that qualifies a result validation status from 0 to 5 and offers three optional qualifiers (A, W, and O) that can be added. The simplest validation state is 0, while the most complete would be 5AWO. This scheme has been implemented in a website https://biocomp.cnb.csic.es/EMValidationService/ to which reconstructed maps and their ESI can be uploaded.

Extraction of Protein Dynamics Hidden in Cryo-EM Maps Using Deep Learning

Extraction of Protein Dynamics Hidden in Cryo-EM Maps Using Deep Learning

Correction: Image processing tools for the validation of CryoEM maps

Correction: Image processing tools for the validation of CryoEM maps

Structural basis of the partially open central gate in the human CNGA1/CNGB1 channel explained by additional density for calmodulin in cryo-EM map

The recently reported structure of the human CNGA1/CNGB1 CNG channel in the open state (Xue et al., 2021a) shows that one CNGA1 and one CNGB1 subunit do not open the central hydrophobic gate completely upon cGMP binding. This is different from what has been reported for CNGA homomeric channels (Xue et al., 2021b; Zheng et al., 2020). In seeking to understand how this difference is due to the presence of the CNGB1 subunit, we find that the deposited density map (Xue et al., 2021a) (EMDB 24465) contains an additional density not reported in the images of the original publication. This additional density fits well the structure of calmodulin (CaM), and it unambiguously connects the newly identified D-helix of CNGB1 to one of the CNGA1 helices (A1R) participating in the coiled-coil region. Interestingly, the CNGA1 subunit that engages in the interaction with this additional density is the one that, together with CNGB1, does not open completely the central gate. The sequence of the D-helix of CNGB1 contains a known CaM-binding site of exquisitely high affinity - named CaM2 (Weitz et al., 1998) -, and thus the presence of CaM in that region is not surprising. The mechanism through which CaM reduces currents across the membrane by acting on the native channel (Bauer, 1996; Hsu and Molday, 1993; Weitz et al., 1998) remains unclear. We suggest that the presence of CaM may explain the partially open central gate reported by Xue et al. (2021a). The structure of the open and closed states of the CNGA1/CNGB1 channel may be different with and without CaM present.

EMDA: A Python package for Electron Microscopy Data Analysis

An open-source Python library EMDA for cryo-EM map and model manipulation is presented with a specific focus on validation. The use of several functionalities in the library is presented through several examples. The utility of local correlation as a metric for identifying map-model differences and unmodeled regions in maps, and how it is used as a metric of map-model validation is demonstrated. The mapping of local correlation to individual atoms, and its use to draw insights on local signal variations are discussed. EMDA’s likelihood-based map overlay is demonstrated by carrying out a superposition of two domains in two related structures. The overlay is carried out first to bring both maps into the same coordinate frame and then to estimate the relative movement of domains. Finally, the map magnification refinement in EMDA is presented with an example to highlight the importance of adjusting the map magnification in structural comparison studies.

Novel Bent Conformation of CD4 Induced by HIV-1 Inhibitor Indirectly Prevents Productive Viral Attachment

GSK3732394 is a multi-specific biologic inhibitor of HIV entry currently under clinical evaluation. A key component of this molecule is an adnectin (6940_B01) that binds to CD4 and inhibits downstream actions of gp160. Studies were performed to determine the binding site of the adnectin on CD4 and to understand the mechanism of inhibition. Using hydrogen–deuterium exchange with mass spectrometry (HDX), CD4 peptides showed differential rates of deuteration (either enhanced or slowed) in the presence of the adnectin that mapped predominantly to the interface of domains 2 and 3 (D2-D3). In addition, an X-ray crystal structure of an ibalizumab Fab/CD4(D1-D4)/adnectin complex revealed an extensive interface between the adnectin and residues on CD4 domains D2-D4 that stabilize a novel T-shaped CD4 conformation. A cryo-EM map of the gp140/CD4/GSK3732394 complex clearly shows the bent conformation for CD4 while bound to gp140. Mutagenic analyses on CD4 confirmed that amino acid F202 forms a key interaction with the adnectin. In addition, amino acid L151 was shown to be a critical indirect determinant of the specificity for binding to the human CD4 protein over related primate CD4 molecules, as it appears to modulate CD4′s flexibility to adopt the adnectin-bound conformation. The significant conformational change of CD4 upon adnectin binding brings the D1 domain of CD4 in proximity to the host cell membrane surface, thereby re-orienting the gp120 binding site in a direction that is inaccessible to incoming virus due to a steric clash between gp160 trimers on the virus surface and the target cell membrane.

Three-Dimensional Graph Matching to Identify Secondary Structure Correspondence of Medium-Resolution Cryo-EM Density Maps.

Cryo-electron microscopy (cryo-EM) is a structural technique that has played a significant role in protein structure determination in recent years. Compared to the traditional methods of X-ray crystallography and NMR spectroscopy, cryo-EM is capable of producing images of much larger protein complexes. However, cryo-EM reconstructions are limited to medium-resolution (~4–10 Å) for some cases. At this resolution range, a cryo-EM density map can hardly be used to directly determine the structure of proteins at atomic level resolutions, or even at their amino acid residue backbones. At such a resolution, only the position and orientation of secondary structure elements (SSEs) such as α-helices and β-sheets are observable. Consequently, finding the mapping of the secondary structures of the modeled structure (SSEs-A) to the cryo-EM map (SSEs-C) is one of the primary concerns in cryo-EM modeling. To address this issue, this study proposes a novel automatic computational method to identify SSEs correspondence in three-dimensional (3D) space. Initially, through a modeling of the target sequence with the aid of extracting highly reliable features from a generated 3D model and map, the SSEs matching problem is formulated as a 3D vector matching problem. Afterward, the 3D vector matching problem is transformed into a 3D graph matching problem. Finally, a similarity-based voting algorithm combined with the principle of least conflict (PLC) concept is developed to obtain the SSEs correspondence. To evaluate the accuracy of the method, a testing set of 25 experimental and simulated maps with a maximum of 65 SSEs is selected. Comparative studies are also conducted to demonstrate the superiority of the proposed method over some state-of-the-art techniques. The results demonstrate that the method is efficient, robust, and works well in the presence of errors in the predicted secondary structures of the cryo-EM images.

Combining Cryo-EM Density Map and Residue Contact for Protein Secondary Structure Topologies.

Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments and a set of traces of secondary structures in three-dimensional space. In order to enhance accuracy in ranking secondary structure topologies, we explored a method that combines three sources of information: a set of sequence segments in 1D, a set of amino acid contact pairs in 2D, and a set of traces in 3D at the secondary structure level. A test of fourteen cases shows that the accuracy of predicted secondary structures is critical for deriving topologies. The use of significant long-range contact pairs is most effective at enriching the rank of the maximum-match topology for proteins with a large number of secondary structures, if the secondary structure prediction is fairly accurate. It was observed that the enrichment depends on the quality of initial topology candidates in this approach. We provide detailed analysis in various cases to show the potential and challenge when combining three sources of information.

A Tool for Segmentation of Secondary Structures in 3D Cryo-EM Density Map Components Using Deep Convolutional Neural Networks.

Although cryo-electron microscopy (cryo-EM) has been successfully used to derive atomic structures for many proteins, it is still challenging to derive atomic structures when the resolution of cryo-EM density maps is in the medium resolution range, such as 5–10 Å. Detection of protein secondary structures, such as helices and β-sheets, from cryo-EM density maps provides constraints for deriving atomic structures from such maps. As more deep learning methodologies are being developed for solving various molecular problems, effective tools are needed for users to access them. We have developed an effective software bundle, DeepSSETracer, for the detection of protein secondary structure from cryo-EM component maps in medium resolution. The bundle contains the network architecture and a U-Net model trained with a curriculum and gradient of episodic memory (GEM). The bundle integrates the deep neural network with the visualization capacity provided in ChimeraX. Using a Linux server that is remotely accessed by Windows users, it takes about 6 s on one CPU and one GPU for the trained deep neural network to detect secondary structures in a cryo-EM component map containing 446 amino acids. A test using 28 chain components of cryo-EM maps shows overall residue-level F1 scores of 0.72 and 0.65 to detect helices and β-sheets, respectively. Although deep learning applications are built on software frameworks, such as PyTorch and Tensorflow, our pioneer work here shows that integration of deep learning applications with ChimeraX is a promising and effective approach. Our experiments show that the F1 score measured at the residue level is an effective evaluation of secondary structure detection for individual classes. The test using 28 cryo-EM component maps shows that DeepSSETracer detects β-sheets more accurately than Emap2sec+, with a weighted average residue-level F1 score of 0.65 and 0.42, respectively. It also shows that Emap2sec+ detects helices more accurately than DeepSSETracer with a weighted average residue-level F1 score of 0.77 and 0.72 respectively.

De novo identification of mammalian ciliary motility proteins using cryo-EM

SUMMARYDynein-decorated doublet microtubules (DMTs) are critical components of the oscillatory molecular machine of cilia, the axoneme, and have luminal surfaces patterned periodically by microtubule inner proteins (MIPs). Here we present an atomic model of the 48-nm repeat of a mammalian DMT, derived from a cryoelectron microscopy (cryo-EM) map of the complex isolated from bovine respiratory cilia. The structure uncovers principles of doublet microtubule organization and features specific to vertebrate cilia, including previously unknown MIPs, a luminal bundle of tektin filaments, and a pentameric dynein-docking complex. We identify a mechanism for bridging 48- to 24-nm periodicity across the microtubule wall and show that loss of the proteins involved causes defective ciliary motility and laterality abnormalities in zebrafish and mice. Our structure identifies candidate genes for diagnosis of ciliopathies and provides a framework to understand their functions in driving ciliary motility.

Redeployment of automated MrBUMP search-model identification for map fitting in cryo-EM.

In crystallography, the phase problem can often be addressed by the careful preparation of molecular-replacement search models. This has led to the development of pipelines such as MrBUMP that can automatically identify homologous proteins from an input sequence and edit them to focus on the areas that are most conserved. Many of these approaches can be applied directly to cryo-EM to help discover, prepare and correctly place models (here called cryo-EM search models) into electrostatic potential maps. This can significantly reduce the amount of manual model building that is required for structure determination. Here, MrBUMP is repurposed to fit automatically obtained PDB-derived chains and domains into cryo-EM maps. MrBUMP was successfully able to identify and place cryo-EM search models across a range of resolutions. Methods such as map segmentation are also explored as potential routes to improved performance. Map segmentation was also found to improve the effectiveness of the pipeline for higher resolution (<8 Å) data sets.

Structures of synthetic nanobody–SARS-CoV-2 receptor-binding domain complexes reveal distinct sites of interaction

Combating the worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the emergence of new variants demands understanding of the structural basis of the interaction of antibodies with the SARS-CoV-2 receptor-binding domain (RBD). Here, we report five X-ray crystal structures of sybodies (synthetic nanobodies) including those of binary and ternary complexes of Sb16–RBD, Sb45–RBD, Sb14–RBD–Sb68, and Sb45–RBD–Sb68, as well as unliganded Sb16. These structures reveal that Sb14, Sb16, and Sb45 bind the RBD at the angiotensin-converting enzyme 2 interface and that the Sb16 interaction is accompanied by a large conformational adjustment of complementarity-determining region 2. In contrast, Sb68 interacts at the periphery of the SARS-CoV-2 RBD–angiotensin-converting enzyme 2 interface. We also determined cryo-EM structures of Sb45 bound to the SARS-CoV-2 spike protein. Superposition of the X-ray structures of sybodies onto the trimeric spike protein cryo-EM map indicates that some sybodies may bind in both “up” and “down” configurations, but others may not. Differences in sybody recognition of several recently identified RBD variants are explained by these structures.

Validation, analysis and annotation of cryo-EM structures.

The process of turning 2D micrographs into 3D atomic models of the imaged macromolecules has been under rapid development and scrutiny in the field of cryo-EM. Here, some important methods for validation at several stages in this process are described. Firstly, how Fourier shell correlation of two independent maps and phase randomization beyond a certain frequency address the assessment of map resolution is reviewed. Techniques for local resolution estimation and map sharpening are also touched upon. The topic of validating models which are either built de novo or based on a known atomic structure fitted into a cryo-EM map is then approached. Map-model comparison using Q-scores and Fourier shell correlation plots is used to assure the agreement of the model with the observed map density. The importance of annotating the model with B factors to account for the resolvability of individual atoms in the map is illustrated. Finally, the timely topic of detecting and validating water molecules and metal ions in maps that have surpassed ∼2 Å resolution is described.

Cryo-EM analysis provides new mechanistic insight into ATP binding to Ca2+ -ATPase SERCA2b.

Sarco/endoplasmic reticulum Ca2+ -ATPase (SERCA) 2b is a ubiquitous SERCA family member that conducts Ca2+ uptake from the cytosol to the ER. Herein, we present a 3.3Å resolution cryo-electron microscopy (cryo-EM) structure of human SERCA2b in the E1·2Ca2+ state, revealing a new conformation for Ca2+ -bound SERCA2b with a much closer arrangement of cytosolic domains than in the previously reported crystal structure of Ca2+ -bound SERCA1a. Multiple conformations generated by 3D classification of cryo-EM maps reflect the intrinsically dynamic nature of the cytosolic domains in this state. Notably, ATP binding residues of SERCA2b in the E1·2Ca2+ state are located at similar positions to those in the E1·2Ca2+ -ATP state; hence, the cryo-EM structure likely represents a preformed state immediately prior to ATP binding. Consistently, a SERCA2b mutant with an interdomain disulfide bridge that locks the closed cytosolic domain arrangement displayed significant autophosphorylation activity in the presence of Ca2+ . We propose a novel mechanism of ATP binding to SERCA2b.