EM Map Research Articles

RETRACTION: High-Resolution Imaging of Human Viruses in Liquid Droplets.

G. M. Jonaid, W. J. Dearnaley, M. A. Casasanta, L. Kaylor, S. Berry, M. J. Dukes, M. S. Spilman, J. L. Gray and D. F. Kelly, "High-Resolution Imaging of Human Viruses in Liquid Droplets," Advanced Materials 33, no. 37 (2021): 2103221, https://doi.org/10.1002/adma.202103221. The above article, published online on 24 July 2021 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the author, M. S. Spilman; the journal Editors-in-Chief, Irem Bayindir-Buchhalter and Esther Levy; and Wiley-VCH GmbH. The retraction has been agreed upon following a thorough peer review process conducted by the author's institution, Penn State University. The peer review determined that there is no significant correlation between the EM map and the model at any resolution. Furthermore, the validation curves and the published curves significantly misrepresent the fit of models to EM maps. The authors didnot provide their original research data, EM maps, and models included in the study, to justify their findings. As a result, the institution recommends the article be retracted. The editors of the journal agree with these findings as they are supported by their own independent investigation. The author, D.F. Kelly, disagrees with the retraction; G.M. Jonaid agrees with the retraction; the other authors were unavailable for comment.

Validation of electron-microscopy maps using solution small-angle X-ray scattering.

The determination of the atomic resolution structure of biomacromolecules isessential for understanding details of their function. Traditionally, such a structure determination has been performed with crystallographic or nuclear resonance methods, but during the last decade, cryogenic transmission electron microscopy (cryo-TEM) has become an equally important tool. As the blotting and flash-freezing of the samples can induce conformational changes, external validation tools are required to ensure that the vitrified samples are representative of the solution. Although many validation tools have already been developed, most of them rely on fully resolved atomic models, which prevents early screening of the cryo-TEM maps. Here, a novel and automated method forperforming such a validation utilizing small-angle X-ray scattering measurements, publicly available through the new software package AUSAXS, is introduced and implemented. The method has been tested on both simulated and experimental data, where it was shown to work remarkably well as a validation tool. The method provides a dummy atomic model derived from the EM map which best represents the solution structure.

Structure-guided discovery of protein and glycan components in native mastigonemes

Mastigonemes, the hair-like lateral appendages lining cilia or flagella, participate in mechanosensation and cellular motion, but their constituents and structure have remained unclear. Here, we report the cryo-EM structure of native mastigonemes isolated from Chlamydomonas at 3.0Å resolution. The long stem assembles as a super spiral, with each helical turn comprising four pairs of anti-parallel mastigoneme-like protein 1 (Mst1). A large array of arabinoglycans, which represents a common class of glycosylation in plants and algae, is resolved surrounding the type II poly-hydroxyproline (Hyp) helix in Mst1. The EM map unveils a mastigoneme axial protein (Mstax) that is rich in heavily glycosylated Hyp and contains a PKD2-like transmembrane domain (TMD). Mstax, with nearly 8,000 residues spanning from the intracellular region to the distal end of the mastigoneme, provides the framework for Mst1 assembly. Our study provides insights into the complexity of protein and glycan interactions in native bio-architectures.

Catspermasome: The matrimony of CatSper and SLCO6C1.

CatSper is a highly specialized Ca2+ channel mediating Ca2+ entry in spermatozoa, which is essential for sperm motility and fertility. CatSper dysfunction would lead to male infertility, and it has been an attractive target for male infertility treatment as well as development of novel non-hormonal contraceptives. CatSper is the most complex ion channel known, consisting of at least ten identified subunits. It is very different from classic Cav channels in many aspects. For instance, the ion conducting pore of CatSper consists of four separate chains CatSper1-4 instead of a single chain in Cav channels. The auxiliary subunits CatSperβ, γ, δ, ε contain large extracellular domains while none of them are homologous to the α2δ subunit of Cav channels, indicating unique assembly of CatSper. To provide structural insights into CatSper composition, assembly, and regulation mechanisms, we purified the native CatSper channel from mouse testicular and epididymal tissues and resolved its structure at an overall resolution of 2.9 Å by cryo-EM. In the extracellular view, CatSper1-4 heterotetramer conform to the conventional domain-swapped voltage-gated ion channel fold, following a counterclockwise arrangement. CatSperβ, γ, δ and ε—each of which contains a single transmembrane segment and a large extracellular domain—constitute a pavilion-like structure that stabilizes the entire complex through interactions with CatSper4, 1, 3 and 2, respectively. Besides, the high-resolution EM map reveals several previously uncharacterized components, including TMEM249, TMEM262 (also named CatSperη) and an organic anion transporter SLCO6C1. Thus, CatSper is actually a channel-transporter ultracomplex that we termed the CatSpermasome. The structure and assembly details of the CatSpermasome revealed by our study help to lay the foundation for the development of CatSpermasome-related treatments for male infertility and non-hormonal contraceptives.

Cryo-EM structure of human voltage-gated sodium channel Nav1.6

Voltage-gated sodium channel Nav1.6 plays a crucial role in neuronal firing in the central nervous system (CNS). Aberrant function of Nav1.6 may lead to epilepsy and other neurological disorders. Specific inhibitors of Nav1.6 thus have therapeutic potentials. Here we present the cryo-EM structure of human Nav1.6 in the presence of auxiliary subunits β1 and fibroblast growth factor homologous factor 2B (FHF2B) at an overall resolution of 3.1 Å. The overall structure represents an inactivated state with closed pore domain (PD) and all "up" voltage-sensing domains. A conserved carbohydrate-aromatic interaction involving Trp302 and Asn326, together with the β1 subunit, stabilizes the extracellular loop in repeat I. Apart from regular lipids that are resolved in the EM map, an unprecedented Y-shaped density that belongs to an unidentified molecule binds to the PD, revealing a potential site for developing Nav1.6-specific blockers. Structural mapping of disease-related Nav1.6 mutations provides insights into their pathogenic mechanism.

DeepHEMNMA: ResNet-based hybrid analysis of continuous conformational heterogeneity in cryo-EM single particle images.

Single-particle cryo-electron microscopy (cryo-EM) is a technique for biomolecular structure reconstruction from vitrified samples containing many copies of a biomolecular complex (known as single particles) at random unknown 3D orientations and positions. Cryo-EM allows reconstructing multiple conformations of the complexes from images of the same sample, which usually requires many rounds of 2D and 3D classifications to disentangle and interpret the combined conformational, orientational, and translational heterogeneity. The elucidation of different conformations is the key to understand molecular mechanisms behind the biological functions of the complexes and the key to novel drug discovery. Continuous conformational heterogeneity, due to gradual conformational transitions giving raise to many intermediate conformational states of the complexes, is both an obstacle for high-resolution 3D reconstruction of the conformational states and an opportunity to obtain information about multiple coexisting conformational states at once. HEMNMA method, specifically developed for analyzing continuous conformational heterogeneity in cryo-EM, determines the conformation, orientation, and position of the complex in each single particle image by image analysis using normal modes (the motion directions simulated for a given atomic structure or EM map), which in turn allows determining the full conformational space of the complex but at the price of high computational cost. In this article, we present a new method, referred to as DeepHEMNMA, which speeds up HEMNMA by combining it with a residual neural network (ResNet) based deep learning approach. The performance of DeepHEMNMA is shown using synthetic and experimental single particle images.

Protein Structural Modeling for Electron Microscopy Maps Using VESPER and MAINMAST.

An increasing number of protein structures are determined by cryo‐electron microscopy (cryo‐EM) and stored in the Electron Microscopy Data Bank (EMDB). To interpret determined cryo‐EM maps, several methods have been developed that model the tertiary structure of biomolecules, particularly proteins. Here we show how to use two such methods, VESPER and MAINMAST, which were developed in our group. VESPER is a method mainly for two purposes: fitting protein structure models into an EM map and aligning two EM maps locally or globally to capture their similarity. VESPER represents each EM map as a set of vectors pointing toward denser points. By considering matching the directions of vectors, in general, VESPER aligns maps better than conventional methods that only consider local densities of maps. MAINMAST is a de novo protein modeling tool designed for EM maps with resolution of 3–5 Å or better. MAINMAST builds a protein main chain directly from a density map by tracing dense points in an EM map and connecting them using a tree‐graph structure. This article describes how to use these two tools using three illustrative modeling examples. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Protein structure model fitting using VESPER Alternate Protocol: Atomic model fitting using VESPER web server Basic Protocol 2: Protein de novo modeling using MAINMAST

Structure of the cytoplasmic ring of the Xenopus laevis nuclear pore complex.

INTRODUCTION The nuclear pore complex (NPC) resides on the nuclear envelope (NE) and mediates nucleocytoplasmic cargo transport. As one of the largest cellular machineries, a vertebrate NPC consists of cytoplasmic filaments, a cytoplasmic ring (CR), an inner ring, a nuclear ring, a nuclear basket, and a luminal ring. Each NPC has eight repeating subunits. Structure determination of NPC is a prerequisite for understanding its functional mechanism. In the past two decades, integrative modeling, which combines x-ray structures of individual nucleoporins and subcomplexes with cryo-electron tomography reconstructions, has played a crucial role in advancing our knowledge about the NPC. The CR has been a major focus of structural investigation. The CR subunit of human NPC was reconstructed by cryo-electron tomography through subtomogram averaging to an overall resolution of ~20 Å, with local resolution up to ~15 Å. Each CR subunit comprises two Y-shaped multicomponent complexes known as the inner and outer Y complexes. Eight inner and eight outer Y complexes assemble in a head-to-tail fashion to form the proximal and distal rings, respectively, constituting the CR scaffold. To achieve higher resolution of the CR, we used single-particle cryo-electron microscopy (cryo-EM) to image the intact NPC from the NE of Xenopus laevis oocytes. Reconstructions of the core region and the Nup358 region of the X. laevis CR subunit had been achieved at average resolutions of 5 to 8 Å, allowing identification of secondary structural elements. RATIONALE Packing interactions among the components of the CR subunit were poorly defined by all previous EM maps. Additional components of the CR subunit are strongly suggested by the EM maps of 5- to 8-Å resolution but remain to be identified. Addressing these issues requires improved resolution of the cryo-EM reconstruction. Therefore, we may need to enhance sample preparation, optimize image acquisition, and develop an effective data-processing strategy. RESULTS To reduce conformational heterogeneity of the sample, we spread the opened NE onto the grids with minimal force and used the chemical cross-linker glutaraldehyde to stabilize the NPC. To alleviate orientation bias of the NPC, we tilted sample grids and imaged the sample with higher electron dose at higher angles. We improved the image-processing protocol. With these efforts, the average resolutions for the core and the Nup358 regions have been improved to 3.7 and 4.7 Å, respectively. The highest local resolution of the core region reaches 3.3 Å. In addition, a cryo-EM structure of the N-terminal α-helical domain of Nup358 has been resolved at 3.0-Å resolution. These EM maps allow the identification of five copies of Nup358, two copies of Nup93, two copies of Nup205, and two copies of Y complexes in each CR subunit. Relying on the EM maps and facilitated by AlphaFold prediction, we have generated a final model for the CR of the X. laevis NPC. Our model of the CR subunit includes 19,037 amino acids in 30 nucleoporins. A previously unknown C-terminal fragment of Nup160 was found to constitute a key part of the vertex, in which the short arm, long arm, and stem of the Y complex meet. The Nup160 C-terminal fragment directly binds the β-propeller proteins Seh1 and Sec13. Two Nup205 molecules, which do not contact each other, bind the inner and outer Y complexes through distinct interfaces. Conformational elasticity of the two Nup205 molecules may underlie their versatility in binding to different nucleoporins in the proximal and distal CR rings. Two Nup93 molecules, each comprising an N-terminal extended helix and an ACE1 domain, bridge the Y complexes and Nup205. Nup93 and Nup205 together play a critical role in mediating the contacts between neighboring CR subunits. Five Nup358 molecules, each in the shape of a shrimp tail and named "the clamp," hold the stems of both Y complexes. The innate conformational elasticity allows each Nup358 clamp to adapt to a distinct local environment for optimal interactions with neighboring nucleoporins. In each CR subunit, the α-helical nucleoporins appear to provide the conformational elasticity; the 12 β-propellers may strengthen the scaffold. CONCLUSION Our EM map-based model of the X. laevis CR subunit substantially expands the molecular mass over the reported composite models of vertebrate CR subunit. In addition to the Y complexes, five Nup358, two Nup205, and two Nup93 molecules constitute the key components of the CR. The improved EM maps reveal insights into the interfaces among the nucleoporins of the CR. [Figure: see text].

Structure of cytoplasmic ring of nuclear pore complex by integrative cryo-EM and AlphaFold

INTRODUCTION The nuclear pore complex (NPC) is the molecular conduit in the nuclear membrane of eukaryotic cells that regulates import and export of biomolecules between the nucleus and the cytosol, with vertebrate NPCs ~110 to 125 MDa in molecular mass and ~120 nm in diameter. NPCs are organized into four main rings: the cytoplasmic ring (CR) at the cytosolic side, the inner ring and the luminal ring on the plane of the nuclear membrane, and the nuclear ring facing the nucleus. Each ring possesses an approximate eightfold symmetry and is composed of multiple copies of different nucleoporins. NPCs have been implicated in numerous biological processes, and their dysfunctions are associated with a growing number of serious human diseases. However, despite pioneering studies from many groups over the past two decades, we still lack a full understanding of NPCs' organization, dynamics, and complexity. RATIONALE We used the Xenopus laevis oocyte as a model system for the structural characterization because each oocyte possesses a large number of NPC particles that can be visualized on native nuclear membranes without the aid of detergent extraction. We used single-particle cryo-electron microscopy (cryo-EM) analysis on data collected at different stage tilt angles for three-dimensional reconstruction and structure prediction with AlphaFold for model building. RESULTS We reconstructed the CR map of X. laevis NPC at 6.9 and 6.7 Å resolutions for the full CR protomer and a core region, respectively, and predicted the structures of the individual nucleoporins using AlphaFold because no high-resolution models of X. laevis Nups were available. For any ambiguous subunit interactions, we also predicted complex structures, which further guided model fitting of the CR protomer. We placed the nucleoporin or complex structures into the CR density to obtain an almost full CR atomic model, composed of the inner and outer Y-complexes, two copies of Nup205, two copies of the Nup214-Nup88-Nup62 complex, one Nup155, and five copies of Nup358. In particular, we predicted the largest protein in the NPC, Nup358, as having an S-shaped globular domain, a coiled-coil domain, and a largely disordered C-terminal region containing phenylalanine-glycine (FG) repeats previously shown to form a gel-like condensate phase for selective cargo passage. Four of the Nup358 copies clamp around the inner and outer Y-complexes to stabilize the CR, and the fifth Nup358 situates in the center of the cluster of clamps. AlphaFold also predicted a homo-oligomeric, likely specifically pentameric, coiled-coil structure of Nup358 that may provide the avidity for Nup358 recruitment to the NPC and for lowering the threshold for Nup358 condensation in NPC biogenesis. CONCLUSION Our studies offer an example of integrative cryo-EM and structure prediction as a general approach for attaining more precise models of megadalton protein complexes from medium-resolution density maps. The more accurate and almost complete model of the CR presented here expands our understanding of the molecular interactions in the NPC and represents a substantial step forward toward the molecular architecture of a full NPC, with implications for NPC function, biogenesis, and regulation. [Figure: see text].

High-speed high-resolution data collection on a 200 keV cryo-TEM.

Limitations to successful single-particle cryo-electron microscopy (cryo-EM) projects include stable sample generation, production of quality cryo-EM grids with randomly oriented particles embedded in thin vitreous ice and access to microscope time. To address the limitation of microscope time, methodologies to more efficiently collect data on a 200 keV Talos Arctica cryo-transmission electron microscope at speeds as fast as 720 movies per hour (∼17 000 per day) were tested. In this study, key parameters were explored to increase data collection speed including: (1) using the beam-image shift method to acquire multiple images per stage position, (2) employing UltrAufoil TEM grids with R0.6/1 hole spacing, (3) collecting hardware-binned data and (4) adjusting the image shift delay factor in SerialEM. Here, eight EM maps of mouse apoferritin at 1.8-1.9 Å resolution were obtained in the analysis with data collection times for each dataset ranging from 56 min to 2 h. An EM map of mouse apoferritin at 1.78 Å was obtained from an overnight data collection at a speed of 500 movies per hour and subgroup analysis performed, with no significant variation observed in data quality by image shift distance and image shift delay. The findings and operating procedures detailed herein allow for rapid turnover of single-particle cryo-EM structure determination.

Structure of a mammalian sperm cation channel complex.

The cation channel of sperm (CatSper) is essential for sperm motility and fertility1,2. CatSper comprises the pore-forming proteins CATSPER1-4 and multiple auxiliary subunits, including CATSPERβ, γ, δ, ε, ζ, and EFCAB91,3-9. Here we report the cryo-electron microscopy (cryo-EM) structure of the CatSper complex isolated from mouse sperm. In the extracellular view, CATSPER1-4 conform to the conventional domain-swapped voltage-gated ion channel fold10, following a counterclockwise arrangement. The auxiliary subunits CATSPERβ, γ, δ and ε-each of which contains a single transmembrane segment and a large extracellular domain-constitute a pavilion-like structure that stabilizes the entire complex through interactions with CATSPER4, 1, 3 and 2, respectively. Our EM map reveals several previously uncharacterized components, exemplified by the organic anion transporter SLCO6C1. We name this channel-transporter ultracomplex the CatSpermasome. The assembly and organization details of the CatSpermasome presented here lay the foundation for the development of CatSpermasome-related treatments for male infertility and non-hormonal contraceptives.

Full-length de novo protein structure determination from cryo-EM maps using deep learning.

Advances in microscopy instruments and image processing algorithms have led to an increasing number of Cryo-electron microscopy (cryo-EM) maps. However, building accurate models for the EM maps at 3-5 Å resolution remains a challenging and time-consuming process. With the rapid growth of deposited EM maps, there is an increasing gap between the maps and reconstructed/modeled three-dimensional (3D) structures. Therefore, automatic reconstruction of atomic-accuracy full-atom structures from EM maps is pressingly needed. We present a semi-automatic de novo structure determination method using a deep learning-based framework, named as DeepMM, which builds atomic-accuracy all-atom models from cryo-EM maps at near-atomic resolution. In our method, the main-chain and Cα positions as well as their amino acid and secondary structure types are predicted in the EM map using Densely Connected Convolutional Networks. DeepMM was extensively validated on 40 simulated maps at 5 Å resolution and 30 experimental maps at 2.6-4.8 Å resolution as well as an Electron Microscopy Data Bank-wide dataset of 2931 experimental maps at 2.6-4.9 Å resolution, and compared with state-of-the-art algorithms including RosettaES, MAINMAST and Phenix. Overall, our DeepMM algorithm obtained a significant improvement over existing methods in terms of both accuracy and coverage in building full-length protein structures on all test sets, demonstrating the efficacy and general applicability of DeepMM. http://huanglab.phys.hust.edu.cn/DeepMM. Supplementary data are available at Bioinformatics online.

Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning

An increasing number of density maps of macromolecular structures, including proteins and DNA/RNA complexes, have been determined by cryo-electron microscopy (cryo-EM). Although lately maps at a near-atomic resolution are routinely reported, there are still substantial fractions of maps determined at intermediate or low resolutions, where extracting structure information is not trivial. Here, we report a new computational method, Emap2sec+, which identifies DNA or RNA as well as the secondary structures of proteins in cryo-EM maps of 5 to 10 Å resolution. Emap2sec+ employs the deep Residual convolutional neural network. Emap2sec+ assigns structural labels with associated probabilities at each voxel in a cryo-EM map, which will help structure modeling in an EM map. Emap2sec+ showed stable and high assignment accuracy for nucleotides in low resolution maps and improved performance for protein secondary structure assignments than its earlier version when tested on simulated and experimental maps.

Two conformations of DNA polymerase D-PCNA-DNA, an archaeal replisome complex, revealed by cryo-electron microscopy

BackgroundDNA polymerase D (PolD) is the representative member of the D family of DNA polymerases. It is an archaea-specific DNA polymerase required for replication and unrelated to other known DNA polymerases. PolD consists of a heterodimer of two subunits, DP1 and DP2, which contain catalytic sites for 3′-5′ editing exonuclease and DNA polymerase activities, respectively, with both proteins being mutually required for the full activities of each enzyme. However, the processivity of the replicase holoenzyme has additionally been shown to be enhanced by the clamp molecule proliferating cell nuclear antigen (PCNA), making it crucial to elucidate the interaction between PolD and PCNA on a structural level for a full understanding of its functional relevance. We present here the 3D structure of a PolD-PCNA-DNA complex from Thermococcus kodakarensis using single-particle cryo-electron microscopy (EM).ResultsTwo distinct forms of the PolD-PCNA-DNA complex were identified by 3D classification analysis. Fitting the reported crystal structures of truncated forms of DP1 and DP2 from Pyrococcus abyssi onto our EM map showed the 3D atomic structural model of PolD-PCNA-DNA. In addition to the canonical interaction between PCNA and PolD via PIP (PCNA-interacting protein)-box motif, we found a new contact point consisting of a glutamate residue at position 171 in a β-hairpin of PCNA, which mediates interactions with DP1 and DP2. The DNA synthesis activity of a mutant PolD with disruption of the E171-mediated PCNA interaction was not stimulated by PCNA in vitro.ConclusionsBased on our analyses, we propose that glutamate residues at position 171 in each subunit of the PCNA homotrimer ring can function as hooks to lock PolD conformation on PCNA for conversion of its activity. This hook function of the clamp molecule may be conserved in the three domains of life.

Comparison of CryoEM and X-ray structures of dimethylformamidase

Dimethylformamidase (DMFase) catalyzes the hydrolysis of dimethylformamide, an industrial solvent, introduced into the environment by humans. Recently, we determined the structures of dimethylformamidase by electron cryo microscopy and X-ray crystallography revealing a tetrameric enzyme with a mononuclear iron at the active site. DMFase from Paracoccus sp. isolated from a waste water treatment plant around the city of Kanpur in India shows maximal activity at 54 °C and is halotolerant. The structures determined by both techniques are mostly identical and the largest difference is in a loop near the active site. This loop could play a role in co-operativity between the monomers. A number of non-protein densities are observed in the EM map, which are modelled as water molecules. Comparison of the structures determined by the two methods reveals conserved water molecules that could play a structural role. The higher stability, unusual active site and negligible activity at low temperature makes this a very good model to study enzyme mechanism by cryoEM.

GemSpot: A Pipeline for Robust Modeling of Ligands into Cryo-EM Maps

Producing an accurate atomic model of biomolecule-ligand interactions from maps generated by cryoelectron microscopy (cryo-EM) often presents challenges inherent to the methodology and the dynamic nature of ligand binding. Here, we present GemSpot, an automated pipeline of computational chemistry methods that take into account EM map potentials, quantum mechanics energy calculations, and water molecule site prediction to generate candidate poses and provide a measure of the degree of confidence. The pipeline is validated through several published cryo-EM structures of complexes in different resolution ranges and various types of ligands. In all cases, at least one identified pose produced both excellent interactions with the target and agreement with the map. GemSpot will be valuable for the robust identification of ligand poses and drug discovery efforts through cryo-EM.

De Novo Protein Structure Modeling Tool MAINMAST Enhanced for Multiple Chain Complexes and Bound Ligands

The significant progress of the cryo-EM poses a pressing need for software for structural interpretation of EM maps. Particularly, protein structure modeling tools are needed for maps determined around 4 Å resolution, where modeling protein structure in EM map are still challenging problems. We have developed a de novo modeling tool named MAINMAST (MAINchain Model trAcing from Spanning Tree, http://kiharalab.org/mainmast/) for EM maps for this resolution range (Nature Communications, 2018). MAINMAST builds main-chain traces of a protein in an EM map from a tree graph structure constructed by connecting local maximum density points (LDPs)in the EM map. Here, we report the new version of MAINMAST that can handle (1) multiple protein chains with symmetry and (2) proteins with bound ligands in EM maps. For modeling of multiple protein chains, the new MAINMAST automatically identifies pairs of LDPs that locate in symmetric positions. Then, the identified LDP pairs are recorded as a tabu-pair list, which should not be included in a single chain. With the computed restrains in the tabu-pair list, MAINMAST constructs minimum spanning trees, which satisfy the all restrains and will produce symmetric chain structures. Once the initial trees are generated, the trees are optimized, and then the target sequence is mapped. For modeling of proteins with bound ligands, MAINMAST analyzes the tree-graph data and constructs main-chain model, and then detects the ligand-binding sites. Once MAINMAST identify the potential position of the bound ligand, MAINMAST segments the density map around the binding site, and models the ligand structure. We tested the new protocol on 24-mer complexes, apo-ferritin (emd-20026, emd-20027 and emd-20028) and a dimer complex, alcohol dehydrogenase with NAD molecules (emd-0406). MAINMAST built accurate protein structure models and NAD ligand models.

Protein Secondary Structure Detection in Intermediate-Resolution Cryo-EM Maps using Deep Learning

Although structures determined at near-atomic resolution are now routinely reported by cryo-electron microscopy (cryo-EM), many density maps are determined at an intermediate resolution, and extracting structure information from these maps is still a challenge. We report a computational method, Emap2sec, that identifies the secondary structures of proteins (α-helices, β-sheets and other structures) in EM maps at resolutions of between 5 and 10 A. Emap2sec uses a three-dimensional deep convolutional neural network to assign secondary structure to each grid point in an EM map. We tested Emap2sec on EM maps simulated from 34 structures at resolutions of 6.0 and 10.0 A, as well as on 43 maps determined experimentally at resolutions of between 5.0 and 9.5 A. Emap2sec was able to clearly identify the secondary structures in many maps tested, and showed substantially better performance than existing methods. Emap2sec uses a deep convolutional neural network to assign protein secondary structures in intermediate-resolution (5–10 A) cryo-EM maps.

Protein-Protein Modeling Using Cryo-EM Restraints.

Recent improvements in cryo-electron microscopy (cryo-EM) in the past few years are now allowing to observe molecular complexes at atomic resolution. As a consequence, numerous structures derived from cryo-EM are now available in the Protein Data Bank. However, if for some complexes atomic resolution is reached, this is not true for all. This is also the case in cryo-electron tomography where the achievable resolution is still limited. Furthermore the resolution in a cryo-EM map is not a constant, with often outer regions being of lower resolution, possibly linked to conformational variability. Although those low- to medium-resolution EM maps (or regions thereof) cannot directly provide atomic structure of large molecular complexes, they provide valuable information to model the individual components and their assembly into them. Most approaches for this kind of modeling are performing rigid fitting of the individual components into the EM density map. While this would appear an obvious option, they ignore key aspects of molecular recognition, the energetics and flexibility of the interfaces. Moreover, this often restricts the modeling to a unique source of data, the EM density map.In this chapter, we describe a protocol where an EM map is used as restraint in HADDOCK to guide the modeling process. In the first step, rigid-body fitting is performed with PowerFit in order to identify the most likely locations of the molecules into the map. These are then used as centroids to which distance restraints are defined from the center of mass of the components of the complex for the initial rigid-body docking. The EM density is then directly used as an additional restraint energy term, which can be combined with all the other types of data supported by HADDOCK. This protocol relies on the new version 2.4 of both the HADDOCK webserver and software. Preparation steps consisting of cropping the EM map and rigid-body fitting of the atomic structure are explained. Then, the EM-driven docking protocol using HADDOCK is illustrated.

Cryo-EM Structure of BIVV001 Reveals Coagulation Factor VIII-Von Willebrand Factor D'D3 Interaction Mode

Introduction Coagulation Factor VIII (FVIII) is a serine protease cofactor that directly interacts with coagulation factors IXa and X on activated platelets, and enhances FIXa activity toward FX by 105. von Willebrand Factor (VWF), via its D'D3 domains, interacts with FVIII and prevents premature deposition on phospholipids until activation by thrombin. Thrombin cleavage at Arg1689 of FVIII promotes VWF dissociation by disrupting the FVIII a3 high affinity interaction with the VWF D' domain. VWF extends the half-life of circulating FVIII from less than 3 hours to ~11 hours in humans. While crystal structures of FVIII and VWF D'D3 alone have been solved, the atomic details of a formed complex are unknown. We sought to determine the FVIII-VWF D'D3 complex structure by using BIVV001, our investigational new drug currently in clinical trials for the treatment of Hemophilia A. BIVV001 (rFVIIIFc-VWF-XTEN) is a novel fusion protein consisting of single chain B-domain deleted (BDD) human FVIII, the Fc domain of human immunoglobulin G1 (IgG1), the FVIII-binding D'D3 domain of human von Willebrand factor, and 2 XTEN polypeptide linkers. The Fc, VWF, and XTEN linker portions of the molecule are each designed to extend the half-life of FVIII. We anticipated that the tethering of FVIII to D'D3 through the Fc dimer in BIVV001 would stabilize the complex for structural studies. Given the large size of BIVV001, at 312 kDa, we thought it an ideal target for structure determination by single particle cryo-EM. Methods We collected a total of 3955 micrographs of BIVV001 embedded in vitreous ice at 81,000x magnification using a Titan Krios electron microscope equipped with a Gatan BioQuantum K3 energy filter and camera operating in super-resolution mode. Preferential particle orientation was a major challenge that was overcome through a variety of methods. Micrograph movies were motion-corrected and summed, and over 2 million candidate particle coordinates were extracted. Repeated rounds of reference-free 2D classification resulted in a set of 1.2 million particles that generated a reasonable ab initio/de novo 3D model. Initial full 3D refinements of this model produced a map at approximately 5 Å resolution, into which available crystal structures can be readily fit. Subsequent iterative 3D refinement and 3D classification resulted in a final map at high resolution, into which an atomic model was built. Results The structure of BIVV001 was solved by single particle cryo-EM. D' of VWF interacts with the front face of the C1 and A3 domains of FVIII, consistent with a lower resolution, negative stain EM map (Yee et al. 2015. Blood). Interface residues on FVIII identified in an HDX-MS dataset (Chiu et al. 2015. Blood.) largely correspond to this high affinity interaction. D' protrudes upward from the VWF D3 domain, which sits centrally located between the C1 and C2 domains of FVIII at a 45° tilt. By occupying this position, D3 likely sterically blocks the FVIII C domains from binding to membrane. The VWD3 module of the D3 domain contacts the base of the C1 domain, whereas C8-3 binds to the bottom of the C2 domain. The conserved Ca2+ site in VWD3 identified previously (Dong et al. 2019. Blood.) is in the interface with C1. This is consistent with Yee et al., where docking placed D3 below the C domains. In that study, a lack of density between FVIII and VWF D3 in the 3D reconstruction, due to flexibility, prevented the detailed analysis that is possible here. In this study, flexibility in this region is also apparent, as C2 is less well ordered than the rest of FVIII and VWF D3 is the least well-ordered portion of the resolved structure. The XTEN linkers are not visible in the final map and were not apparent in any 2D class averages. The Fc is absent in most 2D class averages, due to a lack of consistent positioning relative to FVIII. In the rare cases where the Fc is visible, it adopts a preferred position on the back side of FVIII below the A3 protrusion. Conclusions The structure of BIVV001 has been solved by cryo-electron microscopy to high resolution. Alignment with previous results and the averaging out of BIVV001 elaborations suggests the structure obtained here likely represents WT FVIII-D'D3. This structure demonstrates how VWF D'D3 prevents premature FVIII deposition on phospholipids. The structural basis of type 2N von Willebrand Disease mutations in D'D3 can be readily interpreted. Next steps include solving a FVIII-D'D3 dimer structure at high resolution. Disclosures Fuller: Sanofi: Employment. Batchelor:Sanofi: Employment. Knockenhauer:Sanofi: Employment. Biemann:Sanofi: Employment. Peters:Sanofi: Employment.