Single-particle cryo-EM at atomic resolution

Improving resolution and resolvability of single-particle cryoEM structures using Gaussian mixture models

Cryogenic electron microscopy is widely used in structural biology, but its resolution is often limited by the dynamics of the macromolecule. Here we developed a refinement protocol based on Gaussian mixture models that integrates particle orientation and conformation estimation and improves the alignment for flexible domains of protein structures. We demonstrated this protocol on multiple datasets, resulting in improved resolution and resolvability, locally and globally, by visual and quantitative measures.

Deep Learning Approach for High-accuracy Electron Counting of Monolithic Active Pixel Sensor-type Direct Electron Detectors at Increased Electron Dose

Electron counting can be performed algorithmically for monolithic active pixel sensor direct electron detectors to eliminate readout noise and Landau noise arising from the variability in the amount of deposited energy for each electron. Errors in existing counting algorithms include mistakenly counting a multielectron strike as a single electron event, and inaccurately locating the incident position of the electron due to lateral spread of deposited energy and dark noise. Here, we report a supervised deep learning (DL) approach based on Faster region-based convolutional neural network (R-CNN) to recognize single electron events at varying electron doses and voltages. The DL approach shows high accuracy according to the near-ideal modulation transfer function (MTF) and detector quantum efficiency for sparse images. It predicts, on average, 0.47 pixel deviation from the incident positions for 200 kV electrons versus 0.59 pixel using the conventional counting method. The DL approach also shows better robustness against coincidence loss as the electron dose increases, maintaining the MTF at half Nyquist frequency above 0.83 as the electron density increases to 0.06 e-/pixel. Thus, the DL model extends the advantages of counting analysis to higher dose rates than conventional methods.

Insights into protein structure using cryogenic light microscopy

Fluorescence microscopy has witnessed many clever innovations in the last two decades, leading to new methods such as structured illumination and super-resolution microscopies. The attainable resolution in biological samples is, however, ultimately limited by residual motion within the sample or in the microscope setup. Thus, such experiments are typically performed on chemically fixed samples. Cryogenic light microscopy (Cryo-LM) has been investigated as an alternative, drawing on various preservation techniques developed for cryogenic electron microscopy (Cryo-EM). Moreover, this approach offers a powerful platform for correlative microscopy. Another key advantage of Cryo-LM is the strong reduction in photobleaching at low temperatures, facilitating the collection of orders of magnitude more photons from a single fluorophore. This results in much higher localization precision, leading to Angstrom resolution. In this review, we discuss the general development and progress of Cryo-LM with an emphasis on its application in harnessing structural information on proteins and protein complexes.

MDSPACE and MDTOMO Software for Extracting Continuous Conformational Landscapes from Datasets of Single Particle Images and Subtomograms Based on Molecular Dynamics Simulations: Latest Developments in ContinuousFlex Software Package

Cryo electron microscopy (cryo-EM) instrumentation allows obtaining 3D reconstruction of the structure of biomolecular complexes in vitro (purified complexes studied by single particle analysis) and in situ (complexes studied in cells by cryo electron tomography). Standard cryo-EM approaches allow high-resolution reconstruction of only a few conformational states of a molecular complex, as they rely on data classification into a given number of classes to increase the resolution of the reconstruction from the most populated classes while discarding all other classes. Such discrete classification approaches result in a partial picture of the full conformational variability of the complex, due to continuous conformational transitions with many, uncountable intermediate states. In this article, we present the software with a user-friendly graphical interface for running two recently introduced methods, namely, MDSPACE and MDTOMO, to obtain continuous conformational landscapes of biomolecules by analyzing in vitro and in situ cryo-EM data (single particle images and subtomograms) based on molecular dynamics simulations of an available atomic model of one of the conformations. The MDSPACE and MDTOMO software is part of the open-source ContinuousFlex software package (starting from version 3.4.2 of ContinuousFlex), which can be run as a plugin of the Scipion software package (version 3.1 and later), broadly used in the cryo-EM field.

Emerging Trends in Cryo-EM-based Structural Studies of Neuropathological Amyloids

Tauopathies, synucleinopathies, Aβ amyloidosis, TDP-43 proteinopathies, and prion diseases- these neurodegenerative diseases have in common the formation of amyloid filaments rich in cross-β sheets. Cryo-electron microscopy now permits the visualization of amyloid assemblies at atomic resolution, ushering a wide range of structural studies on several of these poorly understood amyloidogenic proteins. Amyloids are polymorphic with minor modulations in reaction environment affecting the overall architecture of their assembly, making amyloids an extremely challenging venture for structure-based therapeutic intervention. In 2017, the first cryo-EM structure of tau filaments from an Alzheimer's disease-affected brain established that in vitro assemblies might not necessarily reflect the native amyloid fold. Since then, brain-derived amyloid structures for several proteins across many neurodegenerative diseases have uncovered the disease-relevant amyloid folds. It has now been shown for tauopathies, synucleinopathies and TDP-43 proteinopathies, that distinct amyloid folds of the same protein might be related to different diseases. Salient features of each of these brain-derived folds are discussed in detail. It was also recently observed that seeded aggregation does not necessarily replicate the brain-derived structural fold. Owing to high throughput structure determination, some of these native amyloid folds have also been successfully replicated in vitro. In vitro replication of disease-relevant filaments will aid development of imaging ligands and defibrillating drugs. Towards this direction, recent high-resolution structures of tau filaments with positron emission tomography tracers and a defibrillating drug are also discussed. This review summarizes and celebrates the recent advancements in structural understanding of neuropathological amyloid filaments using cryo-EM.

Embracing Heterogeneity: Challenging the Paradigm of Replisomes as Deterministic Machines

The paradigm of cellular systems as deterministic machines has long guided our understanding of biology. Advancements in technology and methodology, however, have revealed a world of stochasticity, challenging the notion of determinism. Here, we explore the stochastic behavior of multi-protein complexes, using the DNA replication system (replisome) as a prime example. The faithful and timely copying of DNA depends on the simultaneous action of a large set of enzymes and scaffolding factors. This fundamental cellular process is underpinned by dynamic protein-nucleic acid assemblies that must transition between distinct conformations and compositional states. Traditionally viewed as a well-orchestrated molecular machine, recent experimental evidence has unveiled significant variability and heterogeneity in the replication process. In this review, we discuss recent advances in single-molecule approaches and single-particle cryo-EM, which have provided insights into the dynamic processes of DNA replication. We comment on the new challenges faced by structural biologists and biophysicists as they attempt to describe the dynamic cascade of events leading to replisome assembly, activation, and progression. The fundamental principles uncovered and yet to be discovered through the study of DNA replication will inform on similar operating principles for other multi-protein complexes.

Single extracellular vesicle imaging and computational analysis identifies inherent architectural heterogeneity

Evaluating the heterogeneity of extracellular vesicles (EVs) is crucial for unraveling their complex actions and biodistribution. Here, we identify consistent architectural heterogeneity of EVs using cryogenic transmission electron microscopy (cryo-TEM) which has an inherent ability to image biological samples without harsh labeling methods and while preserving their native conformation. Imaging EVs isolated using different methodologies from distinct sources such as cancer cells, normal cells, and body fluids, we identify a structural atlas of their dominantly consistent shapes. We identify EV architectural attributes by utilizing a segmentation neural network model. In total, 7,576 individual EVs were imaged and quantified by our computational pipeline. Across all 7,576 independent EVs, the average eccentricity was 0.5366, and the average equivalent diameter was 132.43 nm. The architectural heterogeneity was consistent across all sources of EVs, independent of purification techniques, and compromised of single spherical (S. Spherical), rod-like or tubular, and double shapes. This study will serve as a reference foundation for high-resolution EV images and offer insights into their potential biological impact.

Scaling up cryo-EM for biology and chemistry: The journey from niche technology to mainstream method

Cryoelectron microscopy (cryo-EM) methods have made meaningful contributions in a wide variety of scientific research fields. In structural biology, cryo-EM routinely elucidates molecular structure from isolated biological macromolecular complexes or in a cellular context by harnessing the high-resolution power of the electron in order to image samples in a frozen, hydrated environment. For structural chemistry, the cryo-EM method popularly known as microcrystal electron diffraction (MicroED) has facilitated atomic structure generation of peptides and small molecules from their three-dimensional crystal forms. As cryo-EM has grown from an emerging technology, it has undergone modernization to enable multimodal transmission electron microscopy (TEM) techniques becoming more routine, reproducible, and accessible to accelerate research across multiple disciplines. We review recent advances in modern cryo-EM and assess how they are contributing to the future of the field with an eye to the past.

Structure determination by cryoEM at 100 keV

Electron cryomicroscopy can, in principle, determine the structures of most biological molecules but is currently limited by access, specimen preparation difficulties, and cost. We describe a purpose-built instrument operating at 100 keV-including advances in electron optics, detection, and processing-that makes structure determination fast and simple at a fraction of current costs. The instrument attains its theoretical performance limits, allowing atomic resolution imaging of gold test specimens and biological molecular structure determination in hours. We demonstrate its capabilities by determining the structures of eleven different specimens, ranging in size from 140 kDa to 2 MDa, using a fraction of the data normally required. CryoEM with a microscope designed specifically for high-efficiency, on-the-spot imaging of biological molecules will expand structural biology to a wide range of previously intractable problems.

Automated pipelines for rapid evaluation during cryoEM data acquisition

Cryo-electron microscopy (cryoEM) has become a popular method for determining high-resolution structures of biomolecules. However, data processing can be time-consuming, particularly for new researchers entering the field. To improve data quality and increase data collection efficiency, several software packages have been developed for on-the-fly data processing with various degrees of automation. These software packages allow researchers to perform tasks such as motion correction, CTF estimation, 2D classification, and 3D reconstruction in real-time, with minimal human input. On-the-fly data processing can not only improve data collection efficiency but also increase the productivity of instrumentation in high demand. However, the various software packages available differ in their performance, computational requirements, and levels of automation. In this review, we describe the minimal metrics used to assess data quality during data collection, outline the features of an ideal on-the-fly data processing software systems, and provide results from using three of these systems.

Nanoscale feedback control of six degrees of freedom of a near-sphere

Manipulating the rotational as well as the translational degrees of freedom of rigid bodies has been a crucial ingredient in diverse areas, from optically controlled micro-robots, navigation, and precision measurements at macroscale to artificial and biological Brownian motors at nanoscale. Here, we demonstrate feedback cooling of all the angular motions of a near-spherical neutral nanoparticle with all the translational motions feedback-cooled to near the ground state. The occupation numbers of the three translational motions are 6 ± 1, 6 ± 1, and 0.69 ± 0.18. A tight, anisotropic optical confinement allows us to clearly observe three angular oscillations and to identify the ratio of two radii to the longest radius with a precision of 0.08 %. We develop a thermometry for three angular oscillations and realize feedback cooling of them to temperatures of lower than 0.03 K by electrically controlling the electric dipole moment of the nanoparticle.

Cryo-electron ptychography: Applications and potential in biological characterisation

There is a clear need for developments in characterisation techniques that provide detailed information about structure-function relationships in biology. Using electron microscopy to achieve high resolution while maintaining a broad field of view remains a challenge, particularly for radiation-sensitive specimens where the signal-to-noise ratio required to maintain structural integrity is limited by low electron fluence. In this review, we explore the potential of cryogenic electron ptychography as an alternative method for characterising biological systems under low-fluence conditions. Using this method with increased information content from multiple sampled regions of interest potentially allows 3D reconstruction with far fewer particles than required in conventional cryo-electron microscopy. This is important for achieving higher resolution in systems where distributions of homogeneous single particles are difficult to obtain. We discuss the progress, limitations, and potential areas for future development of this approach for both single particle analysis and applications to heterogeneous large objects.

Mass spectrometers as cryoEM grid preparation instruments

Structure determination by single-particle cryoEM has matured into a core structural biology technique. Despite many methodological advancements, most cryoEM grids are still prepared using the plunge-freezing method developed ∼40 years ago. Embedding samples in thin films and exposing them to the air-water interface often leads to sample damage and preferential orientation of the particles. Using native mass spectrometry to create cryoEM samples, potentially avoids these problems and allows the use of mass spectrometry sample isolation techniques during EM grid creation. We review the recent publications that have demonstrated protein complexes can be ionized, flown through the mass spectrometer, gently landed onto EM grids, imaged, and reconstructed in 3D. Although many uncertainties and challenges remain, the combination of cryoEM and MS has great potential.

The pseudotorsional space of RNA

The characterization of the conformational landscape of the RNA backbone is rather complex due to the ability of RNA to assume a large variety of conformations. These backbone conformations can be depicted by pseudotorsional angles linking RNA backbone atoms, from which Ramachandran-like plots can be built. We explore here different definitions of these pseudotorsional angles, finding that the most accurate ones are the traditional η (eta) and θ (theta) angles, which represent the relative position of RNA backbone atoms P and C4'. We explore the distribution of η - θ in known experimental structures, comparing the pseudotorsional space generated with structures determined exclusively by one experimental technique. We found that the complete picture only appears when combining data from different sources. The maps provide a quite comprehensive representation of the RNA accessible space, which can be used in RNA-structural predictions. Finally, our results highlight that protein interactions lead to significant changes in the population of the η - θ space, pointing toward the role of induced-fit mechanisms in protein-RNA recognition.

Cryo-EM of a heterogeneous biochemical fraction elucidates multiple protein complexes from a multicellular thermophilic eukaryote

Biomolecular complexes and their interactions govern cellular structure and function. Understanding their architecture is a prerequisite for dissecting the cell's inner workings, but their higher-order assembly is often transient and challenging for structural analysis. Here, we performed cryo-EM on a single, highly heterogeneous biochemical fraction derived from Chaetomium thermophilum cell extracts to visualize the biomolecular content of the multicellular eukaryote. After cryo-EM single-particle image processing, results showed that a simultaneous three-dimensional structural characterization of multiple chemically diverse biomacromolecules is feasible. Namely, the thermophilic, eukaryotic complexes of (a) ATP citrate-lyase, (b) Hsp90, (c) 20S proteasome, (d) Hsp60 and (e) UDP-glucose pyrophosphorylase were characterized. In total, all five complexes have been structurally dissected in a thermophilic eukaryote in a total imaged sample area of 190.64 μm2, and two, in particular, 20S proteasome and Hsp60, exhibit side-chain resolution features. The C. thermophilum Hsp60 near-atomic model was resolved at 3.46 Å (FSC = 0.143) and shows a hinge-like conformational change of its equatorial domain, highly similar to the one previously shown for its bacterial orthologue, GroEL. This work demonstrates that cryo-EM of cell extracts will greatly accelerate the structural analysis of cellular complexes and provide unprecedented opportunities to annotate architectures of biomolecules in a holistic approach.

Neutron crystallographic refinement with REFMAC5 from the CCP4 suite

Hydrogen (H) atoms are abundant in macromolecules and often play critical roles in enzyme catalysis, ligand-recognition processes and protein-protein interactions. However, their direct visualization by diffraction techniques is challenging. Macromolecular X-ray crystallography affords the localization of only the most ordered H atoms at (sub-)atomic resolution (around 1.2 Å or higher). However, many H atoms of biochemical significance remain undetectable by this method. In contrast, neutron diffraction methods enable the visualization of most H atoms, typically in the form of deuterium (2H) atoms, at much more common resolution values (better than 2.5 Å). Thus, neutron crystallography, although technically demanding, is often the method of choice when direct information on protonation states is sought. REFMAC5 from the Collaborative Computational Project No. 4 (CCP4) is a program for the refinement of macromolecular models against X-ray crystallographic and cryo-EM data. This contribution describes its extension to include the refinement of structural models obtained from neutron crystallographic data. Stereochemical restraints with accurate bond distances between H atoms and their parent atom nuclei are now part of the CCP4 Monomer Library, the source of prior chemical information used in the refinement. One new feature for neutron data analysis in REFMAC5 is refinement of the protium/deuterium (1H/2H) fraction. This parameter describes the relative 1H/2H contribution to neutron scattering for hydrogen isotopes. The newly developed REFMAC5 algorithms were tested by performing the (re-)refinement of several entries available in the PDB and of one novel structure (FutA) using either (i) neutron data only or (ii) neutron data supplemented by external restraints to a reference X-ray crystallographic structure. Re-refinement with REFMAC5 afforded models characterized by R-factor values that are consistent with, and in some cases better than, the originally deposited values. The use of external reference structure restraints during refinement has been observed to be a valuable strategy, especially for structures at medium-low resolution.

LipIDens: simulation assisted interpretation of lipid densities in cryo-EM structures of membrane proteins

Cryo-electron microscopy (cryo-EM) enables the determination of membrane protein structures in native-like environments. Characterising how membrane proteins interact with the surrounding membrane lipid environment is assisted by resolution of lipid-like densities visible in cryo-EM maps. Nevertheless, establishing the molecular identity of putative lipid and/or detergent densities remains challenging. Here we present LipIDens, a pipeline for molecular dynamics (MD) simulation-assisted interpretation of lipid and lipid-like densities in cryo-EM structures. The pipeline integrates the implementation and analysis of multi-scale MD simulations for identification, ranking and refinement of lipid binding poses which superpose onto cryo-EM map densities. Thus, LipIDens enables direct integration of experimental and computational structural approaches to facilitate the interpretation of lipid-like cryo-EM densities and to reveal the molecular identities of protein-lipid interactions within a bilayer environment. We demonstrate this by application of our open-source LipIDens code to ten diverse membrane protein structures which exhibit lipid-like densities.

Baited reconstruction with 2D template matching for high-resolution structure determination in vitro and in vivo without template bias

Previously we showed that 2D template matching (2DTM) can be used to localize macromolecular complexes in images recorded by cryogenic electron microscopy (cryo-EM) with high precision, even in the presence of noise and cellular background (Lucas et al., 2021; Lucas et al., 2022). Here, we show that once localized, these particles may be averaged together to generate high-resolution 3D reconstructions. However, regions included in the template may suffer from template bias, leading to inflated resolution estimates and making the interpretation of high-resolution features unreliable. We evaluate conditions that minimize template bias while retaining the benefits of high-precision localization, and we show that molecular features not present in the template can be reconstructed at high resolution from targets found by 2DTM, extending prior work at low-resolution. Moreover, we present a quantitative metric for template bias to aid the interpretation of 3D reconstructions calculated with particles localized using high-resolution templates and fine angular sampling.

A generalizable scaffold-based approach for structure determination of RNAs by cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) can reveal the structures of large and often dynamic molecules, but smaller biomolecules (≤50 kDa) remain challenging targets due to their intrinsic low signal to noise ratio. Methods to help resolve small proteins have been applied but development of similar approaches to aid in structural determination of small, structured RNA elements have lagged. Here, we present a scaffold-based approach that we used to recover maps of sub-25 kDa RNA domains to 4.5-5.0 Å. While lacking the detail of true high-resolution maps, these maps are suitable for model building and preliminary structure determination. We demonstrate this method helped faithfully recover the structure of several RNA elements of known structure, and that it promises to be generalized to other RNAs without disturbing their native fold. This approach may streamline the sample preparation process and reduce the optimization required for data collection. This first-generation scaffold approach provides a robust system to aid in RNA structure determination by cryo-EM and lays the groundwork for further scaffold optimization to achieve higher resolution.

Advanced Techniques for Detecting Protein Misfolding and Aggregation in Cellular Environments

Protein misfolding and aggregation, a key contributor to the progression of numerous neurodegenerative diseases, results in functional deficiencies and the creation of harmful intermediates. Detailed visualization of this misfolding process is of paramount importance for improving our understanding of disease mechanisms and for the development of potential therapeutic strategies. While in vitro studies using purified proteins have been instrumental in delivering significant insights into protein misfolding, the behavior of these proteins in the complex milieu of living cells often diverges significantly from such simplified environments. Biomedical imaging performed in cell provides cellular-level information with high physiological and pathological relevance, often surpassing the depth of information attainable through in vitro methods. This review highlights a variety of methodologies used to scrutinize protein misfolding within biological systems. This includes optical-based methods, strategies leaning on mass spectrometry, in-cell nuclear magnetic resonance, and cryo-electron microscopy. Recent advancements in these techniques have notably deepened our understanding of protein misfolding processes and the features of the resulting misfolded species within living cells. The progression in these fields promises to catalyze further breakthroughs in our comprehension of neurodegenerative disease mechanisms and potential therapeutic interventions.

Self Fourier shell correlation: properties and application to cryo-ET

The Fourier shell correlation (FSC) is a measure of the similarity between two signals computed over corresponding shells in the frequency domain and has broad applications in microscopy. In structural biology, the FSC is ubiquitous in methods for validation, resolution determination, and signal enhancement. Computing the FSC usually requires two independent measurements of the same underlying signal, which can be limiting for some applications. Here, we analyze and extend on an approach proposed by Koho et al. [1] to estimate the FSC from a single measurement. In particular, we derive the necessary conditions required to estimate the FSC from downsampled versions of a single noisy measurement. These conditions reveal additional corrections which we implement to increase the applicability of the method. We then illustrate two applications of our approach, first as an estimate of the global resolution from a single 3-D structure and second as a data-driven method for denoising tomographic reconstructions in electron cryo-tomography. These results provide general guidelines for computing the FSC from a single measurement and suggest new applications of the FSC in microscopy.

Virus structures revealed by advanced cryoelectron microscopy methods

Before the resolution revolution, cryoelectron microscopy (cryo-EM) single-particle analysis (SPA) already achieved resolutions beyond 4 Å for certain icosahedral viruses, enabling ab initio atomic model building of these viruses. As the only samples that achieved such high resolution at that time, cryo-EM method development was closely intertwined with the improvement of reconstructions of symmetrical viruses. Viral morphology exhibits significant diversity, ranging from small to large, uniform to non-uniform, and from containing single symmetry to multiple symmetries. Furthermore, viruses undergo conformational changes during their life cycle. Several methods, such as asymmetric reconstruction, Ewald sphere correction, cryoelectron tomography (cryo-ET), and sub-tomogram averaging (STA), have been developed and applied to determine virus structures in vivo and in vitro. This review outlines current advanced cryo-EM methods for high-resolution structure determination of viruses and summarizes accomplishments obtained with these approaches. Moreover, persisting challenges in comprehending virus structures are discussed and we propose potential solutions.

Coherent imaging with low-energy electrons, quantitative analysis

Low-energy electrons (20-300eV) hold the promise for low-dose, non-destructive, high-resolution imaging, but at the price of challenging data analysis. This study provides theoretical considerations and models for the quantitative analysis of experimental data observed in low-energy electron transmission microscopy and in-line holography. The scattering of low-energy electrons and the imaging parameters, such as the inelastic mean free path, point spread function, depth of focus, and resolution, are quantitatively described. It is shown that unlike high-energy electrons (20-300 keV), low-energy electrons (20-300eV) introduce a large phase shift into the probing electron waves. Using the projected potentials formalism, the maximal phase shift acquired by a 120eV electron wave scattered by a carbon atom is theoretically estimated to be 5.03 radian and experimentally measured to be between 3 and 7.5 radian. The point spread function evaluated for low-energy electrons shows that they diffract much stronger than high-energy electrons, and that only very thin objects of up to 3Å in thickness can be imaged in focus. Thus, when imaging an object of finite thickness, such as a macromolecule, the obtained image will always be blurred due to the out-of-focus signal. This can provide an explanation for a long-standing problem of limited resolution in low-energy electron holography of macromolecules. As for imaging of a macromolecule's structure, it is shown that the amplitude of the wavefront reconstructed from the sample's hologram provides the best match to the projected potential distribution of the macromolecule. To evaluate the absorption properties, the inelastic mean free path (IMFP) is considered. The IMFP values calculated from theoretical models agree with the measured values. The IMFP of about 5Å was measured by transmission through graphene of 50-200eV electrons. This result implies that the internal structure of only very thin samples can be imaged in transmission mode. A simple method to quantitatively evaluate the absorption of a specimen from its in-line hologram without the need to reconstruct the hologram is presented.

Exploring the World of Membrane Proteins: Techniques and Methods for Understanding Structure, Function, and Dynamics

In eukaryotic cells, membrane proteins play a crucial role. They fall into three categories: intrinsic proteins, extrinsic proteins, and proteins that are essential to the human genome (30% of which is devoted to encoding them). Hydrophobic interactions inside the membrane serve to stabilize integral proteins, which span the lipid bilayer. This review investigates a number of computational and experimental methods used to study membrane proteins. It encompasses a variety of technologies, including electrophoresis, X-ray crystallography, cryogenic electron microscopy (cryo-EM), nuclear magnetic resonance spectroscopy (NMR), biophysical methods, computational methods, and artificial intelligence. The link between structure and function of membrane proteins has been better understood thanks to these approaches, which also hold great promise for future study in the field. The significance of fusing artificial intelligence with experimental data to improve our comprehension of membrane protein biology is also covered in this paper. This effort aims to shed light on the complexity of membrane protein biology by investigating a variety of experimental and computational methods. Overall, the goal of this review is to emphasize how crucial it is to understand the functions of membrane proteins in eukaryotic cells. It gives a general review of the numerous methods used to look into these crucial elements and highlights the demand for multidisciplinary approaches to advance our understanding.

Automated model building and protein identification in cryo-EM maps

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention. We present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality as those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy as humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will thus remove bottlenecks and increase objectivity in cryo-EM structure determination.

His1-tagged DM or DDM detergent micelles are reversibly conjugated by nickel ions

Specific conjugation of decyl β-D-maltoside (DM) or dodecyl β-D-maltoside (DDM) detergent micelles is accomplished between pH 7.0-8.5 in the presence of an amphiphilic analog of the amino acid histidine, bound to a 10-carbon hydrocarbon chain (His1-C10) and Ni2+ ions. Following addition of 10-15 wt% PEG-6000 as precipitant, phase separation in the form of oil-rich globules (30-600 µm) is observed by light microscopy. Other divalent cations: Zn2+, Fe2+, Cu2+ lead to dark precipitates rather than colorless globules; while Mg2+, Ca2+ do not promote any phase separation at all. Even in the absence of precipitant, dynamic light scattering (DLS) measurements demonstrate that DM micelles (hydrodynamic size ~ 6 nm) or DDM micelles (8 nm) self-associate into larger particles (9 nm and 411 nm for DM; 10 nm and 982 nm for DDM) in the presence of His1-C10 and nickel ions. Micellar conjugation is partially reversible in the presence of water soluble 50 mM EDTA, histidine or imidazole chelators. Cryo-transmission electron microscopy (cryo-TEM) imaging revealed the formation of non-uniformly dense detergent aggregates for both DM and DDM micelles in the presence of precipitant. The possible utility of such His1-tagged DM or DDM micelles for promoting crystallization of integral membrane proteins is discussed.

Structural insights into trehalose capture and translocation by mycobacterial LpqY-SugABC

The human pathogen, Mycobacterium tuberculosis (Mtb) relies heavily on trehalose for both survival and pathogenicity. The type I ATP-binding cassette (ABC) transporter LpqY-SugABC is the only trehalose import pathway in Mtb. Conformational dynamics of ABC transporters is an important feature to explain how they operate, but experimental structures are determined in a static environment. Therefore, a detailed transport mechanism cannot be elucidated because there is a lack of intermediate structures. Here, we used single-particle cryo-electron microscopy (cryo-EM) to determine the structure of the Mycobacterium smegmatis (M. smegmatis) trehalose-specific importer LpqY-SugABC complex in five different conformations. These structures have been classified and reconstructed from a single cryo-EM dataset. This study allows a comprehensive understanding of the trehalose recycling mechanism in Mycobacteria and also demonstrates the potential of single-particle cryo-EM to explore the dynamic structures of other ABC transporters and molecular machines.

The reduction of FIB damage on cryo-lamella by lowering energy of ion beam revealed by a quantitative analysis

Focused ion beam (FIB) is widely used for thinning frozen cells to produce lamellae for cryo-electron microscopy imaging and for protein structures study in vivo. However, FIB damages the lamellae and a quantitative experimental analysis of the damage is lacking. We used a 30-keV gallium FIB to prepare lamellae of a highly concentrated icosahedral virus sample. The viruses were grouped according to their distance from the surface of lamellae and reconstructed. Damage to the approximately 20-nm-thick outermost lamella surface was similar to that from exposure to 16 e-/Å2 in a 300-kV cryo-electron microscope at high-resolution range. The damage was negligible at a depth beyond 50 nm, which was reduced to 30 nm if 8-keV Ga+ was used during polishing. We designed extra steps in the reconstruction refinement to maximize undamaged signals and increase the resolution. The results demonstrated that low-energy beam polishing was essential for high-quality thinner lamellae.

How Neuromembrane Lipids Modulate Membrane Proteins: Insights from G-Protein-Coupled Receptors (GPCRs) and Receptor Tyrosine Kinases (RTKs)

Lipids play a diverse and critical role in cellular processes in all tissues. The unique lipid composition of nerve membranes is particularly interesting because it contains, among other things, polyunsaturated lipids, such as docosahexaenoic acid, which the body only gets through the diet. The crucial role of lipids in neurological processes, especially in receptor-mediated cell signaling, is emphasized by the fact that in many neuropathological diseases there are significant deviations in the lipid composition of nerve membranes compared to healthy individuals. The lipid composition of neuromembranes can significantly affect the function of receptors by regulating the physical properties of the membrane or by affecting specific interactions between receptors and lipids. In addition, it is worth noting that the ligand-binding pocket of many receptors is located inside the cell membrane, due to which lipids can even modulate the binding of ligands to their receptors. These mechanisms highlight the importance of lipids in the regulation of membrane receptor activation and function. In this article, we focus on two major protein families: G-protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs) and discuss how lipids affect their function in neuronal membranes, elucidating the basic mechanisms underlying neuronal function and dysfunction.

Overview of Membrane Protein Sample Preparation for Single-Particle Cryo-Electron Microscopy Analysis

Single-particle cryo-electron microscopy (cryo-EM SPA) has recently emerged as an exceptionally well-suited technique for determining the structure of membrane proteins (MPs). Indeed, in recent years, huge increase in the number of MPs solved via cryo-EM SPA at a resolution better than 3.0 Å in the Protein Data Bank (PDB) has been observed. However, sample preparation remains a significant challenge in the field. Here, we evaluated the MPs solved using cryo-EM SPA deposited in the PDB in the last two years at a resolution below 3.0 Å. The most critical parameters for sample preparation are as follows: (i) the surfactant used for protein extraction from the membrane, (ii) the surfactant, amphiphiles, nanodiscs or other molecules present in the vitrification step, (iii) the vitrification method employed, and (iv) the type of grids used. The aim is not to provide a definitive answer on the optimal sample conditions for cryo-EM SPA of MPs but rather assess the current trends in the MP structural biology community towards obtaining high-resolution cryo-EM structures.

Machine learning for cross-scale microscopy of viruses

Despite advances in virological sciences and antiviral research, viruses continue to emerge, circulate, and threaten public health. We still lack a comprehensive understanding of how cells and individuals remain susceptible to infectious agents. This deficiency is in part due to the complexity of viruses, including the cell states controlling virus-host interactions. Microscopy samples distinct cellular infection stages in a multi-parametric, time-resolved manner at molecular resolution and is increasingly enhanced by machine learning and deep learning. Here we discuss how state-of-the-art artificial intelligence (AI) augments light and electron microscopy and advances virological research of cells. We describe current procedures for image denoising, object segmentation, tracking, classification, and super-resolution and showcase examples of how AI has improved the acquisition and analyses of microscopy data. The power of AI-enhanced microscopy will continue to help unravel virus infection mechanisms, develop antiviral agents, and improve viral vectors.

Searching similar local 3D micro-environments in protein structure databases with MicroMiner

The available protein structure data are rapidly increasing. Within these structures, numerous local structural sites depict the details characterizing structure and function. However, searching and analyzing these sites extensively and at scale poses a challenge. We present a new method to search local sites in protein structure databases using residue-defined local 3D micro-environments. We implemented the method in a new tool called MicroMiner and demonstrate the capabilities of residue micro-environment search on the example of structural mutation analysis. Usually, experimental structures for both the wild-type and the mutant are unavailable for comparison. With MicroMiner, we extracted $>255 \times 10^{6}$ amino acid pairs in protein structures from the PDB, exemplifying single mutations' local structural changes for single chains and $>45 \times 10^{6}$ pairs for protein-protein interfaces. We further annotate existing data sets of experimentally measured mutation effects, like $\Delta \Delta G$ measurements, with the extracted structure pairs to combine the mutation effect measurement with the structural change upon mutation. In addition, we show how MicroMiner can bridge the gap between mutation analysis and structure-based drug design tools. MicroMiner is available as a command line tool and interactively on the https://proteins.plus/ webserver.

Deep learning driven de novo drug design based on gastric proton pump structures

Existing drugs often suffer in their effectiveness due to detrimental side effects, low binding affinity or pharmacokinetic problems. This may be overcome by the development of distinct compounds. Here, we exploit the rich structural basis of drug-bound gastric proton pump to develop compounds with strong inhibitory potency, employing a combinatorial approach utilizing deep generative models for de novo drug design with organic synthesis and cryo-EM structural analysis. Candidate compounds that satisfy pharmacophores defined in the drug-bound proton pump structures, were designed in silico utilizing our deep generative models, a workflow termed Deep Quartet. Several candidates were synthesized and screened according to their inhibition potencies in vitro, and their binding poses were in turn identified by cryo-EM. Structures reaching up to 2.10 Å resolution allowed us to evaluate and re-design compound structures, heralding the most potent compound in this study, DQ-18 (N-methyl-4-((2-(benzyloxy)-5-chlorobenzyl)oxy)benzylamine), which shows a Ki value of 47.6 nM. Further high-resolution cryo-EM analysis at 2.08 Å resolution unambiguously determined the DQ-18 binding pose. Our integrated approach offers a framework for structure-based de novo drug development based on the desired pharmacophores within the protein structure.

Fabrication of Monolayer Graphene-Coated Grids for Cryoelectron Microscopy

Cryogenic electron microscopy (cryoEM) has emerged as a powerful technique for probing the atomic structure of macromolecular complexes. Sample preparation for cryoEM requires preserving specimens in a thin layer of vitreous ice, typically suspended within the holes of a fenestrated support film. However, all commonly used sample preparation approaches for cryoEM studies expose the specimen to the air-water interface, introducing a strong hydrophobic effect on the specimen that often results in denaturation, aggregation, and complex dissociation. Further, preferred hydrophobic interactions between regions of the specimen and the air-water interface impact the orientations adopted by the macromolecules, resulting in 3D reconstructions with anisotropic directional resolution. Adsorption of cryoEM specimens to a monolayer of graphene has been shown to help mitigate interactions with the air-water interface while minimizing the introduction of background noise. Graphene supports also offer the benefit of substantially lowering the required concentration of proteins required for cryoEM imaging. Despite the advantages of these supports, graphene-coated grids are not widely used by the cryoEM community due to the prohibitive expense of commercial options and the challenges associated with large-scale in-house production. This paper describes an efficient method for preparing batches of cryoEM grids that have nearly full coverage of monolayer graphene.

MRC2020: improvements to Ximdisp and the MRC image-processing programs

The great success of single-particle electron cryo-microscopy (cryoEM) during the last decade has involved the development of powerful new computer programs and packages that guide the user along a recommended processing workflow, in which the wisdom and choices made by the developers help everyone, especially new users, to obtain excellent results. The ability to carry out novel, non-standard or unusual combinations of image-processing steps is sometimes compromised by the convenience of a standard procedure. Some of the older programs were written with great flexibility and are still very valuable. Among these, the original MRC image-processing programs for structure determination by 2D crystal and helical processing alongside general-purpose utility programs such as Ximdisp, label, imedit and twofile are still available. This work describes an updated version of the MRC software package (MRC2020) that is freely available from CCP-EM. It includes new features and improvements such as extensions to the MRC format that retain the versatility of the package and make it particularly useful for testing novel computational procedures in cryoEM.

PickYOLO: Fast deep learning particle detector for annotation of cryo electron tomograms

Particle localization (picking) in digital tomograms is a laborious and time-intensive step in cryogenic electron tomography (cryoET) analysis often requiring considerable user involvement, thus becoming a bottleneck for automated cryoET subtomogram averaging (STA) pipelines. In this paper, we introduce a deep learning framework called PickYOLO to tackle this problem. PickYOLO is a super-fast, universal particle detector based on the deep-learning real-time object recognition system YOLO (You Only Look Once), and tested on single particles, filamentous structures, and membrane-embedded particles. After training with the centre coordinates of a few hundred representative particles, the network automatically detects additional particles with high yield and reliability at a rate of 0.24-3.75 s per tomogram. PickYOLO can automatically detect number of particles comparable to those manually selected by experienced microscopists. This makes PickYOLO a valuable tool to substantially reduce the time and manual effort needed to analyse cryoET data for STA, greatly aiding in high-resolution cryoET structure determination.

Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease

The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software ( https://github.com/immunogenomics/HLA_analyses_tutorial ). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.

Big data in contemporary electron microscopy: challenges and opportunities in data transfer, compute and management

The second decade of the twenty-first century witnessed a new challenge in the handling of microscopy data. Big data, data deluge, large data, data compliance, data analytics, data integrity, data interoperability, data retention and data lifecycle are terms that have introduced themselves to the electron microscopy sciences. This is largely attributed to the booming development of new microscopy hardware tools. As a result, large digital image files with an average size of one terabyte within one single acquisition session is not uncommon nowadays, especially in the field of cryogenic electron microscopy. This brings along numerous challenges in data transfer, compute and management. In this review, we will discuss in detail the current state of international knowledge on big data in contemporary electron microscopy and how big data can be transferred, computed and managed efficiently and sustainably. Workflows, solutions, approaches and suggestions will be provided, with the example of the latest experiences in Australia. Finally, important principles such as data integrity, data lifetime and the FAIR and CARE principles will be considered.

Development of Single Molecule Techniques for Sensing and Manipulation of CRISPR and Polymerase Enzymes

Clustered regularly interspaced short palindromic repeats (CRISPR) and polymerases are powerful enzymes and their diverse applications in genomics, proteomics, and transcriptomics have revolutionized the biotechnology industry today. CRISPR has been widely adopted for genomic editing applications and Polymerases can efficiently amplify genomic transcripts via polymerase chain reaction (PCR). Further investigations into these enzymes can reveal specific details about their mechanisms that greatly expand their use. Single-molecule techniques are an effective way to probe enzymatic mechanisms because they may resolve intermediary conformations and states with greater detail than ensemble or bulk biosensing techniques. This review discusses various techniques for sensing and manipulation of single biomolecules that can help facilitate and expedite these discoveries. Each platform is categorized as optical, mechanical, or electronic. The methods, operating principles, outputs, and utility of each technique are briefly introduced, followed by a discussion of their applications to monitor and control CRISPR and Polymerases at the single molecule level, and closing with a brief overview of their limitations and future prospects.

Charging of Vitreous Samples in Cryogenic Electron Microscopy Mitigated by Graphene

Cryogenic electron microscopy can provide high-resolution reconstructions of macromolecules embedded in a thin layer of ice from which atomic models can be built de novo. However, the interaction between the ionizing electron beam and the sample results in beam-induced motion and image distortion, which limit the attainable resolutions. Sample charging is one contributing factor of beam-induced motions and image distortions, which is normally alleviated by including part of the supporting conducting film within the beam-exposed region. However, routine data collection schemes avoid strategies whereby the beam is not in contact with the supporting film, whose rationale is not fully understood. Here we characterize electrostatic charging of vitreous samples, both in imaging and in diffraction mode. We mitigate sample charging by depositing a single layer of conductive graphene on top of regular EM grids. We obtained high-resolution single-particle analysis (SPA) reconstructions at 2 Å when the electron beam only irradiates the middle of the hole on graphene-coated grids, using data collection schemes that previously failed to produce sub 3 Å reconstructions without the graphene layer. We also observe that the SPA data obtained with the graphene-coated grids exhibit a higher b factor and reduced particle movement compared to data obtained without the graphene layer. This mitigation of charging could have broad implications for various EM techniques, including SPA and cryotomography, and for the study of radiation damage and the development of future sample carriers. Furthermore, it may facilitate the exploration of more dose-efficient, scanning transmission EM based SPA techniques.

Molecular docking as a tool for the discovery of molecular targets of nutraceuticals in diseases management

Molecular docking is a computational technique that predicts the binding affinity of ligands to receptor proteins. Although it has potential uses in nutraceutical research, it has developed into a formidable tool for drug development. Bioactive substances called nutraceuticals are present in food sources and can be used in the management of diseases. Finding their molecular targets can help in the creation of disease-specific new therapies. The purpose of this review was to explore molecular docking's application to the study of dietary supplements and disease management. First, an overview of the fundamentals of molecular docking and the various software tools available for docking was presented. The limitations and difficulties of using molecular docking in nutraceutical research are also covered, including the reliability of scoring functions and the requirement for experimental validation. Additionally, there was a focus on the identification of molecular targets for nutraceuticals in numerous disease models, including those for sickle cell disease, cancer, cardiovascular, gut, reproductive, and neurodegenerative disorders. We further highlighted biochemistry pathways and models from recent studies that have revealed molecular mechanisms to pinpoint new nutraceuticals' effects on disease pathogenesis. It is convincingly true that molecular docking is a useful tool for identifying the molecular targets of nutraceuticals in the management of diseases. It may offer information about how nutraceuticals work and support the creation of new therapeutics. Therefore, molecular docking has a bright future in nutraceutical research and has a lot of potentials to lead to the creation of brand-new medicines for the treatment of disease.

Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy

In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomistic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modeling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril, the side chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-β structure of amyloid fibrils.

Recent Developments in Ultralarge and Structure-Based Virtual Screening Approaches

Drug development is a wide scientific field that faces many challenges these days. Among them are extremely high development costs, long development times, and a small number of new drugs that are approved each year. New and innovative technologies are needed to solve these problems that make the drug discovery process of small molecules more time and cost efficient, and that allow previously undruggable receptor classes to be targeted, such as protein-protein interactions. Structure-based virtual screenings (SBVSs) have become a leading contender in this context. In this review, we give an introduction to the foundations of SBVSs and survey their progress in the past few years with a focus on ultralarge virtual screenings (ULVSs). We outline key principles of SBVSs, recent success stories, new screening techniques, available deep learning-based docking methods, and promising future research directions. ULVSs have an enormous potential for the development of new small-molecule drugs and are already starting to transform early-stage drug discovery.

Identity, structure, and function of the mitochondrial permeability transition pore: controversies, consensus, recent advances, and future directions

The mitochondrial permeability transition (mPT) describes a Ca2+-dependent and cyclophilin D (CypD)-facilitated increase of inner mitochondrial membrane permeability that allows diffusion of molecules up to 1.5 kDa in size. It is mediated by a non-selective channel, the mitochondrial permeability transition pore (mPTP). Sustained mPTP opening causes mitochondrial swelling, which ruptures the outer mitochondrial membrane leading to subsequent apoptotic and necrotic cell death, and is implicated in a range of pathologies. However, transient mPTP opening at various sub-conductance states may contribute several physiological roles such as alterations in mitochondrial bioenergetics and rapid Ca2+ efflux. Since its discovery decades ago, intensive efforts have been made to identify the exact pore-forming structure of the mPT. Both the adenine nucleotide translocase (ANT) and, more recently, the mitochondrial F1FO (F)-ATP synthase dimers, monomers or c-subunit ring alone have been implicated. Here we share the insights of several key investigators with different perspectives who have pioneered mPT research. We critically assess proposed models for the molecular identity of the mPTP and the mechanisms underlying its opposing roles in the life and death of cells. We provide in-depth insights into current controversies, seeking to achieve a degree of consensus that will stimulate future innovative research into the nature and role of the mPTP.

InFluence: An Open-Source Python Package to Model Images Captured with Direct Electron Detectors

The high detection efficiencies of direct electron detectors facilitate the routine collection of low fluence electron micrographs and diffraction patterns. Low dose and low fluence electron microscopy experiments are the only practical way to acquire useful data from beam sensitive pharmaceutical and biological materials. Appropriate modeling of low fluence images acquired using direct electron detectors is, therefore, paramount for quantitative analysis of the experimental images. We have developed a new open-source Python package to accurately model any single layer direct electron detector for low and high fluence imaging conditions, including a means to validate against experimental data through computation of modulation transfer function and detective quantum efficiency.

Lysosomal LAMP proteins regulate lysosomal pH by direct inhibition of the TMEM175 channel

Maintaining a highly acidic lysosomal pH is central to cellular physiology. Here, we use functional proteomics, single-particle cryo-EM, electrophysiology, and in vivo imaging to unravel a key biological function of human lysosome-associated membrane proteins (LAMP-1 and LAMP-2) in regulating lysosomal pH homeostasis. Despite being widely used as a lysosomal marker, the physiological functions of the LAMP proteins have long been overlooked. We show that LAMP-1 and LAMP-2 directly interact with and inhibit the activity of the lysosomal cation channel TMEM175, a key player in lysosomal pH homeostasis implicated in Parkinson's disease. This LAMP inhibition mitigates the proton conduction of TMEM175 and facilitates lysosomal acidification to a lower pH environment crucial for optimal hydrolase activity. Disrupting the LAMP-TMEM175 interaction alkalinizes the lysosomal pH and compromises the lysosomal hydrolytic function. In light of the ever-increasing importance of lysosomes to cellular physiology and diseases, our data have widespread implications for lysosomal biology.

Determining the structure of the bacterial voltage-gated sodium channel NaChBac embedded in liposomes by cryo electron tomography and subtomogram averaging

Voltage-gated sodium channels shape action potentials that propagate signals along cells. When the membrane potential reaches a certain threshold, the channels open and allow sodium ions to flow through the membrane depolarizing it, followed by the deactivation of the channels. Opening and closing of the channels is important for cellular signalling and regulates various physiological processes in muscles, heart and brain. Mechanistic insights into the voltage-gated channels are difficult to achieve as the proteins are typically extracted from membranes for structural analysis which results in the loss of the transmembrane potential that regulates their activity. Here, we report the structural analysis of a bacterial voltage-gated sodium channel, NaChBac, reconstituted in liposomes under an electrochemical gradient by cryo electron tomography and subtomogram averaging. We show that the small channel, most of the residues of which are embedded in the membrane, can be localized using a genetically fused GFP. GFP can aid the initial alignment to an average resulting in a correct structure, but does not help for the final refinement. At a moderate resolution of ˜16 Å the structure of NaChBac in an unrestricted membrane bilayer is 10% wider than the structure of the purified protein previously solved in nanodiscs, suggesting the potential movement of the peripheral voltage-sensing domains. Our study explores the limits of structural analysis of membrane proteins in membranes.

Overcoming Resolution Attenuation During Tilted Cryo-EM Data Collection

Structural biology efforts using cryogenic electron microscopy are frequently stifled by specimens adopting "preferred orientations" on grids, leading to anisotropic map resolution and impeding structure determination. Tilting the specimen stage during data collection is a generalizable solution but has historically led to substantial resolution attenuation. Here, we develop updated data collection and image processing workflows and demonstrate, using multiple specimens, that resolution attenuation is negligible or significantly reduced across tilt angles. Reconstructions with and without the stage tilted as high as 60° are virtually indistinguishable. These strategies allowed the reconstruction to 3 Å resolution of a bacterial RNA polymerase with preferred orientation. Furthermore, we present a quantitative framework that allows cryo-EM practitioners to define an optimal tilt angle for dataset acquisition. These data reinforce the utility of employing stage tilt for data collection and provide quantitative metrics to obtain isotropic maps.

Automated simulation-based membrane protein refinement into cryo-EM data

The resolution revolution has increasingly enabled single-particle cryogenic electron microscopy (cryo-EM) reconstructions of previously inaccessible systems, including membrane proteins-a category that constitutes a disproportionate share of drug targets. We present a protocol for using density-guided molecular dynamics simulations to automatically refine atomistic models into membrane protein cryo-EM maps. Using adaptive force density-guided simulations as implemented in the GROMACS molecular dynamics package, we show how automated model refinement of a membrane protein is achieved without the need to manually tune the fitting force ad hoc. We also present selection criteria to choose the best-fit model that balances stereochemistry and goodness of fit. The proposed protocol was used to refine models into a new cryo-EM density of the membrane protein maltoporin, either in a lipid bilayer or detergent micelle, and we found that results do not substantially differ from fitting in solution. Fitted structures satisfied classical model-quality metrics and improved the quality and the model-to-map correlation of the x-ray starting structure. Additionally, the density-guided fitting in combination with generalized orientation-dependent all-atom potential was used to correct the pixel-size estimation of the experimental cryo-EM density map. This work demonstrates the applicability of a straightforward automated approach to fitting membrane protein cryo-EM densities. Such computational approaches promise to facilitate rapid refinement of proteins under different conditions or with various ligands present, including targets in the highly relevant superfamily of membrane proteins.