Статті в журналах: "Cryo-EM structures"

1

Lawson, Catherine L., and Wah Chiu. "Comparing cryo-EM structures." Journal of Structural Biology 204, no. 3 (December 2018): 523–26. http://dx.doi.org/10.1016/j.jsb.2018.10.004.

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2

Jiang, Wen, and Liang Tang. "Atomic cryo-EM structures of viruses." Current Opinion in Structural Biology 46 (October 2017): 122–29. http://dx.doi.org/10.1016/j.sbi.2017.07.002.

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3

Malhotra, Sony, Sylvain Träger, Matteo Dal Peraro, and Maya Topf. "Modelling structures in cryo-EM maps." Current Opinion in Structural Biology 58 (October 2019): 105–14. http://dx.doi.org/10.1016/j.sbi.2019.05.024.

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4

Scheres, Sjors HW, Wenjuan Zhang, Benjamin Falcon, and Michel Goedert. "Cryo-EM structures of tau filaments." Current Opinion in Structural Biology 64 (October 2020): 17–25. http://dx.doi.org/10.1016/j.sbi.2020.05.011.

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5

Subroto, Toto, Rina Fajri Nuwarda, Umi Baroroh, Zuhrotun Nafisah, Bevi Lidya, and Muhammad Yusuf. "IN SILICO STUDY OF CRYO-EM STRUCTURES OF ANTIGEN-ANTIBODY COMPLEX OF CHIKUNGUNYA FOR THE DEVELOPMENT OF DIAGNOSTIC AGENT." Asian Journal of Pharmaceutical and Clinical Research 10, no. 14 (May 1, 2017): 62. http://dx.doi.org/10.22159/ajpcr.2017.v10s2.19489.

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Objective: Despite the availability of the commercial rapid tests of chikungunya, the difference of pathogen’s genotypes amongst different countries has created some causes for concern. It is found that the sensitivity of the current chikungunya rapid tests on Asian strain was only 20.5%, as compared to 90.3% when tested on the African phylogroup. Therefore, the development of diagnostics that is specific for the current strain circulating in the country is important to be done. The cryo-electron microscopy (cryo-EM) structures of antigen-antibody complex can be used as an insightful structural basis to the development of the tailored antibody for diagnostics purposes. However, cryo-EM structures usually were resolved in low resolution, thus some sterical clashes between residues are expected. This work aims to refine the cryo-EM structures of E1 E2 of chikungunya virus (CHIKV) in complex with antibody using molecular mechanics method, to calculate the binding energy of antigen-antibody complex, and to compare it with the experimental results.Methods: Thecryo-EM structures were refined in vacuoby short minimization scheme using AMBER 14. The binding energies were calculated using Firedock and MM/GBSA methods.Results:The results showed that the direct calculation of binding energies of cryo-EM structures reflected high repulsive forces. While the calculation on the refined structured showed lower binding energies. Visual inspections on the complex structures also indicated that the refined structures showed better interactions.Conclusion:As a conclusion, the refinement of cryo-EM structures should be useful to gain more insight into the binding mode of interactions between antigenic protein and antibody, at the atomic level.

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6

Ceska, Tom, Chun-Wa Chung, Rob Cooke, Chris Phillips, and Pamela A. Williams. "Cryo-EM in drug discovery." Biochemical Society Transactions 47, no. 1 (January 15, 2019): 281–93. http://dx.doi.org/10.1042/bst20180267.

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Abstract The impact of structural biology on drug discovery is well documented, and the workhorse technique for the past 30 years or so has been X-ray crystallography. With the advent of several technological improvements, including direct electron detectors, automation, better microscope vacuums and lenses, phase plates and improvements in computing power enabled by GPUs, it is now possible to record and analyse images of protein structures containing high-resolution information. This review, from a pharmaceutical perspective, highlights some of the most relevant and interesting protein structures for the pharmaceutical industry and shows examples of how ligand-binding sites, membrane proteins, both big and small, pseudo symmetry and complexes are being addressed by this technique.

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7

Glaeser, Robert M. "Replication and validation of cryo-EM structures." Journal of Structural Biology 184, no. 2 (November 2013): 379–80. http://dx.doi.org/10.1016/j.jsb.2013.09.007.

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8

Chiu, Wah, and Greg Pintilie. "Quantifying the resolvability in cryo-EM structures." Acta Crystallographica Section A Foundations and Advances 75, a1 (July 20, 2019): a351. http://dx.doi.org/10.1107/s0108767319096582.

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9

Yang, Guanghui, Rui Zhou та Yigong Shi. "Cryo-EM structures of human γ-secretase". Current Opinion in Structural Biology 46 (жовтень 2017): 55–64. http://dx.doi.org/10.1016/j.sbi.2017.05.013.

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10

Lawson, Catherine L., Helen M. Berman, and Wah Chiu. "Evolving data standards for cryo-EM structures." Structural Dynamics 7, no. 1 (January 2020): 014701. http://dx.doi.org/10.1063/1.5138589.

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11

Chen, Lin, and Jing He. "Outlier Profiles of Atomic Structures Derived from X-ray Crystallography and from Cryo-Electron Microscopy." Molecules 25, no. 7 (March 28, 2020): 1540. http://dx.doi.org/10.3390/molecules25071540.

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Background: As more protein atomic structures are determined from cryo-electron microscopy (cryo-EM) density maps, validation of such structures is an important task. Methods: We applied a histogram-based outlier score (HBOS) to six sets of cryo-EM atomic structures and five sets of X-ray atomic structures, including one derived from X-ray data with better than 1.5 Å resolution. Cryo-EM data sets contain structures released by December 2016 and those released between 2017 and 2019, derived from resolution ranges 0–4 Å and 4–6 Å respectively. Results: The distribution of HBOS values in five sets of X-ray structures show that HBOS is sensitive distinguishing sets of X-ray structures derived from different resolution ranges-higher than 1.5 Å, 1.5–2.0 Å, 2.0–2.5 Å, 2.5–3.0 Å, and 3.0–3.5 Å. The overall quality of cryo-EM structures is likely improved, as shown in a comparison of cryo-EM structures released before the end of 2016, those between 2017 and 2018, and those between 2018 and 2019. Our investigation shows that leucine (LEU) has a significantly higher rate of HBOS outliers than that of the reference data set (X-ray-1.5) and of other residue types in the cryo-EM data sets. HBOS was able to detect outliers for those residues that are currently marked as green in PDB validation reports. Conclusions: The HBOS profile of a dataset is a potential method to characterize the overall structural quality of the set. Residue LEU deserves special attention since it has a significantly higher HBOS outlier rate in sets of cryo-EM structures and those X-ray structures derived from X-ray data of lower than 2.5 Å resolutions. Most HBOS outlier residues from the EM-0-4-2019 set are located on loops for most types of residues.

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12

Wang, Liguo, and Fred J. Sigworth. "Cryo-EM and Single Particles." Physiology 21, no. 1 (February 2006): 13–18. http://dx.doi.org/10.1152/physiol.00045.2005.

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Cryoelectronmicroscopy is a method for the imaging of macromolecules in the electron microscope. It was originally developed to determine membrane protein structures from two-dimensional crystals, but more recently “single-particle” techniques have become powerful and popular. Three-dimensional reconstructions are obtained from sets of single-particle images by extensive computer processing; the methods are being applied to many macromolecular assemblies.

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13

Stewart, P. L., and G. R. Nemerow. "Combining structures from cryo-EM and x-ray crystallography." Proceedings, annual meeting, Electron Microscopy Society of America 53 (August 13, 1995): 44–45. http://dx.doi.org/10.1017/s0424820100136593.

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Cryo-electron microscopy (cryo-EM) combined with three-dimensional image reconstruction techniques has produced structures of large macromolecular assemblies. Interpretation of low resolution (25-35 A) cryo-EM density can be greatly enhanced by mapping in crystallographic structures of component molecules. Difference imaging between the cryo-EM structure of the human adenovirus particle and a capsid calculated from the crystal structure of the major structural protein, hexon, revealed numerous minor structural components in the viral capsid. In addition, the atomic binding sites of the minor protein components were visualized on the crystallographic structure of hexon. Current studies are focused on examining the structural events during adenovirus cell entry. The receptor that triggers adenovirus internalization has been shown to be αv integrin. Cryo-EM is being used to solve the structure of adenovirus with bound Fab fragments from a monoclonal antibody that blocks binding of the virus to the receptor (Fig. 1). The antibody recognizes a linear epitope of nine amino acids that includes an Arg-Gly-Asp (RGD) integrin binding motif.

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14

Chari, Ashwin, and Holger Stark. "Prospects and Limitations of High-Resolution Single-Particle Cryo-Electron Microscopy." Annual Review of Biophysics 52, no. 1 (May 9, 2023): 391–411. http://dx.doi.org/10.1146/annurev-biophys-111622-091300.

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Single particle cryo-electron microscopy (cryo-EM) has matured into a robust method for the determination of biological macromolecule structures in the past decade, complementing X-ray crystallography and nuclear magnetic resonance. Constant methodological improvements in both cryo-EM hardware and image processing software continue to contribute to an exponential growth in the number of structures solved annually. In this review, we provide a historical view of the many steps that were required to make cryo-EM a successful method for the determination of high-resolution protein complex structures. We further discuss aspects of cryo-EM methodology that are the greatest pitfalls challenging successful structure determination to date. Lastly, we highlight and propose potential future developments that would improve the method even further in the near future.

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15

García-Nafría, Javier, and Christopher G. Tate. "Cryo-Electron Microscopy: Moving Beyond X-Ray Crystal Structures for Drug Receptors and Drug Development." Annual Review of Pharmacology and Toxicology 60, no. 1 (January 6, 2020): 51–71. http://dx.doi.org/10.1146/annurev-pharmtox-010919-023545.

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Electron cryo-microscopy (cryo-EM) has revolutionized structure determination of membrane proteins and holds great potential for structure-based drug discovery. Here we discuss the potential of cryo-EM in the rational design of therapeutics for membrane proteins compared to X-ray crystallography. We also detail recent progress in the field of drug receptors, focusing on cryo-EM of two protein families with established therapeutic value, the γ-aminobutyric acid A receptors (GABAARs) and G protein–coupled receptors (GPCRs). GABAARs are pentameric ion channels, and cryo-EM structures of physiological heteromeric receptors in a lipid environment have uncovered the molecular basis of receptor modulation by drugs such as diazepam. The structures of ten GPCR–G protein complexes from three different classes of GPCRs have now been determined by cryo-EM. These structures give detailed insights into molecular interactions with drugs, GPCR–G protein selectivity, how accessory membrane proteins alter receptor–ligand pharmacology, and the mechanism by which HIV uses GPCRs to enter host cells.

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16

Misiaszek, Agata D., Mathias Girbig, Helga Grötsch, Florence Baudin, Brice Murciano, Aleix Lafita, and Christoph W. Müller. "Cryo-EM structures of human RNA polymerase I." Nature Structural & Molecular Biology 28, no. 12 (December 2021): 997–1008. http://dx.doi.org/10.1038/s41594-021-00693-4.

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AbstractRNA polymerase I (Pol I) specifically synthesizes ribosomal RNA. Pol I upregulation is linked to cancer, while mutations in the Pol I machinery lead to developmental disorders. Here we report the cryo-EM structure of elongating human Pol I at 2.7 Å resolution. In the exit tunnel, we observe a double-stranded RNA helix that may support Pol I processivity. Our structure confirms that human Pol I consists of 13 subunits with only one subunit forming the Pol I stalk. Additionally, the structure of human Pol I in complex with the initiation factor RRN3 at 3.1 Å resolution reveals stalk flipping upon RRN3 binding. We also observe an inactivated state of human Pol I bound to an open DNA scaffold at 3.3 Å resolution. Lastly, the high-resolution structure of human Pol I allows mapping of disease-related mutations that can aid understanding of disease etiology.

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17

Pintilie, Grigore, and Wah Chiu. "Validation, analysis and annotation of cryo-EM structures." Acta Crystallographica Section D Structural Biology 77, no. 9 (August 31, 2021): 1142–52. http://dx.doi.org/10.1107/s2059798321006069.

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

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18

Jin, Qiuheng, Bo Zhang, Xiang Zheng, Ningning Li, Lingyi Xu, Yuan Xie, Fangjun Song, et al. "Cryo-EM structures of human pannexin 1 channel." Cell Research 30, no. 5 (April 3, 2020): 449–51. http://dx.doi.org/10.1038/s41422-020-0310-0.

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19

Tringides, Marios L., Zhemin Zhang, Christopher E. Morgan, Chih-Chia Su, and Edward W. Yu. "A cryo-electron microscopic approach to elucidate protein structures from human brain microsomes." Life Science Alliance 6, no. 2 (November 30, 2022): e202201724. http://dx.doi.org/10.26508/lsa.202201724.

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We recently developed a “Build and Retrieve” cryo-electron microscopy (cryo-EM) methodology, which is capable of simultaneously producing near-atomic resolution cryo-EM maps for several individual proteins from a heterogeneous, multiprotein sample. Here we report the use of “Build and Retrieve” to define the composition of a raw human brain microsomal lysate. From this sample, we simultaneously identify and solve cryo-EM structures of five different brain enzymes whose functions affect neurotransmitter recycling, iron metabolism, glycolysis, axonal development, energy homeostasis, and retinoic acid biosynthesis. Interestingly, malfunction of these important proteins has been directly linked to several neurodegenerative disorders, such as Alzheimer’s, Huntington’s, and Parkinson’s diseases. Our work underscores the importance of cryo-EM in facilitating tissue and organ proteomics at the atomic level.

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20

Kimanius, Dari, Gustav Zickert, Takanori Nakane, Jonas Adler, Sebastian Lunz, Carola-Bibiane Schönlieb, Ozan Öktem, and Sjors H. W. Scheres. "Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination." IUCrJ 8, no. 1 (January 1, 2021): 60–75. http://dx.doi.org/10.1107/s2052252520014384.

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Three-dimensional reconstruction of the electron-scattering potential of biological macromolecules from electron cryo-microscopy (cryo-EM) projection images is an ill-posed problem. The most popular cryo-EM software solutions to date rely on a regularization approach that is based on the prior assumption that the scattering potential varies smoothly over three-dimensional space. Although this approach has been hugely successful in recent years, the amount of prior knowledge that it exploits compares unfavorably with the knowledge about biological structures that has been accumulated over decades of research in structural biology. Here, a regularization framework for cryo-EM structure determination is presented that exploits prior knowledge about biological structures through a convolutional neural network that is trained on known macromolecular structures. This neural network is inserted into the iterative cryo-EM structure-determination process through an approach that is inspired by regularization by denoising. It is shown that the new regularization approach yields better reconstructions than the current state of the art for simulated data, and options to extend this work for application to experimental cryo-EM data are discussed.

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21

Henderson, Richard, and Samar Hasnain. "`Cryo-EM': electron cryomicroscopy, cryo electron microscopy or something else?" IUCrJ 10, no. 5 (September 1, 2023): 519–20. http://dx.doi.org/10.1107/s2052252523006759.

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Structural biology continues to benefit from an expanding toolkit, which is helping to gain unprecedented insight into the assembly and organization of multi-protein machineries, enzyme mechanisms and ligand/inhibitor binding. During the last ten years, cryoEM has become widely available and has provided a major boost to structure determination of membrane proteins and large multi-protein complexes. Many of the structures have now been made available at resolutions around 2 Å, where fundamental questions regarding enzyme mechanisms can be addressed. Over the years, the abbreviation cryoEM has been understood to stand for different things. We wish the wider community to engage and clarify the definition of cryoEM so that the expanding literature involving cryoEM is unified.

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22

Zeng, Lingxiao, Wei Ding, and Quan Hao. "Using cryo-electron microscopy maps for X-ray structure determination of homologues." Acta Crystallographica Section D Structural Biology 76, no. 1 (January 1, 2020): 63–72. http://dx.doi.org/10.1107/s2059798319015924.

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The combination of cryo-electron microscopy (cryo-EM) and X-ray crystallography reflects an important trend in structural biology. In a previously published study, a hybrid method for the determination of X-ray structures using initial phases provided by the corresponding parts of cryo-EM maps was presented. However, if the target structure of X-ray crystallography is not identical but homologous to the corresponding molecular model of the cryo-EM map, then the decrease in the accuracy of the starting phases makes the whole process more difficult. Here, a modified hybrid method is presented to handle such cases. The whole process includes three steps: cryo-EM map replacement, phase extension by NCS averaging and dual-space iterative model building. When the resolution gap between the cryo-EM and X-ray crystallographic data is large and the sequence identity is low, an intermediate stage of model building is necessary. Six test cases have been studied with sequence identity between the corresponding molecules in the cryo-EM and X-ray structures ranging from 34 to 52% and with sequence similarity ranging from 86 to 91%. This hybrid method consistently produced models with reasonable R work and R free values which agree well with the previously determined X-ray structures for all test cases, thus indicating the general applicability of the method for X-ray structure determination of homologues using cryo-EM maps as a starting point.

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23

Kikkawa, Masahide, and Haruaki Yanagisawa. "Identifying proteins in the cell by tagging techniques for cryo-electron microscopy." Microscopy 71, Supplement_1 (February 18, 2022): i60—i65. http://dx.doi.org/10.1093/jmicro/dfab059.

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Abstract Cryo-electron microscopy (cryo-EM) is currently expanding its application from molecular structures to cellular structures. The cellular environment is heterogeneous, containing many different proteins, and very crowded. This environment is in sharp contrast to the specimens for single particle analysis, by which purified homogeneous samples are analyzed. To answer biological questions from the structural studies of cells, it is crucial to identify biological molecules (typically, proteins) of interest and tagging is becoming the critical technique for cryo-EM. In this review, we explain the requirements for tags and review recent advances of tagging and identification methods for cryo-EM.

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24

Morris, Edward P., and Paula C. A. da Fonseca. "High-resolution cryo-EM proteasome structures in drug development." Acta Crystallographica Section D Structural Biology 73, no. 6 (May 31, 2017): 522–33. http://dx.doi.org/10.1107/s2059798317007021.

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With the recent advances in biological structural electron microscopy (EM), protein structures can now be obtained by cryo-EM and single-particle analysis at resolutions that used to be achievable only by crystallographic or NMR methods. We have explored their application to study protein–ligand interactions using the human 20S proteasome, a well established target for cancer therapy that is also being investigated as a target for an increasing range of other medical conditions. The map of a ligand-bound human 20S proteasome served as a proof of principle that cryo-EM is emerging as a realistic approach for more general structural studies of protein–ligand interactions, with the potential benefits of extending such studies to complexes that are unfavourable to other methods and allowing structure determination under conditions that are closer to physiological, preserving ligand specificity towards closely related binding sites. Subsequently, the cryo-EM structure of thePlasmodium falciparum20S proteasome, with a new prototype specific inhibitor bound, revealed the molecular basis for the ligand specificity towards the parasite complex, which provides a framework to guide the development of highly needed new-generation antimalarials. Here, the cryo-EM analysis of the ligand-bound human andP. falciparum20S proteasomes is reviewed, and a complete description of the methods used for structure determination is provided, including the strategy to overcome the bias orientation of the human 20S proteasome on electron-microscope grids and details of theicr3dsoftware used for three-dimensional reconstruction.

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25

Chandra, Mintu, Amy K. Kendall, and Lauren P. Jackson. "Unveiling the cryo-EM structure of retromer." Biochemical Society Transactions 48, no. 5 (October 14, 2020): 2261–72. http://dx.doi.org/10.1042/bst20200552.

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Retromer (VPS26/VPS35/VPS29) is a highly conserved eukaryotic protein complex that localizes to endosomes to sort transmembrane protein cargoes into vesicles and elongated tubules. Retromer mediates retrieval pathways from endosomes to the trans-Golgi network in all eukaryotes and further facilitates recycling pathways to the plasma membrane in metazoans. In cells, retromer engages multiple partners to orchestrate the formation of tubulovesicular structures, including sorting nexin (SNX) proteins, cargo adaptors, GTPases, regulators, and actin remodeling proteins. Retromer-mediated pathways are especially important for sorting cargoes required for neuronal maintenance, which links retromer loss or mutations to multiple human brain diseases and disorders. Structural and biochemical studies have long contributed to the understanding of retromer biology, but recent advances in cryo-electron microscopy and cryo-electron tomography have further uncovered exciting new snapshots of reconstituted retromer structures. These new structures reveal retromer assembles into an arch-shaped scaffold and suggest the scaffold may be flexible and adaptable in cells. Interactions with cargo adaptors, particularly SNXs, likely orient the scaffold with respect to phosphatidylinositol-3-phosphate (PtdIns3P)-enriched membranes. Pharmacological small molecule chaperones have further been shown to stabilize retromer in cultured cell and mouse models, but mechanisms by which these molecules bind remain unknown. This review will emphasize recent structural and biophysical advances in understanding retromer structure as the field moves towards a molecular view of retromer assembly and regulation on membranes.

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Ravikumar, Ashraya, Mrugsen Nagsen Gopnarayan, Sriram Subramaniam, and Narayanaswamy Srinivasan. "Comparison of side-chain dispersion in protein structures determined by cryo-EM and X-ray crystallography." IUCrJ 9, no. 1 (December 10, 2021): 98–103. http://dx.doi.org/10.1107/s2052252521011945.

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An evaluation of systematic differences in local structure and conformation in the interior of protein tertiary structures determined by crystallography and by cryo-electron microscopy (cryo-EM) is reported. The expectation is that any consistent differences between the derived atomic models could provide insights into variations in side-chain packing that result from differences in specimens prepared for analysis between these two methods. By computing an atomic packing score, which provides a quantitative measure of clustering of side-chain atoms in the core of the tertiary structures, it is found that, in general, for structures determined by cryo-EM, side chains are more dispersed than in structures determined by X-ray crystallography over a similar resolution range. This trend is also observed in the packing comparison at subunit interfaces. Similar trends were observed in the packing comparison at the core of tertiary structures of the same proteins determined by both X-ray and cryo-EM methods. It is proposed here that the reduced dispersion of side chains in protein crystals could be due to some level of dehydration in 3D crystals prepared for X-ray crystallography and also because the higher rate of freezing of protein samples for cryo-EM may enable preservation of a more native conformation.

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27

Svensson, Bengt, David D. Thomas, and Razvan L. Cornea. "Visualizing Unresolved Segments in Ryanodine Receptor Cryo-EM Structures." Biophysical Journal 120, no. 3 (February 2021): 150a. http://dx.doi.org/10.1016/j.bpj.2020.11.1095.

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28

Goedert, Michel. "Cryo-EM structures of τ filaments from human brain". Essays in Biochemistry 65, № 7 (грудень 2021): 949–59. http://dx.doi.org/10.1042/ebc20210025.

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Abstract Electron cryo-microscopy (cryo-EM) has made it possible to determine near-atomic structures of τ filaments from human brain. Previous work had shown that the cores of paired helical and straight filaments of Alzheimer's disease are made of two identical, but differently arranged C-shaped protofilaments. In recent years, cryo-EM has shown that the Alzheimer τ fold is 79 amino acids long. Five of the eight β-strands give rise to two antiparallel β-sheets, with the other three forming a β-helix. High-affinity binding sites of positron emission tomography ligand APN-1607 (PM-PBB3) are in the β-helix region. The Alzheimer fold contrasts with the 94 amino acid-long Pick fold, which is J-shaped and comprises nine β-strands that give rise to four antiparallel β-sheets, in the absence of a β-helix. Chronic traumatic encephalopathy τ fold is similar to the Alzheimer fold, but differs in the β-helix region, which is larger and contains a non-proteinaceous density that is probably hydrophobic. These folds are mostly two-layered. By contrast, the 107 amino acid τ fold of the 4R tauopathy corticobasal degeneration is four-layered and comprises 11 β-strands. It contains an internal, probably hydrophilic, density that is surrounded by τ. The τ folds described here share the presence of microtubule-binding repeats 3 and 4, as well as 10–13 amino acids after repeat 4.

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29

Forino, Nicholas M., Jendrik Hentschel, and Michael D. Stone. "Cryo-EM structures tell a tale of two telomerases." Nature Structural & Molecular Biology 28, no. 6 (May 28, 2021): 457–59. http://dx.doi.org/10.1038/s41594-021-00611-8.

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30

Ellinger, Emily M., Adrien Chauvier, Jason Porta, Aaron T. Frank, Melanie D. Ohi, and Nils G. Walter. "Cryo-EM structures of riboswitches in paused elongation complexes." Biophysical Journal 121, no. 3 (February 2022): 359a. http://dx.doi.org/10.1016/j.bpj.2021.11.951.

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31

Sigworth, Fred J. "From cryo-EM, multiple protein structures in one shot." Nature Methods 4, no. 1 (January 2007): 20–21. http://dx.doi.org/10.1038/nmeth0107-20.

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32

Fitzpatrick, Anthony W. P., Benjamin Falcon, Shaoda He, Alexey G. Murzin, Garib Murshudov, Holly J. Garringer, R. Anthony Crowther, Bernardino Ghetti, Michel Goedert, and Sjors H. W. Scheres. "Cryo-EM structures of tau filaments from Alzheimer’s disease." Nature 547, no. 7662 (July 2017): 185–90. http://dx.doi.org/10.1038/nature23002.

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Mao, Chunyou, Cangsong Shen, Chuntao Li, Dan-Dan Shen, Chanjuan Xu, Shenglan Zhang, Rui Zhou, et al. "Cryo-EM structures of inactive and active GABAB receptor." Cell Research 30, no. 7 (June 3, 2020): 564–73. http://dx.doi.org/10.1038/s41422-020-0350-5.

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Gilbert, Robert J. C., Paola Fucini, Sean Connell, Stephen D. Fuller, Knud H. Nierhaus, Carol V. Robinson, Christopher M. Dobson, and David I. Stuart. "Three-Dimensional Structures of Translating Ribosomes by Cryo-EM." Molecular Cell 14, no. 1 (April 2004): 57–66. http://dx.doi.org/10.1016/s1097-2765(04)00163-7.

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McCoy, Airlie, Randy Read, Robert Oeffner, and Andrea Thorn. "Solving X-ray crystal structures with cryo-EM reconstructions." Acta Crystallographica Section A Foundations and Advances 74, a2 (August 22, 2018): e150-e150. http://dx.doi.org/10.1107/s205327331809304x.

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36

Egelman, Edward H., and Fengbin Wang. "Cryo-EM is a powerful tool, but helical applications can have pitfalls." Soft Matter 17, no. 12 (2021): 3291–93. http://dx.doi.org/10.1039/d1sm00282a.

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Kochovski, Zdravko, Guosong Chen, Jiayin Yuan, and Yan Lu. "Cryo-Electron microscopy for the study of self-assembled poly(ionic liquid) nanoparticles and protein supramolecular structures." Colloid and Polymer Science 298, no. 7 (May 23, 2020): 707–17. http://dx.doi.org/10.1007/s00396-020-04657-w.

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Abstract Cryo-electron microscopy (cryo-EM) is a powerful structure determination technique that is well-suited to the study of protein and polymer self-assembly in solution. In contrast to conventional transmission electron microscopy (TEM) sample preparation, which often times involves drying and staining, the frozen-hydrated sample preparation allows the specimens to be kept and imaged in a state closest to their native one. Here, we give a short overview of the basic principles of Cryo-EM and review our results on applying it to the study of different protein and polymer self-assembled nanostructures. More specifically, we show how we have applied cryo-electron tomography (cryo-ET) to visualize the internal morphology of self-assembled poly(ionic liquid) nanoparticles and cryo-EM single particle analysis (SPA) to determine the three-dimensional (3D) structures of artificial protein microtubules.

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García-Nafría, Javier, and Christopher G. Tate. "Structure determination of GPCRs: cryo-EM compared with X-ray crystallography." Biochemical Society Transactions 49, no. 5 (September 28, 2021): 2345–55. http://dx.doi.org/10.1042/bst20210431.

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G protein-coupled receptors (GPCRs) are the largest single family of cell surface receptors encoded by the human genome and they play pivotal roles in co-ordinating cellular systems throughout the human body, making them ideal drug targets. Structural biology has played a key role in defining how receptors are activated and signal through G proteins and β-arrestins. The application of structure-based drug design (SBDD) is now yielding novel compounds targeting GPCRs. There is thus significant interest from both academia and the pharmaceutical industry in the structural biology of GPCRs as currently only about one quarter of human non-odorant receptors have had their structure determined. Initially, all the structures were determined by X-ray crystallography, but recent advances in electron cryo-microscopy (cryo-EM) now make GPCRs tractable targets for single-particle cryo-EM with comparable resolution to X-ray crystallography. So far this year, 78% of the 99 GPCR structures deposited in the PDB (Jan–Jul 2021) were determined by cryo-EM. Cryo-EM has also opened up new possibilities in GPCR structural biology, such as determining structures of GPCRs embedded in a lipid nanodisc and multiple GPCR conformations from a single preparation. However, X-ray crystallography still has a number of advantages, particularly in the speed of determining many structures of the same receptor bound to different ligands, an essential prerequisite for effective SBDD. We will discuss the relative merits of cryo-EM and X-ray crystallography for the structure determination of GPCRs and the future potential of both techniques.

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Lyu, Meinan, Chih-Chia Su, Masaru Miyagi, and Edward W. Yu. "Simultaneous solving high-resolution structures of various enzymes from human kidney microsomes." Life Science Alliance 6, no. 2 (November 30, 2022): e202201580. http://dx.doi.org/10.26508/lsa.202201580.

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The ability to investigate tissues and organs through an integrated systems biology approach has been thought to be unobtainable in the field of structural biology, where the techniques mainly focus on a particular biomacromolecule of interest. Here we report the use of cryo-electron microscopy (cryo-EM) to define the composition of a raw human kidney microsomal lysate. We simultaneously identify and solve cryo-EM structures of four distinct kidney enzymes whose functions have been linked to protein biosynthesis and quality control, biosynthesis of retinoic acid, gluconeogenesis and glycolysis, and the regulation and metabolism of amino acids. Interestingly, all four of these enzymes are directly linked to cellular processes that, when disrupted, can contribute to the onset and progression of diabetes. This work underscores the potential of cryo-EM to facilitate tissue and organ proteomics at the atomic level.

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Liebschner, Dorothee, Pavel V. Afonine, Nigel W. Moriarty, Billy K. Poon, Vincent B. Chen, and Paul D. Adams. "CERES: a cryo-EM re-refinement system for continuous improvement of deposited models." Acta Crystallographica Section D Structural Biology 77, no. 1 (January 1, 2021): 48–61. http://dx.doi.org/10.1107/s2059798320015879.

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The field of electron cryomicroscopy (cryo-EM) has advanced quickly in recent years as the result of numerous technological and methodological developments. This has led to an increase in the number of atomic structures determined using this method. Recently, several tools for the analysis of cryo-EM data and models have been developed within the Phenix software package, such as phenix.real_space_refine for the refinement of atomic models against real-space maps. Also, new validation metrics have been developed for low-resolution cryo-EM models. To understand the quality of deposited cryo-EM structures and how they might be improved, models deposited in the Protein Data Bank that have map resolutions of better than 5 Å were automatically re-refined using current versions of Phenix tools. The results are available on a publicly accessible web page (https://cci.lbl.gov/ceres). The implementation of a Cryo-EM Re-refinement System (CERES) for the improvement of models deposited in the wwPDB, and the results of the re-refinements, are described. Based on these results, contents are proposed for a `cryo-EM Table 1', which summarizes experimental details and validation metrics in a similar way to `Table 1' in crystallography. The consistent use of robust metrics for the evaluation of cryo-EM models and data should accompany every structure deposition and be reported in scientific publications.

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Lévy, Daniel, Aurélie Di Cicco, Aurélie Bertin, and Manuela Dezi. "La cryo-microscopie électronique révèle une nouvelle vision de la cellule et de ses composants." médecine/sciences 37, no. 4 (April 2021): 379–85. http://dx.doi.org/10.1051/medsci/2021034.

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La cryo-microscopie électronique (cryo-EM) est une technique d’imagerie du vivant qui prend désormais une place prépondérante en biologie structurale, avec des retombées en biologie cellulaire et du développement, en bioinformatique, en biomédecine ou en physique de la cellule. Elle permet de déterminer des structures de protéines purifiées in vitro ou au sein des cellules. Cette revue décrit les principales avancées récentes de la cryo-EM, illustrées par des exemples d’élucidation de structures de protéines d’intérêt en biomédecine, et les pistes de développements futurs.

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Lian, Ruyi, Bingyao Huang, Liguo Wang, Qun Liu, Yuewei Lin, and Haibin Ling. "End-to-end orientation estimation from 2D cryo-EM images." Acta Crystallographica Section D Structural Biology 78, no. 2 (January 21, 2022): 174–86. http://dx.doi.org/10.1107/s2059798321011761.

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Cryo-electron microscopy (cryo-EM) is a Nobel Prize-winning technique for determining high-resolution 3D structures of biological macromolecules. A 3D structure is reconstructed from hundreds of thousands of noisy 2D projection images. However, existing 3D reconstruction methods are still time-consuming, and one of the major computational bottlenecks is recovering the unknown orientation of the particle in each 2D image. The dominant methods typically exploit an expensive global search on each image to estimate the missing orientations. Here, a novel end-to-end supervised learning method is introduced to directly recover the missing orientations from 2D cryo-EM images. A neural network is used to approximate the mapping from images to orientations. A robust loss function is proposed for optimizing the parameters of the network, which can handle both asymmetric and symmetric 3D structures. Experiments on synthetic data sets with various symmetry types confirm that the neural network is capable of recovering orientations from 2D cryo-EM images, and the results on a real cryo-EM data set further demonstrate its potential under more challenging imaging conditions.

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43

Lander, Gabriel C., and Robert M. Glaeser. "Conquer by cryo-EM without physically dividing." Biochemical Society Transactions 49, no. 5 (October 28, 2021): 2287–98. http://dx.doi.org/10.1042/bst20210360.

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This mini-review provides an update regarding the substantial progress that has been made in using single-particle cryo-EM to obtain high-resolution structures for proteins and other macromolecules whose particle sizes are smaller than 100 kDa. We point out that establishing the limits of what can be accomplished, both in terms of particle size and attainable resolution, serves as a guide for what might be expected when attempting to improve the resolution of small flexible portions of a larger structure using focused refinement approaches. These approaches, which involve computationally ignoring all but a specific, targeted region of interest on the macromolecules, is known as ‘masking and refining,' and it thus is the computational equivalent of the ‘divide and conquer' approach that has been used so successfully in X-ray crystallography. The benefit of masked refinement, however, is that one is able to determine structures in their native architectural context, without physically separating them from the biological connections that they require for their function. This mini-review also compares where experimental achievements currently stand relative to various theoretical estimates for the smallest particle size that can be successfully reconstructed to high resolution. Since it is clear that a substantial gap still remains between the two, we briefly recap the areas in which further improvement seems possible, both in equipment and in methods.

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Boland, Andreas, Leifu Chang, and David Barford. "The potential of cryo-electron microscopy for structure-based drug design." Essays in Biochemistry 61, no. 5 (November 8, 2017): 543–60. http://dx.doi.org/10.1042/ebc20170032.

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Structure-based drug design plays a central role in therapeutic development. Until recently, protein crystallography and NMR have dominated experimental approaches to obtain structural information of biological molecules. However, in recent years rapid technical developments in single particle cryo-electron microscopy (cryo-EM) have enabled the determination to near-atomic resolution of macromolecules ranging from large multi-subunit molecular machines to proteins as small as 64 kDa. These advances have revolutionized structural biology by hugely expanding both the range of macromolecules whose structures can be determined, and by providing a description of macromolecular dynamics. Cryo-EM is now poised to similarly transform the discipline of structure-based drug discovery. This article reviews the potential of cryo-EM for drug discovery with reference to protein ligand complex structures determined using this technique.

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45

Ultee, Eveline, Fred Schenkel, Wen Yang, Susanne Brenzinger, Jamie S. Depelteau, and Ariane Briegel. "An Open-Source Storage Solution for Cryo-Electron Microscopy Samples." Microscopy and Microanalysis 24, no. 1 (January 18, 2018): 60–63. http://dx.doi.org/10.1017/s143192761701279x.

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AbstractCryo-electron microscopy (cryo-EM) enables the study of biological structures in situ in great detail and to solve protein structures at Ångstrom level resolution. Due to recent advances in instrumentation and data processing, the field of cryo-EM is a rapidly growing. Access to facilities and national centers that house the state-of-the-art microscopes is limited due to the ever-rising demand, resulting in long wait times between sample preparation and data acquisition. To improve sample storage, we have developed a cryo-storage system with an efficient, high storage capacity that enables sample storage in a highly organized manner. This system is simple to use, cost-effective and easily adaptable for any type of grid storage box and dewar and any size cryo-EM laboratory.

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46

Yonekura, Koji, and Saori Maki-Yonekura. "Refinement of cryo-EM structures using scattering factors of charged atoms." Journal of Applied Crystallography 49, no. 5 (August 24, 2016): 1517–23. http://dx.doi.org/10.1107/s1600576716011274.

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This paper reports a suitable treatment of electron scattering factors of charged atoms for refinement of atomic models against cryo-electron microscopy (cryo-EM) maps. The ScatCurve package developed here supports various curve models for parameterization of scattering factors and the parameter tables can be implemented in major refinement programs in structural biology. Partial charge values of charged amino acids in crystal structures were changed in small steps for refinement of the atomic models against electron diffraction data from three-dimensional crystals. By exploring a range of partial charges, the authors found the electrostatic setting that produces atomic models with improved statistics and better reflects experimental data. Structure refinement for single-particle analysis also benefits from the more accurate analysis and the programs could find wide use for model refinement against cryo-EM maps.

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47

Creekmore, Benjamin C., Yi-Wei Chang, and Edward B. Lee. "The Cryo-EM Effect: Structural Biology of Neurodegenerative Disease Aggregates." Journal of Neuropathology & Experimental Neurology 80, no. 6 (May 10, 2021): 514–29. http://dx.doi.org/10.1093/jnen/nlab039.

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Abstract Neurogenerative diseases are characterized by diverse protein aggregates with a variety of microscopic morphologic features. Although ultrastructural studies of human neurodegenerative disease tissues have been conducted since the 1960s, only recently have near-atomic resolution structures of neurodegenerative disease aggregates been described. Solid-state nuclear magnetic resonance spectroscopy and X-ray crystallography have provided near-atomic resolution information about in vitro aggregates but pose logistical challenges to resolving the structure of aggregates derived from human tissues. Recent advances in cryo-electron microscopy (cryo-EM) have provided the means for near-atomic resolution structures of tau, amyloid-β (Aβ), α-synuclein (α-syn), and transactive response element DNA-binding protein of 43 kDa (TDP-43) aggregates from a variety of diseases. Importantly, in vitro aggregate structures do not recapitulate ex vivo aggregate structures. Ex vivo tau aggregate structures indicate individual tauopathies have a consistent aggregate structure unique from other tauopathies. α-syn structures show that even within a disease, aggregate heterogeneity may correlate to disease course. Ex vivo structures have also provided insight into how posttranslational modifications may relate to aggregate structure. Though there is less cryo-EM data for human tissue-derived TDP-43 and Aβ, initial structural studies provide a basis for future endeavors. This review highlights structural variations across neurodegenerative diseases and reveals fundamental differences between experimental systems and human tissue derived protein inclusions.

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Avramov, Todor, Dan Vyenielo, Josue Gomez-Blanco, Swathi Adinarayanan, Javier Vargas, and Dong Si. "Deep Learning for Validating and Estimating Resolution of Cryo-Electron Microscopy Density Maps †." Molecules 24, no. 6 (March 26, 2019): 1181. http://dx.doi.org/10.3390/molecules24061181.

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Cryo-electron microscopy (cryo-EM) is becoming the imaging method of choice for determining protein structures. Many atomic structures have been resolved based on an exponentially growing number of published three-dimensional (3D) high resolution cryo-EM density maps. However, the resolution value claimed for the reconstructed 3D density map has been the topic of scientific debate for many years. The Fourier Shell Correlation (FSC) is the currently accepted cryo-EM resolution measure, but it can be subjective, manipulated, and has its own limitations. In this study, we first propose supervised deep learning methods to extract representative 3D features at high, medium and low resolutions from simulated protein density maps and build classification models that objectively validate resolutions of experimental 3D cryo-EM maps. Specifically, we build classification models based on dense artificial neural network (DNN) and 3D convolutional neural network (3D CNN) architectures. The trained models can classify a given 3D cryo-EM density map into one of three resolution levels: high, medium, low. The preliminary DNN and 3D CNN models achieved 92.73% accuracy and 99.75% accuracy on simulated test maps, respectively. Applying the DNN and 3D CNN models to thirty experimental cryo-EM maps achieved an agreement of 60.0% and 56.7%, respectively, with the author published resolution value of the density maps. We further augment these previous techniques and present preliminary results of a 3D U-Net model for local resolution classification. The model was trained to perform voxel-wise classification of 3D cryo-EM density maps into one of ten resolution classes, instead of a single global resolution value. The U-Net model achieved 88.3% and 94.7% accuracy when evaluated on experimental maps with local resolutions determined by MonoRes and ResMap methods, respectively. Our results suggest deep learning can potentially improve the resolution evaluation process of experimental cryo-EM maps.

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Fàbrega-Ferrer, Montserrat, Ana Cuervo, Francisco J. Fernández, Cristina Machón, Rosa Pérez-Luque, Joan Pous, M. Cristina Vega, José L. Carrascosa, and Miquel Coll. "Using a partial atomic model from medium-resolution cryo-EM to solve a large crystal structure." Acta Crystallographica Section D Structural Biology 77, no. 1 (January 1, 2021): 11–18. http://dx.doi.org/10.1107/s2059798320015156.

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Medium-resolution cryo-electron microscopy maps, in particular when they include a significant number of α-helices, may allow the building of partial models that are useful for molecular-replacement searches in large crystallographic structures when the structures of homologs are not available and experimental phasing has failed. Here, as an example, the solution of the structure of a bacteriophage portal using a partial 30% model built into a 7.8 Å resolution cryo-EM map is shown. Inspection of the self-rotation function allowed the correct oligomerization state to be determined, and density-modification procedures using rotation matrices and a mask based on the cryo-EM structure were critical for solving the structure. A workflow is described that may be applicable to similar cases and this strategy is compared with direct use of the cryo-EM map for molecular replacement.

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50

Chen, Lin, Brandon Baker, Eduardo Santos, Michell Sheep, and Darius Daftarian. "A Visualization Tool for Cryo-EM Protein Validation with an Unsupervised Machine Learning Model in Chimera Platform." Medicines 6, no. 3 (August 6, 2019): 86. http://dx.doi.org/10.3390/medicines6030086.

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Background: Cryo-electron microscopy (cryo-EM) has become a major technique for protein structure determination. However, due to the low quality of cryo-EM density maps, many protein structures derived from cryo-EM contain outliers introduced during the modeling process. The current protein model validation system lacks identification features for cryo-EM proteins making it not enough to identify outliers in cryo-EM proteins. Methods: This study introduces an efficient unsupervised outlier detection model for validating protein models built from cryo-EM technique. The current model uses a high-resolution X-ray dataset (<1.5 Å) as the reference dataset. The distal block distance, side-chain length, phi, psi, and first chi angle of the residues in the reference dataset are collected and saved as a database of the histogram-based outlier score (HBOS). The HBOS value of the residues in target cryo-EM proteins can be read from this HBOS database. Results: Protein residues with a HBOS value greater than ten are labeled as outliers by default. Four datasets containing proteins derived from cryo-EM density maps were tested with this probabilistic anomaly detection model. Conclusions: According to the proposed model, a visualization assistant tool was designed for Chimera, a protein visualization platform.

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