CryoEM maps are full of potential

Molecular basis of TRPV3 channel blockade by intracellular polyamines

ThermoTRPV1-4 channels are involved in the regulation of multiple physiological processes, including thermo- and pain perception, thermoregulation, itch, and nociception and therefore tight control of their activity is a critical requirement for correct perception of noxious stimuli and pain. We previously reported a voltage-dependent inhibition of TRPV1-4 channels by intracellular polyamines that could be explained by high affinity spermine binding in, and passage through, the permeation path. Here, using electrophysiology and cryo-electron microscopy, we elucidate molecular details of TRPV3 blockade by endogenous spermine and its analog NASPM. We identify a high-affinity polyamine interaction site at the intracellular side of the pore, formed by residues E679 and E682, with no significant contribution of residues at the channel selectivity filter. A cryo-EM structure of TRPV3 in the presence of NASPM reveals conformational changes coupled to polyamine blockade. Paradoxically, although the TRPV3 'gating switch' is in the 'activated' configuration, the pore is closed at both gates. A modified blocking model, in which spermine interacts with the cytoplasmic entrance to the channel, from which spermine may permeate, or cause closure of the channel, provides a unifying explanation for electrophysiological and structural data and furnishes the essential background for further exploitation of this regulatory process.

Cryo-EM of Mitochondrial Complex I and ATP Synthase

Cryo-electron microscopy (cryo-EM) is the method of choice for investigating the structures of membrane protein complexes at high resolution under near-native conditions. This review focuses on recent cryo-EM work on mitochondrial complex I and ATP synthase. Single-particle cryo-EM structures of complex I from mammals, plants, and fungi extending to a resolution of 2 Å show different functional states, indicating consistent conformational changes of loops near the Q binding site, clusters of internal water molecules in the membrane arm, and an α-π transition in a membrane-spanning helix that opens and closes the proton transfer path. Cryo-EM structures of ATP synthase dimers from mammalian, yeast, and Polytomella mitochondria show several rotary states at a resolution of 2.7 to 3.5 Å. The new structures of complex I and ATP synthase are important steps along the way toward understanding the detailed molecular mechanisms of both complexes. Cryo-electron tomography and subtomogram averaging have the potential to resolve their high-resolution structures in situ.

Comprehensive microcrystal electron diffraction sample preparation for cryo-EM

Microcrystal electron diffraction (MicroED) has advanced structural methods across a range of sample types, from small molecules to proteins. This cryogenic electron microscopy (cryo-EM) technique involves the continuous rotation of small 3D crystals in the electron beam, while a high-speed camera captures diffraction data in the form of a movie. The crystal structure is subsequently determined by using established X-ray crystallographic software. MicroED is a technique still under development, and hands-on expertise in sample preparation, data acquisition and processing is not always readily accessible. This comprehensive guide on MicroED sample preparation addresses commonly used methods for various sample categories, including room temperature solid-state small molecules and soluble and membrane protein crystals. Beyond detailing the steps of sample preparation for new users, and because every crystal requires unique growth and sample-preparation conditions, this resource provides instructions and optimization strategies for MicroED sample preparation. The protocol is suitable for users with expertise in biochemistry, crystallography, general cryo-EM and crystallography data processing. MicroED experiments, from sample vitrification to final structure, can take anywhere from one workday to multiple weeks, especially when cryogenic focused ion beam milling is involved.

Cryo-EM analyses unveil details of mechanism and targocil-II mediated inhibition of S. aureus WTA transporter TarGH

Wall teichoic acid (WTA) is a polyol phosphate polymer that covalently decorates peptidoglycan of gram-positive bacteria, including Staphylococcus aureus. Central to WTA biosynthesis is flipping of lipid-linked precursors across the cell membrane by TarGH, a type V ABC transporter. Here, we present cryo-EM structures of S. aureus TarGH in the presence of targocil-II, a promising small-molecule lead with β-lactam antibiotic synergistic action. Targocil-II binds to the extracellular dimerisation interface of TarG, we suggest mimicking flipped but not yet released substrate. In absence of targocil-II and in complex with ATP analogue ATPγS, determined at 2.3 Å resolution, the ATPase active site is allosterically inhibited. This is due to a so far undescribed D-loop conformation, potentially minimizing spurious ATP hydrolysis in the absence of substrate. Targocil-II binding comparatively causes local and remote conformational changes through to the TarH active site, with the D-loop now optimal for ATP hydrolysis. These structures suggest an ability to modulate ATP hydrolysis in a WTA substrate dependent manner and a jammed ATPase cycle as the basis of the observed inhibition by targocil-II. The molecular insights provide an unprecedented basis for development of TarGH targeted therapeutics for treatment of multidrug-resistant S. aureus and other gram-positive bacterial infections.

Advances in cryo-electron microscopy (cryoEM) for structure-based drug discovery

INTRODUCTION

Macromolecular X-ray crystallography (XRC), nuclear magnetic resonance (NMR), and cryo-electron microscopy (cryoEM) are the primary techniques for determining atomic-level, three-dimensional structures of macromolecules essential for drug discovery. With advancements in artificial intelligence (AI) and cryoEM, the Protein Data Bank (PDB) is solidifying its role as a key resource for 3D macromolecular structures. These developments underscore the growing need for enhanced quality metrics and robust validation standards for experimental structures.

AREAS COVERED

This review examines recent advancements in cryoEM for drug discovery, analyzing structure quality metrics, resolution improvements, metal-ligand and water molecule identification, and refinement software. It compares cryoEM with other techniques like XRC and NMR, emphasizing the global expansion of cryoEM facilities and its increasing significance in drug discovery.

EXPERT OPINION

CryoEM is revolutionizing structural biology and drug discovery, particularly for large, complex structures in induced proximity and antibody-antigen interactions. It supports vaccine design, CAR T-cell optimization, gene editing, and gene therapy. Combined with AI, cryoEM enhances particle identification and 3D structure determination. With recent breakthroughs, cryoEM is emerging as a crucial tool in drug discovery, driving the development of new, effective therapies.

Assessment of amino acid charge states based on cryo-electron microscopy and molecular dynamics simulations of respiratory complex I

The charge states of titratable amino acid residues play a key role in the function of membrane-bound bioenergetic proteins. However, determination of these charge states both through experimental and computational approaches is extremely challenging. Cryo-EM density maps can provide insights on the charge states of titratable amino acid residues. By performing classical atomistic molecular dynamics simulations on the high resolution cryo-EM structures of respiratory complex I from Yarrowia lipolytica, we analyze the conformational and charge states of a key acidic residue in its ND1 subunit, aspartic acid D203, which is also a mitochondrial disease mutation locus. We suggest that in the native state of respiratory complex I, D203 is negatively charged and maintains a stable hydrogen bond to a conserved arginine residue. Alternatively, upon conformational change in the turnover state of the enzyme, its sidechain attains a charge-neutral status. We discuss the implications of this analysis on the molecular mechanism of respiratory complex I.

Ligand identification in CryoEM and X-ray maps using deep learning

MOTIVATION

Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule ligands bind to active sites of interest. However, the interpretation of density maps is challenging, and cognitive bias can sometimes mislead investigators into modeling fictitious compounds. Ligand identification can be aided by automatic methods, but existing approaches are available only for X-ray diffraction and are based on iterative fitting or feature-engineered machine learning rather than end-to-end deep learning.

RESULTS

Here, we propose to identify ligands using a deep-learning approach that treats density maps as 3D point clouds. We show that the proposed model is on par with existing machine learning methods for X-ray crystallography while also being applicable to cryoEM density maps. Our study demonstrates that electron density map fragments can aid the training of models that can later be applied to cryoEM structures but also highlights challenges associated with the standardization of electron microscopy maps and the quality assessment of cryoEM ligands.

AVAILABILITY AND IMPLEMENTATION

Code and model weights are available on GitHub at https://github.com/jkarolczak/ligands-classification. An accompanying ChimeraX bundle is available at https://github.com/wtaisner/chimerax-ligand-recognizer.

Ligand Identification in CryoEM and X-ray Maps Using Deep Learning

Motivation

Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule ligands bind to active sites of interest. However, the interpretation of density maps is challenging, and cognitive bias can sometimes mislead investigators into modeling fictitious compounds. Ligand identification can be aided by automatic methods, but existing approaches are available only for X-ray diffraction and are based on iterative fitting or feature-engineered machine learning rather than end-to-end deep learning.

Results

Here, we propose to identify ligands using a deep learning approach that treats density maps as 3D point clouds. We show that the proposed model is on par with existing machine learning methods for X-ray crystallography while also being applicable to cryoEM density maps. Our study demonstrates that electron density map fragments can aid the training of models that can later be applied to cryoEM structures but also highlights challenges associated with the standardization of electron microscopy maps and the quality assessment of cryoEM ligands.

Availability

Code and model weights are available on GitHub at https://github.com/jkarolczak/ligands-classification. Datasets used for training and testing are hosted at Zenodo: 10.5281/zenodo.10908325. An accompanying ChimeraX bundle is available at https://github.com/wtaisner/chimerax-ligand-recognizer.

Structural biology and molecular pharmacology of voltage-gated ion channels

Voltage-gated ion channels (VGICs), including those for Na+, Ca2+ and K+, selectively permeate ions across the cell membrane in response to changes in membrane potential, thus participating in physiological processes involving electrical signalling, such as neurotransmission, muscle contraction and hormone secretion. Aberrant function or dysregulation of VGICs is associated with a diversity of neurological, psychiatric, cardiovascular and muscular disorders, and approximately 10% of FDA-approved drugs directly target VGICs. Understanding the structure-function relationship of VGICs is crucial for our comprehension of their working mechanisms and role in diseases. In this Review, we discuss how advances in single-particle cryo-electron microscopy have afforded unprecedented structural insights into VGICs, especially on their interactions with clinical and investigational drugs. We present a comprehensive overview of the recent advances in the structural biology of VGICs, with a focus on how prototypical drugs and toxins modulate VGIC activities. We explore how these structures elucidate the molecular basis for drug actions, reveal novel pharmacological sites, and provide critical clues to future drug discovery.

Metal ions in biomedically relevant macromolecular structures

Understanding the functions of metal ions in biological systems is crucial for many aspects of research, including deciphering their roles in diseases and potential therapeutic use. Structural information about the molecular or atomic details of these interactions, generated by methods like X-ray crystallography, cryo-electron microscopy, or nucleic magnetic resonance, frequently provides details that no other method can. As with any experimental method, they have inherent limitations that sometimes lead to an erroneous interpretation. This manuscript highlights different aspects of structural data available for metal-protein complexes. We examine the quality of modeling metal ion binding sites across different structure determination methods, where different kinds of errors stem from, and how they can impact correct interpretations and conclusions.

X-rays, electrons, and neutrons as probes of atomic matter

X-rays, electrons, and neutrons probe different properties of matter. X-rays feel electron density (ED). Electrons sense the electrostatic potential (ESP) of electrons and nuclei. Neutrons are sensitive to nuclear coherent scattering length (NCSL). While NCSL maps are widely understood to be different, ED and ESP maps are tacitly assumed to be similar. Here, I show that the belief in ED and ESP map equivalence is mistaken, but contains a grain of truth. Using density functional theory (DFT), the Bethe-Mott (BM) relation, and the Thomas-Fermi (TF) and Cromer-Mann (CM) atomic models, I show that ED and ESP maps are indeed more similar to each other than to NCSL maps. Nevertheless, peak and integrated map values depend differently on the atomic order number and on the contributions from electrons in the inner and outer CM shells. ED and ESP maps also differ in the sign and relative magnitude of excess charge effects.

Conformational changes in the Niemann-Pick type C1 protein NCR1 drive sterol translocation

The membrane protein Niemann-Pick type C1 (NPC1, named NCR1 in yeast) is central to sterol homeostasis in eukaryotes. Saccharomyces cerevisiae NCR1 is localized to the vacuolar membrane, where it is suggested to carry sterols across the protective glycocalyx and deposit them into the vacuolar membrane. However, documentation of a vacuolar glycocalyx in fungi is lacking, and the mechanism for sterol translocation has remained unclear. Here, we provide evidence supporting the presence of a glycocalyx in isolated S. cerevisiae vacuoles and report four cryo-EM structures of NCR1 in two distinct conformations, named tense and relaxed. These two conformations illustrate the movement of sterols through a tunnel formed by the luminal domains, thus bypassing the barrier presented by the glycocalyx. Based on these structures and on comparison with other members of the Resistance-Nodulation-Division (RND) superfamily, we propose a transport model that links changes in the luminal domains with a cycle of protonation and deprotonation within the transmembrane region of the protein. Our model suggests that NPC proteins work by a generalized RND mechanism where the proton motive force drives conformational changes in the transmembrane domains that are allosterically coupled to luminal/extracellular domains to promote sterol transport.

Role of Protonation States in the Stability of Molecular Dynamics Simulations of High-Resolution Membrane Protein Structures

Classical molecular dynamics (MD) simulations provide unmatched spatial and time resolution of protein structure and function. However, the accuracy of MD simulations often depends on the quality of force field parameters and the time scale of sampling. Another limitation of conventional MD simulations is that the protonation states of titratable amino acid residues remain fixed during simulations, even though protonation state changes coupled to conformational dynamics are central to protein function. Due to the uncertainty in selecting protonation states, classical MD simulations are sometimes performed with all amino acids modeled in their standard charged states at pH 7. Here, we performed and analyzed classical MD simulations on high-resolution cryo-EM structures of two large membrane proteins that transfer protons by catalyzing protonation/deprotonation reactions. In simulations performed with titratable amino acids modeled in their standard protonation (charged) states, the structure diverges far from its starting conformation. In comparison, MD simulations performed with predetermined protonation states of amino acid residues reproduce the structural conformation, protein hydration, and protein-water and protein-protein interactions of the structure much better. The results support the notion that it is crucial to perform basic protonation state calculations, especially on structures where protonation changes play an important functional role, prior to the launch of any conventional MD simulations. Furthermore, the combined approach of fast protonation state prediction and MD simulations can provide valuable information about the charge states of amino acids in the cryo-EM sample. Even though accurate prediction of protonation states in proteinaceous environments currently remains a challenge, we introduce an approach of combining pKa prediction with cryo-EM density map analysis that helps in improving not only the protonation state predictions but also the atomic modeling of density data.

Exploiting the full potential of cryo-EM maps

The Coulomb potential maps generated by electron microscopy (EM) experiments contain not only information about the position but also about the charge state of the atom. This feature of EM maps allows the identification of specific ions and the protonation state of amino acid side chains in the sample. Here, we summarize qualitative observations of charges in EM maps, discuss the difficulties in interpreting the charge in Coulomb potential maps with respect to distinguishing it from radiation damage, and outline considerations to implement the correct charge in fitting algorithms.

Structural and functional basis of inositol hexaphosphate stimulation of NHEJ through stabilization of Ku-XLF interaction

The classical Non-Homologous End Joining (c-NHEJ) pathway is the predominant process in mammals for repairing endogenous, accidental or programmed DNA Double-Strand Breaks. c-NHEJ is regulated by several accessory factors, post-translational modifications, endogenous chemical agents and metabolites. The metabolite inositol-hexaphosphate (IP6) stimulates c-NHEJ by interacting with the Ku70-Ku80 heterodimer (Ku). We report cryo-EM structures of apo- and DNA-bound Ku in complex with IP6, at 3.5 Å and 2.74 Å resolutions respectively, and an X-ray crystallography structure of a Ku in complex with DNA and IP6 at 3.7 Å. The Ku-IP6 interaction is mediated predominantly via salt bridges at the interface of the Ku70 and Ku80 subunits. This interaction is distant from the DNA, DNA-PKcs, APLF and PAXX binding sites and in close proximity to XLF binding site. Biophysical experiments show that IP6 binding increases the thermal stability of Ku by 2°C in a DNA-dependent manner, stabilizes Ku on DNA and enhances XLF affinity for Ku. In cells, selected mutagenesis of the IP6 binding pocket reduces both Ku accrual at damaged sites and XLF enrolment in the NHEJ complex, which translate into a lower end-joining efficiency. Thus, this study defines the molecular bases of the IP6 metabolite stimulatory effect on the c-NHEJ repair activity.

Na+ Binding and Transport: Insights from Light-Driven Na+-Pumping Rhodopsin

Na+ plays a vital role in numerous physiological processes across humans and animals, necessitating a comprehensive understanding of Na+ transmembrane transport. Among the various Na+ pumps and channels, light-driven Na+-pumping rhodopsin (NaR) has emerged as a noteworthy model in this field. This review offers a concise overview of the structural and functional studies conducted on NaR, encompassing ground/intermediate-state structures and photocycle kinetics. The primary focus lies in addressing key inquiries: (1) unraveling the translocation pathway of Na+; (2) examining the role of structural changes within the photocycle, particularly in the O state, in facilitating Na+ transport; and (3) investigating the timing of Na+ uptake/release. By delving into these unresolved issues and existing debates, this review aims to shed light on the future direction of Na+ pump research.

Direct measurements of biomolecular electrostatics through experiments

Biomolecular electrostatics has been a subject of computational investigations based on 3D structures. This situation is changing because emerging experimental tools allow us to quantitatively investigate biomolecular electrostatics without any use of structure information. Now, electrostatic potentials around biomolecules can directly be measured for many residues simultaneously by nuclear magnetic resonance (NMR) spectroscopy. This NMR method can be used to study electrostatic aspects of various processes, including macromolecular association and liquid-liquid phase separation. Applications to structurally flexible biomolecules such as intrinsically disordered proteins are particularly useful. The new tools also facilitate examination of theoretical models and methods for biomolecular electrostatics.

Investigation of hydrated channels and proton pathways in a high-resolution cryo-EM structure of mammalian complex I

Respiratory complex I, a key enzyme in mammalian metabolism, captures the energy released by reduction of ubiquinone by NADH to drive protons across the inner mitochondrial membrane, generating the proton-motive force for ATP synthesis. Despite remarkable advances in structural knowledge of this complicated membrane-bound enzyme, its mechanism of catalysis remains controversial. In particular, how ubiquinone reduction is coupled to proton pumping and the pathways and mechanisms of proton translocation are contested. We present a 2.4-Å resolution cryo-EM structure of complex I from mouse heart mitochondria in the closed, active (ready-to-go) resting state, with 2945 water molecules modeled. By analyzing the networks of charged and polar residues and water molecules present, we evaluate candidate pathways for proton transfer through the enzyme, for the chemical protons for ubiquinone reduction, and for the protons transported across the membrane. Last, we compare our data to the predictions of extant mechanistic models, and identify key questions to answer in future work to test them.

Anionic G•U pairs in bacterial ribosomal rRNAs

Wobble GU pairs (or G•U) occur frequently within double-stranded RNA helices interspersed between standard G=C and A-U Watson-Crick pairs. Another type of G•U pair interacting via their Watson-Crick edges has been observed in the A site of ribosome structures between a modified U34 in the tRNA anticodon triplet and G + 3 in the mRNA. In such pairs, the electronic structure of the U is changed with a negative charge on N3(U), resulting in two H-bonds between N1(G)…O4(U) and N2(G)…N3(U). Here, we report that such pairs occur in other highly conserved positions in ribosomal RNAs of bacteria in the absence of U modification. An anionic cis Watson-Crick G•G pair is also observed and well conserved in the small subunit. These pairs are observed in tightly folded regions.

Mechanism of action for small-molecule inhibitors of triacylglycerol synthesis

Inhibitors of triacylglycerol (TG) synthesis have been developed to treat metabolism-related diseases, but we know little about their mechanisms of action. Here, we report cryo-EM structures of the TG-synthesis enzyme acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1), a membrane bound O-acyltransferase (MBOAT), in complex with two different inhibitors, T863 and DGAT1IN1. Each inhibitor binds DGAT1's fatty acyl-CoA substrate binding tunnel that opens to the cytoplasmic side of the ER. T863 blocks access to the tunnel entrance, whereas DGAT1IN1 extends further into the enzyme, with an amide group interacting with more deeply buried catalytic residues. A survey of DGAT1 inhibitors revealed that this amide group may serve as a common pharmacophore for inhibition of MBOATs. The inhibitors were minimally active against the related MBOAT acyl-CoA:cholesterol acyltransferase 1 (ACAT1), yet a single-residue mutation sensitized ACAT1 for inhibition. Collectively, our studies provide a structural foundation for developing DGAT1 and other MBOAT inhibitors.

Analytic modeling of inhomogeneous-resolution maps in cryo-electron microscopy and crystallography

Refinement of macromolecular atomic models versus experimental maps in crystallography and cryo-electron microscopy is a critical step in structure solution. For an appropriate comparison, model maps should mimic the imperfections in the experimental maps, mainly atomic disorder and limited resolution, which are often inhomogeneous over the molecular region. In the suggested method, these model maps are calculated as the sum of atomic contributions expressed through a specifically designed function describing a solitary spherical wave. Thanks to this function, atomic contributions are analytically expressed through their atomic displacement parameter and local resolution, a value now associated with each atom. Such a full analytic dependence of inhomogeneous-resolution map values on model parameters permits the refinement of all of these parameters together.

Toward Real Real-Space Refinement of Atomic Models

High-quality atomic models providing structural information are the results of their refinement versus diffraction data (reciprocal-space refinement), or versus experimental or experimentally based maps (real-space refinement). A proper real-space refinement can be achieved by comparing such a map with a map calculated from the atomic model. Similar to density distributions, the maps of a limited and even inhomogeneous resolution can also be calculated as sums of terms, known as atomic images, which are three-dimensional peaky functions surrounded by Fourier ripples. These atomic images and, consequently, the maps for the respective models, can be expressed analytically as functions of coordinates, atomic displacement parameters, and the local resolution. This work discusses the practical feasibility of such calculation for the real-space refinement of macromolecular atomic models.

Theoretical 3D electron diffraction electrostatic potential maps of proteins modeled with a multipolar pseudoatom data bank

The availability of atomic resolution experimental maps of electrostatic potential from 3D electron diffraction (3D ED) extends the possibility of investigating the electrostatic potential beyond the determination of non-H-atom positions. However, accurate tools to calculate this potential for macromolecules, without the use of expensive quantum calculations, are lacking. The University at Buffalo Data Bank (UBDB) gathers atom types that can be used to calculate accurate electrostatic potential maps via structure-factor calculations. Here, the transferable aspherical atom model (TAAM) is applied with UBDB to investigate theoretically obtained electrostatic potential maps of lysozyme and proteinase K, and compare them with experimental maps from 3D ED. UBDB better reproduces the molecular electrostatic potential of molecules within their entire volume compared with the neutral spherical models used in the popular independent atom model (IAM). Additionally, the theoretical electron-density maps of the studied proteins are shown and compared with the electrostatic potential maps. The atomic displacement parameters (B factors) may affect the electrostatic potential maps in a different way than in the case of electron-density maps. The computational method presented in this study could potentially facilitate the interpretation of the less resolved regions of cryo-electron microscopy density maps and pave the way for distinguishing between different ions/water molecules in the active sites of macromolecules in high-resolution structures, which is of interest for drug-design purposes.

Better, Faster, Cheaper: Recent Advances in Cryo-Electron Microscopy

Cryo-electron microscopy (cryo-EM) continues its remarkable growth as a method for visualizing biological objects, which has been driven by advances across the entire pipeline. Developments in both single-particle analysis and in situ tomography have enabled more structures to be imaged and determined to better resolutions, at faster speeds, and with more scientists having improved access. This review highlights recent advances at each stageof the cryo-EM pipeline and provides examples of how these techniques have been used to investigate real-world problems, including antibody development against the SARS-CoV-2 spike during the recent COVID-19 pandemic.

Cryo-EM structures define ubiquinone-10 binding to mitochondrial complex I and conformational transitions accompanying Q-site occupancy

Mitochondrial complex I is a central metabolic enzyme that uses the reducing potential of NADH to reduce ubiquinone-10 (Q₁₀) and drive four protons across the inner mitochondrial membrane, powering oxidative phosphorylation. Although many complex I structures are now available, the mechanisms of Q₁₀ reduction and energy transduction remain controversial. Here, we reconstitute mammalian complex I into phospholipid nanodiscs with exogenous Q₁₀. Using cryo-EM, we reveal a Q₁₀ molecule occupying the full length of the Q-binding site in the 'active' (ready-to-go) resting state together with a matching substrate-free structure, and apply molecular dynamics simulations to propose how the charge states of key residues influence the Q₁₀ binding pose. By comparing ligand-bound and ligand-free forms of the 'deactive' resting state (that require reactivating to catalyse), we begin to define how substrate binding restructures the deactive Q-binding site, providing insights into its physiological and mechanistic relevance.

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

SEQUENCE SLIDER: integration of structural and genetic data to characterize isoforms from natural sources

Proteins isolated from natural sources can be composed of a mixture of isoforms with similar physicochemical properties that coexist in the final steps of purification. Yet, even where unverified, the assumed sequence is enforced throughout the structural studies. Herein, we propose a novel perspective to address the usually neglected sequence heterogeneity of natural products by integrating biophysical, genetic and structural data in our program SEQUENCE SLIDER. The aim is to assess the evidence supporting chemical composition in structure determination. Locally, we interrogate the experimental map to establish which side chains are supported by the structural data, and the genetic information relating sequence conservation is integrated into this statistic. Hence, we build a constrained peptide database, containing most probable sequences to interpret mass spectrometry data (MS). In parallel, we perform MS de novo sequencing with genomic-based algorithms to detect point mutations. We calibrated SLIDER with Gallus gallus lysozyme, whose sequence is unequivocally established and numerous natural isoforms are reported. We used SLIDER to characterize a metalloproteinase and a phospholipase A2-like protein from the venom of Bothrops moojeni and a crotoxin from Crotalus durissus collilineatus. This integrated approach offers a more realistic structural descriptor to characterize macromolecules isolated from natural sources.

Training data composition affects performance of protein structure analysis algorithms

The three-dimensional structures of proteins are crucial for understanding their molecular mechanisms and interactions. Machine learning algorithms that are able to learn accurate representations of protein structures are therefore poised to play a key role in protein engineering and drug development. The accuracy of such models in deployment is directly influenced by training data quality. The use of different experimental methods for protein structure determination may introduce bias into the training data. In this work, we evaluate the magnitude of this effect across three distinct tasks: estimation of model accuracy, protein sequence design, and catalytic residue prediction. Most protein structures are derived from X-ray crystallography, nuclear magnetic resonance (NMR), or cryo-electron microscopy (cryo-EM); we trained each model on datasets consisting of either all three structure types or of only X-ray data. We Find that across these tasks, models consistently perform worse on test sets derived from NMR and cryo-EM than they do on test sets of structures derived from X-ray crystallography, but that the difference can be mitigated when NMR and cryo-EM structures are included in the training set. Importantly, we show that including all three types of structures in the training set does not degrade test performance on X-ray structures, and in some cases even increases it. Finally, we examine the relationship between model performance and the biophysical properties of each method, and recommend that the biochemistry of the task of interest should be considered when composing training sets.

Protein of a thousand faces: The tumor-suppressive and oncogenic responses of p53

The p53 protein is a pleiotropic regulator working as a tumor suppressor and as an oncogene. Depending on the cellular insult and the mutational status, p53 may trigger opposing activities such as cell death or survival, senescence and cell cycle arrest or proliferative signals, antioxidant or prooxidant activation, glycolysis, or oxidative phosphorylation, among others. By augmenting or repressing specific target genes or directly interacting with cellular partners, p53 accomplishes a particular set of activities. The mechanism in which p53 is activated depends on increased stability through post-translational modifications (PTMs) and the formation of higher-order structures (HOS). The intricate cell death and metabolic p53 response are reviewed in light of gaining stability via PTM and HOS formation in health and disease.

Cryo-EM to visualize the structural organization of viruses

It is intriguing to think that over millions of years, groups of nucleic acids got the chance to hold together with groups of proteins to build up what today is called a virus. Their only goal is to guarantee a successful replication inside a host. If their genome information is preserved, the task is accomplished. Viruses have evolved to infect organisms and propagate with high degree of adaptation, as it is the case of the SARS-CoV-2, agent of the 2020 world pandemic. The technological progress observed in the field of structural biology, especially in cryo-EM, has offered scientists the possibility of a better understanding of virus origins, behavior, and structural organization. In this minireview we summarize few perspectives about the origins and organization of viruses and the advances of cryo-EM to aid structural virologists to sample the virosphere.

Molecular Dynamics to Predict Cryo-EM: Capturing Transitions and Short-Lived Conformational States of Biomolecules

Single-particle cryogenic electron microscopy (cryo-EM) has revolutionized the field of the structural biology, providing an access to the atomic resolution structures of large biomolecular complexes in their near-native environment. Today's cryo-EM maps can frequently reach the atomic-level resolution, while often containing a range of resolutions, with conformationally variable regions obtained at 6 Å or worse. Low resolution density maps obtained for protein flexible domains, as well as the ensemble of coexisting conformational states arising from cryo-EM, poses new challenges and opportunities for Molecular Dynamics (MD) simulations. With the ability to describe the biomolecular dynamics at the atomic level, MD can extend the capabilities of cryo-EM, capturing the conformational variability and predicting biologically relevant short-lived conformational states. Here, we report about the state-of-the-art MD procedures that are currently used to refine, reconstruct and interpret cryo-EM maps. We show the capability of MD to predict short-lived conformational states, finding remarkable confirmation by cryo-EM structures subsequently solved. This has been the case of the CRISPR-Cas9 genome editing machinery, whose catalytically active structure has been predicted through both long-time scale MD and enhanced sampling techniques 2 years earlier than cryo-EM. In summary, this contribution remarks the ability of MD to complement cryo-EM, describing conformational landscapes and relating structural transitions to function, ultimately discerning relevant short-lived conformational states and providing mechanistic knowledge of biological function.

Identification of Mg2+ ions next to nucleotides in cryo-EM maps using electrostatic potential maps

Cryo electron microscopy (cryo-EM) can produce maps of macromolecules that have resolutions that are sufficiently high that structural details such as chemical modifications, water molecules and bound metal ions can be discerned. However, those accustomed to interpreting the electron-density maps of macromolecules produced by X-ray crystallography need to be careful when assigning features such as these in cryo-EM maps because cations, for example, interact far more strongly with electrons than they do with X-rays. Using simulated electrostatic potential (ESP) maps as a tool led us to re-examine a recent cryo-EM map of the human ribosome, and we realized that some of the ESP peaks originally identified as novel groups covalently bonded to the N7, O6 or O4 atoms of several guanines, adenines or uridines, respectively, in this structure are likely to instead represent Mg2+ ions coordinated to these atoms, which provide only partial charge compensation compared with Mg2+ ions located next to phosphate groups. In addition, direct evidence is provided for a variation in the level of 2'-O ribose methylation of nucleotides in the human ribosome. ESP maps can thus help in identifying ions next to nucleotide bases, i.e. at positions that can be difficult to address in cryo-EM maps due to charge effects, which are specifically encountered in cryo-EM. This work is particularly relevant to nucleoprotein complexes and shows that it is important to consider charge effects when interpreting cryo-EM maps, thus opening possibilities for localizing charges in structures that may be relevant for enzymatic mechanisms and drug interactions.

Structural interpretation of cryo-EM image reconstructions

The productivity of single-particle cryo-EM as a structure determination method has rapidly increased as many novel biological structures are being elucidated. The ultimate result of the cryo-EM experiment is an atomic model that should faithfully represent the computed image reconstruction. Although the principal approach of atomic model building and refinement from maps resembles that of the X-ray crystallographic methods, there are important differences due to the unique properties resulting from the 3D image reconstructions. In this review, we discuss the practiced work-flow from the cryo-EM image reconstruction to the atomic model. We give an overview of (i) resolution determination methods in cryo-EM including local and directional resolution variation, (ii) cryo-EM map contrast optimization including complementary map types that can help in identifying ambiguous density features, (iii) atomic model building and (iv) refinement in various resolution regimes including (v) their validation and (vi) discuss differences between X-ray and cryo-EM maps. Based on the methods originally developed for X-ray crystallography, the path from 3D image reconstruction to atomic coordinates has become an integral and important part of the cryo-EM structure determination work-flow that routinely delivers atomic models.

DRPnet: automated particle picking in cryo-electron micrographs using deep regression

BACKGROUND

Identification and selection of protein particles in cryo-electron micrographs is an important step in single particle analysis. In this study, we developed a deep learning-based particle picking network to automatically detect particle centers from cryoEM micrographs. This is a challenging task due to the nature of cryoEM data, having low signal-to-noise ratios with variable particle sizes, shapes, distributions, grayscale variations as well as other undesirable artifacts.

RESULTS

We propose a double convolutional neural network (CNN) cascade for automated detection of particles in cryo-electron micrographs. This approach, entitled Deep Regression Picker Network or "DRPnet", is simple but very effective in recognizing different particle sizes, shapes, distributions and grayscale patterns corresponding to 2D views of 3D particles. Particles are detected by the first network, a fully convolutional regression network (FCRN), which maps the particle image to a continuous distance map that acts like a probability density function of particle centers. Particles identified by FCRN are further refined to reduce false particle detections by the second classification CNN. DRPnet's first CNN pretrained with only a single cryoEM dataset can be used to detect particles from different datasets without retraining. Compared to RELION template-based autopicking, DRPnet results in better particle picking performance with drastically reduced user interactions and processing time. DRPnet also outperforms the state-of-the-art particle picking networks in terms of the supervised detection evaluation metrics recall, precision, and F-measure. To further highlight quality of the picked particle sets, we compute and present additional performance metrics assessing the resulting 3D reconstructions such as number of 2D class averages, efficiency/angular coverage, Rosenthal-Henderson plots and local/global 3D reconstruction resolution.

CONCLUSION

DRPnet shows greatly improved time-savings to generate an initial particle dataset compared to manual picking, followed by template-based autopicking. Compared to other networks, DRPnet has equivalent or better performance. DRPnet excels on cryoEM datasets that have low contrast or clumped particles. Evaluating other performance metrics, DRPnet is useful for higher resolution 3D reconstructions with decreased particle numbers or unknown symmetry, detecting particles with better angular orientation coverage.

Changes in Membrane Protein Structural Biology

Membrane proteins are essential components of many biochemical processes and are important pharmaceutical targets. Membrane protein structural biology provides the molecular rationale for these biochemical process as well as being a highly useful tool for drug discovery. Unfortunately, membrane protein structural biology is a difficult area of study due to low protein yields and high levels of instability especially when membrane proteins are removed from their native environments. Despite this instability, membrane protein structural biology has made great leaps over the last fifteen years. Today, the landscape is almost unrecognisable. The numbers of available atomic resolution structures have increased 10-fold though advances in crystallography and more recently by cryo-electron microscopy. These advances in structural biology were achieved through the efforts of many researchers around the world as well as initiatives such as the Membrane Protein Laboratory (MPL) at Diamond Light Source. The MPL has helped, provided access to and contributed to advances in protein production, sample preparation and data collection. Together, these advances have enabled higher resolution structures, from less material, at a greater rate, from a more diverse range of membrane protein targets. Despite this success, significant challenges remain. Here, we review the progress made and highlight current and future challenges that will be overcome.

Density modification of cryo-EM maps

Density modification uses expectations about features of a map such as a flat solvent and expected distributions of density in the region of the macromolecule to improve individual Fourier terms representing the map. This process transfers information from one part of a map to another and can improve the accuracy of a map. Here, the assumptions behind density modification for maps from electron cryomicroscopy are examined and a procedure is presented that allows the incorporation of model-based information. Density modification works best in cases where unfiltered, unmasked maps with clear boundaries between the macromolecule and solvent are visible, and where there is substantial noise in the map, both in the region of the macromolecule and the solvent. It also is most effective if the characteristics of the map are relatively constant within regions of the macromolecule and the solvent. Model-based information can be used to improve density modification, but model bias can in principle occur. Here, model bias is reduced by using ensemble models that allow an estimation of model uncertainty. A test of model bias is presented that suggests that even if the expected density in a region of a map is specified incorrectly by using an incorrect model, the incorrect expectations do not strongly affect the final map.

Structure of the bacterial ribosome at 2 Å resolution

Using cryo-electron microscopy (cryo-EM), we determined the structure of the Escherichia coli 70S ribosome with a global resolution of 2.0 Å. The maps reveal unambiguous positioning of protein and RNA residues, their detailed chemical interactions, and chemical modifications. Notable features include the first examples of isopeptide and thioamide backbone substitutions in ribosomal proteins, the former likely conserved in all domains of life. The maps also reveal extensive solvation of the small (30S) ribosomal subunit, and interactions with A-site and P-site tRNAs, mRNA, and the antibiotic paromomycin. The maps and models of the bacterial ribosome presented here now allow a deeper phylogenetic analysis of ribosomal components including structural conservation to the level of solvation. The high quality of the maps should enable future structural analyses of the chemical basis for translation and aid the development of robust tools for cryo-EM structure modeling and refinement.

Structure of the bacterial ribosome at 2 Å resolution

Using cryo-electron microscopy (cryo-EM), we determined the structure of the Escherichia coli 70S ribosome with a global resolution of 2.0 Å. The maps reveal unambiguous positioning of protein and RNA residues, their detailed chemical interactions, and chemical modifications. Notable features include the first examples of isopeptide and thioamide backbone substitutions in ribosomal proteins, the former likely conserved in all domains of life. The maps also reveal extensive solvation of the small (30S) ribosomal subunit, and interactions with A-site and P-site tRNAs, mRNA, and the antibiotic paromomycin. The maps and models of the bacterial ribosome presented here now allow a deeper phylogenetic analysis of ribosomal components including structural conservation to the level of solvation. The high quality of the maps should enable future structural analyses of the chemical basis for translation and aid the development of robust tools for cryo-EM structure modeling and refinement.

Improvement of cryo-EM maps by density modification

A density-modification procedure for improving maps from single-particle electron cryogenic microscopy (cryo-EM) is presented. The theoretical basis of the method is identical to that of maximum-likelihood density modification, previously used to improve maps from macromolecular X-ray crystallography. Key differences from applications in crystallography are that the errors in Fourier coefficients are largely in the phases in crystallography but in both phases and amplitudes in cryo-EM, and that half-maps with independent errors are available in cryo-EM. These differences lead to a distinct approach for combination of information from starting maps with information obtained in the density-modification process. The density-modification procedure was applied to a set of 104 datasets and improved map-model correlation and increased the visibility of details in many of the maps. The procedure requires two unmasked half-maps and a sequence file or other source of information on the volume of the macromolecule that has been imaged.

2.7 Å cryo-EM structure of vitrified M. musculus H-chain apoferritin from a compact 200 keV cryo-microscope

Here we present the structure of mouse H-chain apoferritin at 2.7 Å (FSC = 0.143) solved by single particle cryogenic electron microscopy (cryo-EM) using a 200 kV device, the Thermo Fisher Glacios®. This is a compact, two-lens illumination system with a constant power objective lens, without any energy filters or aberration correctors, often thought of as a "screening cryo-microscope". Coulomb potential maps reveal clear densities for main chain carbonyl oxygens, residue side chains (including alternative conformations) and bound solvent molecules. We used a quasi-crystallographic reciprocal space approach to fit model coordinates to the experimental cryo-EM map. We argue that the advantages offered by (a) the high electronic and mechanical stability of the microscope, (b) the high emission stability and low beam energy spread of the high brightness Field Emission Gun (X-FEG), (c) direct electron detection technology and (d) particle-based Contrast Transfer Function (CTF) refinement have contributed to achieving high resolution. Overall, we show that basic electron optical settings for automated cryo-electron microscopy imaging can be used to determine structures approaching atomic resolution.