cryo-EM Density Research Articles

Cryo-EM Structure of the Photosynthetic LH1-RC Complex from Rhodospirillum rubrum.

Rhodospirillum (Rsp.) rubrum is one of the most widely used model organisms in bacterial photosynthesis. This purple phototroph is characterized by the presence of both rhodoquinone (RQ) and ubiquinone as electron carriers and bacteriochlorophyll (BChl) a esterified at the propionic acid side chain by geranylgeraniol (BChl aG) instead of phytol. Despite intensive efforts, the structure of the light-harvesting-reaction center (LH1-RC) core complex from Rsp. rubrum remains at low resolutions. Using cryo-EM, here we present a robust new view of the Rsp. rubrum LH1-RC at 2.76 Å resolution. The LH1 complex forms a closed, slightly elliptical ring structure with 16 αβ-polypeptides surrounding the RC. Our biochemical analysis detected RQ molecules in the purified LH1-RC, and the cryo-EM density map specifically positions RQ at the QA site in the RC. The geranylgeraniol side chains of BChl aG coordinated by LH1 β-polypeptides exhibit a highly homologous tail-up conformation that allows for interactions with the bacteriochlorin rings of nearby LH1 α-associated BChls aG. The structure also revealed key protein-protein interactions in both N- and C-terminal regions of the LH1 αβ-polypeptides, mainly within a face-to-face structural subunit. Our high-resolution Rsp. rubrum LH1-RC structure provides new insight for evaluating past experimental and computational results obtained with this old organism over many decades and lays the foundation for more detailed exploration of light-energy conversion, quinone transport, and structure-function relationships in this pigment-protein complex.

Cryo-EM structure of monomeric photosystem II at 2.78 Å resolution reveals factors important for the formation of dimer

Photosystem II (PSII) functions mainly as a dimer to catalyze the light energy conversion and water oxidation reactions. However, monomeric PSII also exists and functions in vivo in some cases. The crystal structure of monomeric PSII has been solved at 3.6 Å resolution, but it is still not clear which factors contribute to the formation of the dimer. Here, we solved the structure of PSII monomer at a resolution of 2.78 Å using cryo-electron microscopy (cryo-EM). From our cryo-EM density map, we observed apparent differences in pigments and lipids in the monomer-monomer interface between the PSII monomer and dimer. One β-carotene and two sulfoquinovosyl diacylglycerol (SQDG) molecules are found in the monomer-monomer interface of the dimer structure but not in the present monomer structure, although some SQDG and other lipid molecules are found in the analogous region of the low-resolution crystal structure of the monomer, or cryo-EM structure of an apo-PSII monomer lacking the extrinsic proteins from Synechocystis sp. PCC 6803. In the current monomer structure, a large part of the PsbO subunit was also found to be disordered. These results indicate the importance of the β-carotene, SQDG and PsbO in formation of the PSII dimer.

Efficient Flexible Fitting Refinement with Automatic Error Fixing for De Novo Structure Modeling from Cryo-EM Density Maps

Structural modeling of proteins from cryo-electron microscopy (cryo-EM) density maps is one of the challenging issues in structural biology. De novo modeling combined with flexible fitting refinement (FFR) has been widely used to build a structure of new proteins. In de novo prediction, artificial conformations containing local structural errors such as chirality errors, cis peptide bonds, and ring penetrations are frequently generated and cannot be easily removed in the subsequent FFR. Moreover, refinement can be significantly suppressed due to the low mobility of atoms inside the protein. To overcome these problems, we propose an efficient scheme for FFR, in which the local structural errors are fixed first, followed by FFR using an iterative simulated annealing (SA) molecular dynamics protocol with the united atom (UA) model in an implicit solvent model; we call this scheme “SAUA-FFR”. The best model is selected from multiple flexible fitting runs with various biasing force constants to reduce overfitting. We apply our scheme to the decoys obtained from MAINMAST and demonstrate an improvement of the best model of eight selected proteins in terms of the root-mean-square deviation, MolProbity score, and RWplus score compared to the original scheme of MAINMAST. Fixing the local structural errors can enhance the formation of secondary structures, and the UA model enables progressive refinement compared to the all-atom model owing to its high mobility in the implicit solvent. The SAUA-FFR scheme realizes efficient and accurate protein structure modeling from medium-resolution maps with less overfitting.

Cryo-EM Map-Based Model Validation Using the False Discovery Rate Approach.

Significant technological developments and increasing scientific interest in cryogenic electron microscopy (cryo-EM) has resulted in a rapid increase in the amount of data generated by these experiments and the derived atomic models. Robust measures for the validation of 3D reconstructions and atomic models are essential for appropriate interpretation of the data. The resolution of data and availability of software tools that work across a range of resolutions often limit the quality of derived models. Hence, the final atomic model is often incomplete or contains regions where atomic positions are less reliable or incorrectly built. Extensive manual pruning and local adjustments or rebuilding are usually required to address these issues. The presented research introduces a software tool for the validation of the backbone trace of atomic models built in the cryo-EM density maps. In this study, we use the false discovery rate analysis, which can be used to segregate molecular signals from the background. Each atomic position in the model can be associated with an FDR backbone validation score, which can be used to identify potential mistraced residues. We demonstrate that the proposed validation score is complementary to existing validation metrics and is useful especially in cases where the model is built in the maps having varying local resolution. We also discuss the application of the score for automated pruning of atomic models built ab-initio during the iterative model building process in Buccaneer. We have implemented this score in the CCP-EM software suite.

ProDy 2.0: increased scale and scope after 10 years of protein dynamics modelling with Python.

Summary ProDy, an integrated application programming interface developed for modelling and analysing protein dynamics, has significantly evolved in recent years in response to the growing data and needs of the computational biology community. We present major developments that led to ProDy 2.0: (i) improved interfacing with databases and parsing new file formats, (ii) SignDy for signature dynamics of protein families, (iii) CryoDy for collective dynamics of supramolecular systems using cryo-EM density maps and (iv) essential site scanning analysis for identifying sites essential to modulating global dynamics.Availability and implementation ProDy is open-source and freely available under MIT License from https://github.com/prody/ProDy.Supplementary information Supplementary data are available at Bioinformatics online.

Multi-Scale Flexible Fitting of Proteins to Cryo-EM Density Maps at Medium Resolution

Structure determination using cryo-electron microscopy (cryo-EM) medium-resolution density maps is often facilitated by flexible fitting. Avoiding overfitting, adjusting force constants driving the structure to the density map, and emulating complex conformational transitions are major concerns in the fitting. To address them, we develop a new method based on a three-step multi-scale protocol. First, flexible fitting molecular dynamics (MD) simulations with coarse-grained structure-based force field and replica-exchange scheme between different force constants replicas are performed. Second, fitted Cα atom positions guide the all-atom structure in targeted MD. Finally, the all-atom flexible fitting refinement in implicit solvent adjusts the positions of the side chains in the density map. Final models obtained via the multi-scale protocol are significantly better resolved and more reliable in comparison with long all-atom flexible fitting simulations. The protocol is useful for multi-domain systems with intricate structural transitions as it preserves the secondary structure of single domains.

Archaeal chromatin 'slinkies' are inherently dynamic complexes with deflected DNA wrapping pathways.

Eukaryotes and many archaea package their DNA with histones. While the four eukaryotic histones wrap ~147 DNA base pairs into nucleosomes, archaeal histones form 'nucleosome-like' complexes that continuously wind between 60 and 500 base pairs of DNA ('archaeasomes'), suggested by crystal contacts and analysis of cellular chromatin. Solution structures of large archaeasomes (>90 DNA base pairs) have never been directly observed. Here, we utilize molecular dynamics simulations, analytical ultracentrifugation, and cryoEM to structurally characterize the solution state of archaeasomes on longer DNA. Simulations reveal dynamics of increased accessibility without disruption of DNA-binding or tetramerization interfaces. Mg2+ concentration influences compaction, and cryoEM densities illustrate that DNA is wrapped in consecutive substates arranged 90o out-of-plane with one another. Without ATP-dependent remodelers, archaea may leverage these inherent dynamics to balance chromatin packing and accessibility.

GOLEM: Automated and Robust Cryo-EM-Guided Ligand Docking with Explicit Water Molecules

A detailed understanding of ligand-protein interactions underpins rational drug-design strategies. In recent years, technological advances in cryo-electron microscopy (cryo-EM) brought a new era for the structural determination of biological macromolecules and assemblies at a high resolution, marking cryo-EM a promising tool for studying ligand-protein interactions. However, even in high-resolution cryo-EM structures, the bound ligand's densities are often of lower quality due to its dynamic nature, frustrating an accurate coordinate assignment. Computational methods have been offering complementary efforts to aid structure modeling, such as MDFF (molecular dynamics flexible fitting) to fit atomic structures of macromolecules into corresponding cryo-EM densities. To address the challenge of ligand modeling in cryo-EM maps, here we report the development and validation of GOLEM (Genetic Optimization of Ligand in Experimental Maps), an automated and robust ligand docking method that models the ligand's optimal pose and conformation in cryo-EM maps. GOLEM employs a Lamarckian genetic algorithm, which performs a hybrid global/local search to explore the ligand's conformational, orientational, and positional space, with explicit consideration of water displacement and bridging water molecules' position and orientation. GOLEM takes into account both energetics and the correlation with the electron density maps in its scoring function, which is a combination of the system's energy and the energy of the ligand in a cryo-EM-derived external potential. GOLEM is validated in multiple cryo-EM structures with a wide range of map resolutions and ligand types, producing ligand poses in excellent agreement with the densities. As a VMD plugin, GOLEM is free-of-charge and accessible to the community. With these features, we believe GOLEM will be a valuable tool for ligand modeling in cryo-EM efforts towards drug discoveries.

Extraction of protein dynamics information from cryo-EM maps using deep learning

Elucidation of both the three-dimensional structure and the dynamics of a protein is essential to understand its function. Technical breakthroughs in single-particle analysis based on cryo-electron microscopy (cryo-EM) have enabled the three-dimensional structures of numerous proteins to be solved at atomic or near-atomic resolution. However, the analysis of the dynamics of protein targets using cryo-EM is often challenging because of their large sizes and complex structural assemblies. Here, we describe DEFMap, a deep learning-based approach to directly extract the dynamics associated with the atomic fluctuations that are hidden in cryo-EM density maps. Using only cryo-EM density data, DEFMap provides dynamics that correlate well with data obtained from molecular dynamics simulations and experimental approaches. Furthermore, DEFMap successfully detects changes in dynamics that are associated with molecular recognition. This strategy combines deep learning, experimental data and molecular dynamics simulations, and may reveal a new multidisciplinary approach for protein science. Cryo-electron microscopy (cryo-EM) can be used to determine the three-dimensional structure of proteins at atomic-scale resolution. It is challenging to observe the dynamics of proteins using cryo-EM because of their large sizes and complex structural assemblies. A new deep-learning approach called DEFMap extracts the dynamics associated with the atomic fluctuations that are hidden in cryo-EM density maps.

A Structurally Conserved Human and Tetrahymena Telomerase Catalytic Core

Telomerase is a ribonucleoprotein complex that counteracts the shortening of chromosome ends due to incomplete replication. Telomerase contains a catalytic core of telomerase reverse transcriptase (TERT) and telomerase RNA (TER). However, what defines TERT and separates it from other reverse transcriptases remains a subject of debate. A recent cryoEM map of Tetrahymena telomerase revealed the structure of a previously uncharacterized TERT domain (TRAP) with unanticipated interactions with TEN domain and roles in telomerase activity. Both TEN and TRAP are absent in the putative Tribolium TERT that has been used as a model for telomerase for over a decade. To investigate the conservation of TRAP and TEN across species, we performed multiple sequence alignments and statistical coupling analysis on all identified TERTs and find that TEN and TRAP have co-evolved as telomerase specific domains. Integrating the data from bioinformatic analysis and the structure of Tetrahymena telomerase, we built a new pseudoatomic model of human telomerase catalytic core that accounts for almost all of the cryoEM density in a published map, including TRAP in previously unassigned density as well as telomerase RNA domains essential for activity. This more complete model of human telomerase catalytic core illustrates how domains of TER and TERT, including the TEN-TRAP complex, can interact in a conserved manner to regulate telomere synthesis.

Molecular Mechanism of Force Generation by the Actin-Myosin Complex During Cardiac Muscle Contraction

Cardiac muscle contraction is performed by arrays of contractile proteins in the sarcomere. Serious heart diseases, such as cardiomyopathy, can often be results of mutations in myosin and actin, which slide along each other to generate force using the energy from ATP hydrolysis. All-atom molecular dynamics (MD) simulations have been growing its power in predicting protein structure-function relationships. However, such approaches are limited in the study of the myosin crossbridge cycle owing to the slow timescale as well as the lack of high-resolution structures of various intermediate states for the human cardiac myosin-actin complex. Here, combining comparative modeling and enhanced sampling MD simulations, we characterize how the myosin-actin interactions in human are influenced by the myosin functional states. By incorporating structural information from multiple templates, our comparative modeling provides conformational ensembles for different myosin-actin states, which enable us to efficiently sample the energy landscape using Gaussian accelerated MD simulations. Our results reveal novel interactions between key myosin loops and actin, which are consistent with recent cryo-EM density data. Furthermore, we find that the myosin cleft motion is impacted by the ATP binding site dynamics and that ADP release is coupled to the lever arm swing. Our approach demonstrates the potential to link genotype and molecular structures to the physical properties of the sarcomere.

Cryo-EM Structure of K+-Bound hERG Channel Complexed with the Blocker Astemizole

The hERG channel is a voltage-gated potassium channel involved in cardiac repolarization. Off-target hERG inhibition by drugs has become a critical issue in the pharmaceutical industry. The three-dimensional structure of the hERG channel was recently reported at 3.8-Å resolution using cryogenic electron microscopy (cryo-EM). However, the drug inhibition mechanism remains unclear because of the scarce structural information regarding the drug- and potassium-bound hERG channels. In this study, we obtained the cryo-EM density map of potassium-bound hERG channel complexed with astemizole, a well-known hERG inhibitor that increases risk of potentially fatal arrhythmia, at 3.5-Å resolution. The structure suggested that astemizole inhibits potassium conduction by binding directly below the selectivity filter. Furthermore, we propose a possible binding model of astemizole to the hERG channel and provide insights into the unusual sensitivity of hERG to several drugs.

Molecular structure of a prevalent amyloid-β fibril polymorph from Alzheimer's disease brain tissue

Amyloid-β (Aβ) fibrils exhibit self-propagating, molecular-level polymorphisms that may contribute to variations in clinical and pathological characteristics of Alzheimer's disease (AD). We report the molecular structure of a specific fibril polymorph, formed by 40-residue Aβ peptides (Aβ40), that is derived from cortical tissue of an AD patient by seeded fibril growth. The structure is determined from cryogenic electron microscopy (cryoEM) images, supplemented by mass-per-length (MPL) measurements and solid-state NMR (ssNMR) data. Previous ssNMR studies with multiple AD patients had identified this polymorph as the most prevalent brain-derived Aβ40 fibril polymorph from typical AD patients. The structure, which has 2.8-Å resolution according to standard criteria, differs qualitatively from all previously described Aβ fibril structures, both in its molecular conformations and its organization of cross-β subunits. Unique features include twofold screw symmetry about the fibril growth axis, despite an MPL value that indicates three Aβ40 molecules per 4.8-Å β-sheet spacing, a four-layered architecture, and fully extended conformations for molecules in the central two cross-β layers. The cryoEM density, ssNMR data, and MPL data are consistent with β-hairpin conformations for molecules in the outer cross-β layers. Knowledge of this brain-derived fibril structure may contribute to the development of structure-specific amyloid imaging agents and aggregation inhibitors with greater diagnostic and therapeutic utility.

Fitting Low-Resolution Protein Structures into Cryo-EM Density Maps by Multiobjective Optimization of Global and Local Correlations

The rigid-body fitting of predicted structural models into cryo-electron microscopy (cryo-EM) density maps is a necessary procedure for density map-guided protein structure determination and prediction. We proposed a novel multiobjective optimization protocol, MOFIT, which performs a rigid-body density-map fitting based on particle swarm optimization (PSO). MOFIT was tested on a large set of 292 nonhomologous single-domain proteins. Starting from structural models predicted by I-TASSER, MOFIT achieved an average coordinate root-mean-square deviation of 2.46 Å, which was 1.57, 2.79, and 3.95 Å lower than three leading single-objective function-based methods, where the differences were statistically significant with p-values of 1.65 × 10-6, 6.36 × 10-8, and 6.44 × 10-11 calculated using two-tail Student's t tests. Detailed analyses showed that the major advantages of MOFIT lie in the multiobjective protocol and the extensive PSO search simulations guided by the composite objective functions, which integrates complementary correlation coefficients from the global structure, local fragments, and individual residues with the cryo-EM density maps.

IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics

Proteomics methodology has expanded to include protein structural analysis, primarily through cross-linking mass spectrometry (XL-MS) and hydrogen–deuterium exchange mass spectrometry (HX-MS). However, while the structural proteomics community has effective tools for primary data analysis, there is a need for structure modeling pipelines that are accessible to the proteomics specialist. Integrative structural biology requires the aggregation of multiple distinct types of data to generate models that satisfy all inputs. Here, we describe IMProv, an app in the Mass Spec Studio that combines XL-MS data with other structural data, such as cryo-EM densities and crystallographic structures, for integrative structure modeling on high-performance computing platforms. The resource provides an easily deployed bundle that includes the open-source Integrative Modeling Platform program (IMP) and its dependencies. IMProv also provides functionality to adjust cross-link distance restraints according to the underlying dynamics of cross-linked sites, as characterized by HX-MS. A dynamics-driven conditioning of restraint values can improve structure modeling precision, as illustrated by an integrative structure of the five-membered Polycomb Repressive Complex 2. IMProv is extensible to additional types of data.

Application of transport-based metric for continuous interpolation between cryo-EM density maps.

Cryogenic electron microscopy (cryo-EM) has become widely used for the past few years in structural biology, to collect single images of macromolecules “frozen in time”. As this technique facilitates the identification of multiple conformational states adopted by the same molecule, a direct product of it is a set of 3D volumes, also called EM maps. To gain more insights on the possible mechanisms that govern transitions between different states, and hence the mode of action of a molecule, we recently introduced a bioinformatic tool that interpolates and generates morphing trajectories joining two given EM maps. This tool is based on recent advances made in optimal transport, that allow efficient evaluation of Wasserstein barycenters of 3D shapes. As the overall performance of the method depends on various key parameters, including the sensitivity of the regularization parameter, we performed various numerical experiments to demonstrate how MorphOT can be applied in different contexts and settings. Finally, we discuss current limitations and further potential connections between other optimal transport theories and the conformational heterogeneity problem inherent with cryo-EM data.

Low-cooling-rate freezing in biomolecular cryo-electron microscopy for recovery of initial frames.

When biological samples are first exposed to electrons in cryo-electron microcopy (cryo-EM), proteins exhibit a rapid 'burst' phase of beam-induced motion that cannot be corrected with software. This lowers the quality of the initial frames, which are the least damaged by the electrons. Hence, they are commonly excluded or down-weighted during data processing, reducing the undamaged signal and the resolution in the reconstruction. By decreasing the cooling rate during sample preparation, either with a cooling-rate gradient or by increasing the freezing temperature, we show that the quality of the initial frames for various protein and virus samples can be recovered. Incorporation of the initial frames in the reconstruction increases the resolution by an amount equivalent to using ~60% more data. Moreover, these frames preserve the high-quality cryo-EM densities of radiation-sensitive residues, which is often damaged or very weak in canonical three-dimensional reconstruction. The improved freezing conditions can be easily achieved using existing devices and enhance the overall quality of cryo-EM structures.

Evaluating Local and Directional Resolution of Cryo-EM Density Maps.

A systematic and quantitative evaluation of cryo-EM maps is necessary to judge their quality and to capture all possible sources of error. A single value for global resolution is insufficient to accurately describe the quality of a reconstructed density. We describe the estimation and evaluation of two additional resolution measures, local and directional resolution, using methods based on the Fourier shell correlation (FSC). We apply the protocol to samples that encompass different types of pathologies a user is expected to encounter and provide analyses on how to interpret the output files and resulting maps. Implementation of these tools will facilitate density interpretation and can guide the user in adapting their experiments to improve the quality of cryo-EM maps, and by extension atomic models.

Multiplexed Functional Assessment of Genetic Variants in CARD11

SummaryGenetic testing has increased the number of variants identified in disease genes, but the diagnostic utility is limited by lack of understanding variant function. CARD11 encodes an adaptor protein that expresses dominant-negative and gain-of-function variants associated with distinct immunodeficiencies. Here, we used a “cloning-free” saturation genome editing approach in a diploid cell line to simultaneously score 2,542 variants for decreased or increased function in the region of CARD11 associated with immunodeficiency. We also described an exon-skipping mechanism for CARD11 dominant-negative activity. The classification of reported clinical variants was sensitive (94.6%) and specific (88.9%), which rendered the data immediately useful for interpretation of seven coding and splicing variants implicated in immunodeficiency found in our clinic. This approach is generalizable for variant interpretation in many other clinically actionable genes, in any relevant cell type.

Atomic-resolution protein structure determination by cryo-EM.

Single-particle electron cryo-microscopy (cryo-EM) is a powerful method for solving the three-dimensional structures of biological macromolecules. The technological development of transmission electron microscopes, detectors and automated procedures in combination with user-friendly image processing software and ever-increasing computational power have made cryo-EM a successful and expanding technology over the past decade1. At resolutions better than 4Å, atomic model building starts to become possible, but the direct visualization of true atomic positions in protein structure determination requires much higher (better than 1.5Å) resolution, which so far has not been attained by cryo-EM. The direct visualization of atom positions is essential for understanding the mechanisms of protein-catalysed chemical reactions, and for studying how drugs bind to and interfere with the function of proteins2. Here we report a 1.25Å-resolution structure of apoferritin obtained by cryo-EM with a newly developed electron microscope that provides, to our knowledge, unprecedented structural detail. Our apoferritin structure has almost twice the 3D information content of the current world record reconstruction (at 1.54Å resolution3). We can visualize individual atoms in a protein, see density for hydrogen atoms and image single-atom chemical modifications. Beyond the nominal improvement in resolution, we also achieve a substantial improvement in the quality of the cryo-EM density map, which is highly relevant for using cryo-EM in structure-based drug design.