Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 7Advanced Electron Microscopy Techniques and ApplicationsEnzyme Structure and FunctionProtein Structure and Dynamics

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Factors affecting macromolecule orientations in thin films formed in cryo-EM

Open access
Yadav, Swati, Vinothkumar, Kutti R.·2024·Acta Crystallographica Section D Structural Biology
DOI 10.1107/s2059798324005229PMC PMC11220838

Published version of a preprint

Open this paper in CoChat — free account

Abstract

The formation of a vitrified thin film embedded with randomly oriented macromolecules is an essential prerequisite for cryogenic sample electron microscopy. Most commonly, this is achieved using the plunge-freeze method first described nearly 40 years ago. Although this is a robust method, the behaviour of different macromolecules shows great variation upon freezing and often needs to be optimized to obtain an isotropic, high-resolution reconstruction. For a macromolecule in such a film, the probability of encountering the air–water interface in the time between blotting and freezing and adopting preferred orientations is very high. 3D reconstruction using preferentially oriented particles often leads to anisotropic and uninterpretable maps. Currently, there are no general solutions to this prevalent issue, but several approaches largely focusing on sample preparation with the use of additives and novel grid modifications have been attempted. In this study, the effect of physical and chemical factors on the orientations of macromolecules was investigated through an analysis of selected well studied macromolecules, and important parameters that determine the behaviour of proteins on cryo-EM grids were revealed. These insights highlight the nature of the interactions that cause preferred orientations and can be utilized to systematically address orientation bias for any given macromolecule and to provide a framework to design small-molecule additives to enhance sample stability and behaviour.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1107/s2059798324005229

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Examples of anisotropic cryo-EM maps resulting from orientation bias. The upper panel shows the reference-free 2D class averages of (a) SARS-CoV-2 spike protein and (b) human erythrocyte catalase. For the spike protein, preferred bottom views are observed. In the case of catalase, a preference for the top/bottom view is evident. In the lower panel, 3D maps with anisotropic features are shown for the preferred and perpendicular views as labelled. The symmetries applied during reconstruction were C1 and D2 for the spike protein and catalase, respectively.
Figure 1 Examples of anisotropic cryo-EM maps resulting from orientation bias. The upper panel shows the reference-free 2D class averages of (a) SARS-CoV-2 spike protein and (b) human erythrocyte catalase. For the spike protein, preferred bottom views are observed. In the case of catalase, a preference for the top/bottom view is evident. In the lower panel, 3D maps with anisotropic features are shown for the preferred and perpendicular views as labelled. The symmetries applied during reconstruction were C1 and D2 for the spike protein and catalase, respectively.CC BY · PubMed Central
Figure 2 Representative micrographs, with a few selected particles indicated with red circles, and 2D class averages of the test proteins used in this study. (a) The C-reactive protein (CRP) pentamer adopts a preferred bottom view, which shows the pentameric arrangement of the monomers. (b) The CRP decamer adopts a preferred side view, which shows the staggered arrangement of two CRP pentamers stacked on top of each other. The same micrograph is used in (a) and (b). (c) Catalase adopts a preferred top view, as seen in the micrograph and 2D class averages. (d) SARS-CoV-2 spike adopts a preferred bottom view showing the trimeric arrangement. (e) PaaZ adopts a preferred side view, as seen in the 2D class averages, and the micrograph shows occasional clumping of hexamers on the grids. (f) β-Galactosidase with an N-terminal polyhistidine tag adopts a preferred side view, as seen in the 2D class averages, and the micrograph shows aggregation on grids. For the above data sets, the catalase and PaaZ grids were prepared at 4°C and all other grids were prepared at 20°C.
Figure 2 Representative micrographs, with a few selected particles indicated with red circles, and 2D class averages of the test proteins used in this study. (a) The C-reactive protein (CRP) pentamer adopts a preferred bottom view, which shows the pentameric arrangement of the monomers. (b) The CRP decamer adopts a preferred side view, which shows the staggered arrangement of two CRP pentamers stacked on top of each other. The same micrograph is used in (a) and (b). (c) Catalase adopts a preferred top view, as seen in the micrograph and 2D class averages. (d) SARS-CoV-2 spike adopts a preferred bottom view showing the trimeric arrangement. (e) PaaZ adopts a preferred side view, as seen in the 2D class averages, and the micrograph shows occasional clumping of hexamers on the grids. (f) β-Galactosidase with an N-terminal polyhistidine tag adopts a preferred side view, as seen in the 2D class averages, and the micrograph shows aggregation on grids. For the above data sets, the catalase and PaaZ grids were prepared at 4°C and all other grids were prepared at 20°C.CC BY · PubMed Central
Figure 3 Orientation-distribution plots from RELION (Scheres, 2012 ▸) of proteins upon the addition of surfactants with varying properties to the sample buffer before grid preparation. The reference structures of the respective proteins are generated by creating a surface representation in ChimeraX from models from PDB entries 7pkb, 7pk9, 1dgf and 6jql. (a) Changes in the CRP pentamer orientation distribution upon the addition of surfactants. The distributions are distinct from each other, except for Tween 20 and Tween 80, which have similar distributions. (b) Changes in the CRP decamer orientation distribution upon surfactant addition; all surfactants lead to a similar even orientation distribution. (c) Changes in the catalase orientation distribution upon the addition of surfactants, where the charged surfactants have distinct distributions (CTAB and SLS) and the neutral surfactants (Tween 20 and Tween 80) and A8-35 show similar distributions. (d) Changes in PaaZ orientation distributions upon the addition of the cationic surfactant CTAB. The effects of SLS and Tween 20 on PaaZ were also tested, but visual inspection of the micrographs (Supplementary Fig. S3) showed no improvement and no data were collected; therefore they are not included (marked by asterisks). The effects of Tween 80 and A8-35 on PaaZ were not tested.
Figure 3 Orientation-distribution plots from RELION (Scheres, 2012 ▸) of proteins upon the addition of surfactants with varying properties to the sample buffer before grid preparation. The reference structures of the respective proteins are generated by creating a surface representation in ChimeraX from models from PDB entries 7pkb, 7pk9, 1dgf and 6jql. (a) Changes in the CRP pentamer orientation distribution upon the addition of surfactants. The distributions are distinct from each other, except for Tween 20 and Tween 80, which have similar distributions. (b) Changes in the CRP decamer orientation distribution upon surfactant addition; all surfactants lead to a similar even orientation distribution. (c) Changes in the catalase orientation distribution upon the addition of surfactants, where the charged surfactants have distinct distributions (CTAB and SLS) and the neutral surfactants (Tween 20 and Tween 80) and A8-35 show similar distributions. (d) Changes in PaaZ orientation distributions upon the addition of the cationic surfactant CTAB. The effects of SLS and Tween 20 on PaaZ were also tested, but visual inspection of the micrographs (Supplementary Fig. S3) showed no improvement and no data were collected; therefore they are not included (marked by asterisks). The effects of Tween 80 and A8-35 on PaaZ were not tested.CC BY · PubMed Central
Figure 4 The effect of a polyhistidine affinity tag on the SARS-CoV-2 spike protein and β-galactosidase orientation distributions. The different parameters that are used to analyse the quality of the maps are shown next to the orientation plots. N indicates the number of particles used for reconstruction, R indicates the final resolution of the map, S indicates the sphericity and Eod indicates the efficiency of Fourier space coverage. (a) The locations of the tags on the protein models are indicated by black stars. The models used as references are PDB entries 8h3d and 6cvm for the spike protein and β-galactosidase, respectively. (b) The orientation-distribution plots of the spike protein change upon removal of the affinity tag, but the change is not sufficient to obtain an isotropic map. The addition of the cationic surfactant CTAB further alters the orientations of the spike protein without tag and leads to a more isotropic map. β-Galactosidase enzyme (bottom panel) orientations change upon removal of the affinity tag and lead to an isotropic high-resolution map without any additive. The unsharpened final combined maps are shown in grey in (b).
Figure 4 The effect of a polyhistidine affinity tag on the SARS-CoV-2 spike protein and β-galactosidase orientation distributions. The different parameters that are used to analyse the quality of the maps are shown next to the orientation plots. N indicates the number of particles used for reconstruction, R indicates the final resolution of the map, S indicates the sphericity and Eod indicates the efficiency of Fourier space coverage. (a) The locations of the tags on the protein models are indicated by black stars. The models used as references are PDB entries 8h3d and 6cvm for the spike protein and β-galactosidase, respectively. (b) The orientation-distribution plots of the spike protein change upon removal of the affinity tag, but the change is not sufficient to obtain an isotropic map. The addition of the cationic surfactant CTAB further alters the orientations of the spike protein without tag and leads to a more isotropic map. β-Galactosidase enzyme (bottom panel) orientations change upon removal of the affinity tag and lead to an isotropic high-resolution map without any additive. The unsharpened final combined maps are shown in grey in (b).CC BY · PubMed Central
Figure 5 The effect of temperature during cryo-EM sample preparation of catalase and PaaZ. Micrographs, maps, orientation-distribution plots and the different parameters that are used to analyse the quality of the maps are shown. N indicates the number of particles used for reconstruction, R indicates the final resolution of the map, S indicates the sphericity and Eod indicates the efficiency of Fourier space coverage. (a) Catalase orientation distributions change significantly when grids are blotted at different temperatures in the absence of any additive. (b) PaaZ orientation distributions change slightly when grids are held and blotted at different temperatures in the absence of any additive. In the case of PaaZ, the condition with grids prepared at 4°C with CTAB as an additive is included for comparison as this combination led to a high-resolution isotropic map.
Figure 5 The effect of temperature during cryo-EM sample preparation of catalase and PaaZ. Micrographs, maps, orientation-distribution plots and the different parameters that are used to analyse the quality of the maps are shown. N indicates the number of particles used for reconstruction, R indicates the final resolution of the map, S indicates the sphericity and Eod indicates the efficiency of Fourier space coverage. (a) Catalase orientation distributions change significantly when grids are blotted at different temperatures in the absence of any additive. (b) PaaZ orientation distributions change slightly when grids are held and blotted at different temperatures in the absence of any additive. In the case of PaaZ, the condition with grids prepared at 4°C with CTAB as an additive is included for comparison as this combination led to a high-resolution isotropic map.CC BY · PubMed Central
Figure 6 High-resolution cryo-EM map from PaaZ grids prepared at 4°C with CTAB additive. (a) Comparison of the half-maps and map-versus-model FSCs of the PaaZ data set. (b) The six polypeptides coloured individually and in cartoon representation fitted into the cryo-EM map (transparent grey) of PaaZ. (c) Electrostatic potential surface representation of the domain-swapped PaaZ dimer with waters modelled and shown as cyan spheres. (d) ResLog plot of PaaZ with the experimental and theoretical numbers of particles required to reach a particular resolution. N indicates the number of particles used for reconstruction, d is the resolution and B indicates the B factor, as estimated by RELION post-processing. D3 symmetry was applied for the reconstruction and the ResLog plot indicates the number of particles used, not the number of asymmetric units averaged.
Figure 6 High-resolution cryo-EM map from PaaZ grids prepared at 4°C with CTAB additive. (a) Comparison of the half-maps and map-versus-model FSCs of the PaaZ data set. (b) The six polypeptides coloured individually and in cartoon representation fitted into the cryo-EM map (transparent grey) of PaaZ. (c) Electrostatic potential surface representation of the domain-swapped PaaZ dimer with waters modelled and shown as cyan spheres. (d) ResLog plot of PaaZ with the experimental and theoretical numbers of particles required to reach a particular resolution. N indicates the number of particles used for reconstruction, d is the resolution and B indicates the B factor, as estimated by RELION post-processing. D3 symmetry was applied for the reconstruction and the ResLog plot indicates the number of particles used, not the number of asymmetric units averaged.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 95

  1. Adrian, 1984, Nature, 308, 32, 10.1038/308032a0 · DOI
  2. Afonine, 2018, Acta Cryst. D, 74, 531, 10.1107/S2059798318006551 · DOI
  3. Aiyer, 2024, Nat. Commun., 15, 389, 10.1038/s41467-023-44555-7 · DOI
  4. Baek, 2021, Science, 373, 871, 10.1126/science.abj8754 · DOI · Paper page
  5. Bai, 2021, Trends Biochem. Sci., 46, 253, 10.1016/j.tibs.2021.01.001 · DOI
  6. Baker, 2021, Commun. Biol., 4, 625, 10.1038/s42003-021-02156-4 · DOI
  7. Bangaru, 2020, Science, 370, 1089, 10.1126/science.abe1502 · DOI · Paper page
  8. Bartesaghi, 2018, Structure, 26, 848, 10.1016/j.str.2018.04.004 · DOI
  9. Bodakuntla, 2023, Front. Mol. Biosci., 10, 1252529, 10.3389/fmolb.2023.1252529 · DOI
  10. Bromberg, 2022, Front. Mol. Biosci., 9, 912072, 10.3389/fmolb.2022.912072 · DOI
  11. Campbell, 2015, eLife, 4, e06380, 10.7554/eLife.06380 · DOI
  12. Carter-Fenk, 2021, Chem. Sci., 12, 8320, 10.1039/D1SC01276B · DOI
  13. Chaplin, 2009, Water, 1, 1, 10.3390/w1010001 · DOI
  14. Chen, 2019, J. Struct. Biol. X, 1, 100005
  15. Chen, 2022, Microscopy, 71, i51, 10.1093/jmicro/dfab037 · DOI
  16. Cheng, 2023, J. Am. Chem. Soc., 145, 8073, 10.1021/jacs.3c00659 · DOI
  17. Cheng, 2015, Cell, 161, 450, 10.1016/j.cell.2015.03.049 · DOI
  18. Chua, 2022, Annu. Rev. Biochem., 91, 1, 10.1146/annurev-biochem-032620-110705 · DOI
  19. Dandey, 2020, Nat. Methods, 17, 897, 10.1038/s41592-020-0925-6 · DOI
  20. D'Imprima, 2019, eLife, 8, e42747, 10.7554/eLife.42747 · DOI
  21. Drulyte, 2018, Acta Cryst. D, 74, 560, 10.1107/S2059798318006496 · DOI
  22. Drzymala, 1999, J. Colloid Interface Sci., 220, 229, 10.1006/jcis.1999.6528 · DOI
  23. Dubochet, 1988, Q. Rev. Biophys., 21, 129, 10.1017/S0033583500004297 · DOI · Paper page
  24. Dubochet, 1985, Trends Biochem. Sci., 10, 143, 10.1016/0968-0004(85)90150-1 · DOI
  25. Dubochet, 1982, J. Microsc., 128, 219, 10.1111/j.1365-2818.1982.tb04625.x · DOI
  26. Dubochet, 1981, J. Microsc., 124, 3, 10.1111/j.1365-2818.1981.tb02483.x · DOI
  27. Emsley, 2010, Acta Cryst. D, 66, 486, 10.1107/S0907444910007493 · DOI · Paper page
  28. Esfahani, 2024, bioRxiv, 20240124577038
  29. Fan, 2021, Nat. Commun., 12, 7257, 10.1038/s41467-021-27596-8 · DOI
  30. Frederik, 1989, J. Microsc., 153, 81, 10.1111/j.1365-2818.1989.tb01469.x · DOI
  31. Glaeser, 2017, Biophys. Rep., 3, 1, 10.1007/s41048-016-0026-3 · DOI
  32. Hardenbrook, 2022, Curr. Opin. Virol., 52, 123, 10.1016/j.coviro.2021.11.011 · DOI
  33. Harvey, W. T., Carabelli, A. M., Jackson, B., Gupta, R. K., Thomson, E. C., Harrison, E. M., Ludden, C., Reeve, R., Rambaut, A., COVID-19 Genomics UK (COG-UK) Consortium, Peacock, S. J. & Robertson, D. L. (2021). Nat. Rev. Microbiol. 19, 409-424. · DOI · Paper page
  34. He, 2023, Nat. Commun., 14, 3217, 10.1038/s41467-023-39031-1 · DOI
  35. Henderson, 1995, Q. Rev. Biophys., 28, 171, 10.1017/S003358350000305X · DOI · Paper page
  36. Hesketh, 2018, Nat. Commun., 9, 2369, 10.1038/s41467-018-04793-6 · DOI
  37. Hochuli, 1988, Nat. Biotechnol., 6, 1321, 10.1038/nbt1188-1321 · DOI · Paper page
  38. Huang, 2020, Acta Pharmacol. Sin., 41, 1141, 10.1038/s41401-020-0485-4 · DOI
  39. Huber, 2022, eLife, 11, e72629, 10.7554/eLife.72629 · DOI
  40. Jain, 2012, J. Struct. Biol., 179, 68, 10.1016/j.jsb.2012.04.020 · DOI
  41. Juers, 2000, Protein Sci., 9, 1685, 10.1110/ps.9.9.1685 · DOI
  42. Juers, 2012, Protein Sci., 21, 1792, 10.1002/pro.2165 · DOI
  43. Jurrus, 2018, Protein Sci., 27, 112, 10.1002/pro.3280 · DOI
  44. Kampjut, 2021, iScience, 24, 102139, 10.1016/j.isci.2021.102139 · DOI
  45. Ko, 2000, Acta Cryst. D, 56, 241, 10.1107/S0907444999015930 · DOI
  46. Li, 2021, J. Struct. Biol., 213, 107783, 10.1016/j.jsb.2021.107783 · DOI
  47. Liebschner, 2019, Acta Cryst. D, 75, 861, 10.1107/S2059798319011471 · DOI · Paper page
  48. Liu, 2023, J. Mol. Biol., 435, 167926, 10.1016/j.jmb.2022.167926 · DOI
  49. Lu, 2022, Nat. Commun., 13, 6718, 10.1038/s41467-022-34579-w · DOI
  50. Lyumkis, 2019, J. Biol. Chem., 294, 5181, 10.1074/jbc.REV118.005602 · DOI
  51. Martins-Costa, 2023, J. Am. Chem. Soc., 145, 1400, 10.1021/jacs.2c12089 · DOI
  52. Merchant, 1998, Nat. Biotechnol., 16, 677, 10.1038/nbt0798-677 · DOI
  53. Murshudov, 2011, Acta Cryst. D, 67, 355, 10.1107/S0907444911001314 · DOI
  54. Naydenova, 2017, Nat. Commun., 8, 629, 10.1038/s41467-017-00782-3 · DOI
  55. Nguyen, 2020, J. Oleo Sci., 69, 519, 10.5650/jos.ess20024 · DOI
  56. Noble, 2018, eLife, 7, e34257, 10.7554/eLife.34257 · DOI
  57. Noble, 2018, Nat. Methods, 15, 793, 10.1038/s41592-018-0139-3 · DOI
  58. Nogales, 2016, Nat. Methods, 13, 24, 10.1038/nmeth.3694 · DOI · Paper page
  59. Noone, 2021, Front. Immunol., 12, 757633, 10.3389/fimmu.2021.757633 · DOI
  60. Okemefuna, 2010, J. Biol. Chem., 285, 1041, 10.1074/jbc.M109.044495 · DOI
  61. Patwardhan, 2017, Acta Cryst. D, 73, 503, 10.1107/S2059798317004181 · DOI
  62. Pettersen, 2004, J. Comput. Chem., 25, 1605, 10.1002/jcc.20084 · DOI · Paper page
  63. Pettersen, 2021, Protein Sci., 30, 70, 10.1002/pro.3943 · DOI
  64. Pintilie, 2020, Nat. Methods, 17, 328, 10.1038/s41592-020-0731-1 · DOI
  65. Quispe, 2007, Microsc. Microanal., 13, 365, 10.1017/S1431927607070791 · DOI
  66. Rabe, 2020, Eur. Biophys. J., 49, 533, 10.1007/s00249-020-01459-4 · DOI
  67. Ramírez-Aportela, 2022, IUCrJ, 9, 632, 10.1107/S2052252522006959 · DOI
  68. Rosenthal, 2003, J. Mol. Biol., 333, 721, 10.1016/j.jmb.2003.07.013 · DOI · Paper page
  69. Russo, 2016, J. Struct. Biol., 193, 33, 10.1016/j.jsb.2015.11.006 · DOI
  70. Samanta, 2011, Chem. Eng. Res. Des., 89, 2344, 10.1016/j.cherd.2011.04.006 · DOI
  71. Sanchez-Garcia, 2021, Commun. Biol., 4, 874, 10.1038/s42003-021-02399-1 · DOI
  72. Sathyanarayanan, 2019, Nat. Commun., 10, 4127, 10.1038/s41467-019-11931-1 · DOI
  73. Schauperl, 2022, J. Chem. Inf. Model., 62, 3142, 10.1021/acs.jcim.2c00026 · DOI · Paper page
  74. Scheres, 2012, J. Struct. Biol., 180, 519, 10.1016/j.jsb.2012.09.006 · DOI · Paper page
  75. Schürmann, 2017, Ultramicroscopy, 182, 10, 10.1016/j.ultramic.2017.06.003 · DOI
  76. Sorzano, 2022, Acta Cryst. D, 78, 410, 10.1107/S2059798322001978 · DOI
  77. Sorzano, 2021, J. Struct. Biol., 213, 107695, 10.1016/j.jsb.2020.107695 · DOI
  78. Szymczyk, 2018, J. Solution Chem., 47, 1824, 10.1007/s10953-018-0823-z · DOI
  79. Tan, 2017, Nat. Methods, 14, 793, 10.1038/nmeth.4347 · DOI
  80. Tang, 2020, Chem. Rev., 120, 3633, 10.1021/acs.chemrev.9b00512 · DOI
  81. Tang, 2007, J. Struct. Biol., 157, 38, 10.1016/j.jsb.2006.05.009 · DOI
  82. Taylor, 1974, Science, 186, 1036, 10.1126/science.186.4168.1036 · DOI
  83. Tobiasson, 2022, Nat. Commun., 13, 6132, 10.1038/s41467-022-33582-5 · DOI
  84. Vinothkumar, 2016, Q. Rev. Biophys., 49, e13, 10.1017/S0033583516000068 · DOI
  85. Vogel, 1986, Nature, 320, 533, 10.1038/320533a0 · DOI
  86. Wei, 2018, J. Struct. Biol., 202, 170, 10.1016/j.jsb.2018.01.001 · DOI
  87. Wrapp, 2020, Science, 367, 1260, 10.1126/science.abb2507 · DOI · Paper page
  88. Wrobel, 2023, Curr. Opin. Struct. Biol., 81, 102619, 10.1016/j.sbi.2023.102619 · DOI
  89. Xu, 2021, SmartMat, 2, 202, 10.1002/smm2.1045 · DOI
  90. Yamashita, 2021, Acta Cryst. D, 77, 1282, 10.1107/S2059798321009475 · DOI
  91. Zhang, 2016, J. Struct. Biol., 193, 1, 10.1016/j.jsb.2015.11.003 · DOI
  92. Zheng, 2023, Nat. Methods, 20, 123, 10.1038/s41592-022-01693-y · DOI
  93. Zhong, 2019, Annu. Rev. Phys. Chem., 70, 45, 10.1146/annurev-physchem-042018-052311 · DOI
  94. Zivanov, 2018, eLife, 7, e42166, 10.7554/eLife.42166 · DOI · Paper page
  95. Zivanov, 2019, IUCrJ, 6, 5, 10.1107/S205225251801463X · DOI

Metadata

Authors
Yadav, S., & Vinothkumar, K. R.
Affiliations
Tata Institute of Fundamental Research (IN)
ORCID
Venue
Acta Crystallographica Section D Structural Biology
Publisher
International Union of Crystallography (IUCr)
Published
2024-06-27
Volume
80
Issue
7
Pages
535-550
ISSN
2059-7983 (ISSN-L)
DOI
10.1107/s2059798324005229
PMC
PMC11220838
OpenAlex
W4400103674
Cited by
7
References
2
Citations by year
2026: 5 · 2025: 2
FWCI
1.28
Type
journal article
Language
en
Open access
Licence
Locations
  • Acta Crystallographica Section D Structural Biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Department of Biotechnology, Ministry of Science and Technology, India (DBT/PR12422/MED/31/287/2014)
  • Department of Atomic Energy, Government of India (RTI4006)
  • National Centre for Biological Sciences
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Advanced Electron Microscopy Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Keywords
crystallographic texture, orientation bias, air-water interface, protein adsorption, sample preparation, 3D reconstruction, vitrification
MeSH terms
SARS-CoV-2, Escherichia coli, Humans, Models, Molecular, Proteins, Surface-Active Agents, Temperature, Protein Structure, Tertiary, Cryoelectron Microscopy, Protein Structure, Quaternary

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.