Cited by 9Advanced Electron Microscopy Techniques and ApplicationsEnzyme Structure and FunctionProtein Structure and Dynamics

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Direct calculation of cryo-EM and crystallographic model maps for real-space refinement

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Urzhumtsev, Alexandre G., Urzhumtseva, Ludmila M., Lunin, Vladimir Y.·2022·Acta Crystallographica Section D Structural Biology

Published version of a preprint

Abstract

This work addresses the problem of the calculation of limited-resolution maps from an atomic model in cryo-electron microscopy and in X-ray and neutron crystallography, including cases where the resolution varies from one molecular region to another. Such maps are necessary in real-space refinement for comparison with the experimental maps. For an appropriate numeric comparison, the calculated maps should reproduce not only the structural features contained in the experimental maps but also the principal map distortions. These model maps can be obtained with no use of Fourier transforms but, similar to density distributions, as a sum of individual atomic contributions. Such contributions, referred to as atomic density images, are atomic densities morphed to reflect distortions of the experimental map, in particular the loss of resolution. They are described by functions composed of a central peak surrounded by Fourier ripples. For practical calculations, atomic images should be cut at some distance. It is shown that to reach a reasonable accuracy such a distance should be significantly larger than the distance customarily applied when calculating density distributions. This is a consequence of the slow rate with which the amplitude of the Fourier ripples decreases. Such a large distance means that at least a few ripples should be included in calculations in order to obtain a map that is sufficiently accurate. Oscillating functions describing these atomic contributions depend, for a given atomic type, on the resolution and on the atomic displacement parameter values. To express both the central peak and the Fourier ripples of the atomic images, these functions are represented by the sums of especially designed terms, each concentrated in a spherical shell and depending analytically on the atomic parameters. In this work, the strength of the dependence of the accuracy of resulting map on the accuracy of the atomic displacement parameters and on the truncation distance, i.e. the number of ripples included in atomic density images, is analyzed. This analysis is completed by practical aspects of the calculation of maps of inhomogeneous resolution. Tests show that the calculation of limited-resolution maps from an atomic model as a sum of atomic contributions requires a large truncation radius extending beyond the central peak of an atomic image and the first Fourier ripples. The article discusses the practical details of such calculations expressing atomic contributions as analytic functions of the atomic coordinates, the atomic displacement parameters and the local resolution.

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Cites

Research works printed but not linked: 56

  1. Afonine, 2007, Acta Cryst. D, 63, 1194, 10.1107/S0907444907046148 · DOI
  2. Afonine, 2018, Acta Cryst. D, 74, 814, 10.1107/S2059798318009324 · DOI
  3. Afonine, 2018, Acta Cryst. D, 74, 531, 10.1107/S2059798318006551 · DOI
  4. Afonine, 2004, Acta Cryst. A, 60, 19, 10.1107/S0108767303022062 · DOI
  5. Afonine, 2012, Comput. Crystallogr. Newsl., 3, 43
  6. Agarwal, 1978, Acta Cryst. A, 34, 791, 10.1107/S0567739478001618 · DOI
  7. Baek, 2021, Science, 373, 871, 10.1126/science.abj8754 · DOI · Paper page
  8. Brown, 2015, Acta Cryst. D, 71, 136, 10.1107/S1399004714021683 · DOI
  9. Brown, P. J., Fox, A. G., Maslen, E. N., O'Keefe, M. A. & Willis, B. T. M. (2006). International Tables for X-ray Crystallography, Vol. C, edited by E. Prince, pp. 554-595. Dordrecht: Springer. · DOI
  10. Cardone, 2013, J. Struct. Biol., 184, 226, 10.1016/j.jsb.2013.08.002 · DOI
  11. Chapman, 1995, Acta Cryst. A, 51, 69, 10.1107/S0108767394007130 · DOI
  12. Chapman, 2013, J. Struct. Biol., 182, 10, 10.1016/j.jsb.2013.01.003 · DOI
  13. Cochran, 1948, Acta Cryst., 1, 138, 10.1107/S0365110X48000375 · DOI
  14. DiMaio, 2015, Nat. Methods, 12, 361, 10.1038/nmeth.3286 · DOI
  15. Doyle, 1968, Acta Cryst. A, 24, 390, 10.1107/S0567739468000756 · DOI
  16. Emsley, 2004, Acta Cryst. D, 60, 2126, 10.1107/S0907444904019158 · DOI · Paper page
  17. Fox, 1989, Acta Cryst. A, 45, 786, 10.1107/S0108767389007567 · DOI
  18. Grosse-Kunstleve, 2004, IUCr Comm. Crystallogr. Comput. Newsl., 3, 22
  19. Harker, 1948, Acta Cryst., 1, 70, 10.1107/S0365110X4800020X · DOI
  20. Iudin, 2016, Nat. Methods, 13, 387, 10.1038/nmeth.3806 · DOI
  21. Jakobi, 2017, eLife, 6, e27131, 10.7554/eLife.27131 · DOI
  22. Kostrewa, 1995, Jnt CCP4/ESF-EACBM Newsl. Protein Crystallogr., 34, 9
  23. Kucukelbir, 2014, Nat. Methods, 11, 63, 10.1038/nmeth.2727 · DOI
  24. Lawson, 2016, Nucleic Acids Res., 44, D396, 10.1093/nar/gkv1126 · DOI
  25. Lehmann, 2006, Biochemistry, 45, 11, 10.1021/bi051502y · DOI
  26. Liebschner, 2019, Acta Cryst. D, 75, 861, 10.1107/S2059798319011471 · DOI · Paper page
  27. Lunin, 1988, Acta Cryst. A, 44, 144, 10.1107/S0108767387009784 · DOI
  28. Lunin, 2002, Acta Cryst. A, 58, 270, 10.1107/S0108767302001046 · DOI
  29. Lunin, 1984, Acta Cryst. A, 40, 269, 10.1107/S0108767384000544 · DOI
  30. Lunin, 1985, Acta Cryst. A, 41, 327, 10.1107/S010876738500071X · DOI
  31. Marques, 2019, Curr. Opin. Struct. Biol., 58, 214, 10.1016/j.sbi.2019.04.006 · DOI
  32. Mooij, 2006, ChemMedChem, 1, 827, 10.1002/cmdc.200600074 · DOI
  33. Navaza, 2002, Acta Cryst. A, 58, 568, 10.1107/S0108767302016318 · DOI
  34. Navaza, 2002, Acta Cryst. D, 58, 1820, 10.1107/S0907444902013707 · DOI
  35. Nicholls, 2018, Acta Cryst. D, 74, 492, 10.1107/S2059798318007313 · DOI
  36. Peng, 1999, Micron, 30, 625, 10.1016/S0968-4328(99)00033-5 · DOI
  37. Pintilie, 2020, Nat. Methods, 17, 328, 10.1038/s41592-020-0731-1 · DOI
  38. Ramírez-Aportela, 2019, IUCrJ, 6, 1054, 10.1107/S2052252519011692 · DOI
  39. Rossmann, 2000, Acta Cryst. D, 56, 1341, 10.1107/S0907444900009562 · DOI
  40. Rossmann, 2001, J. Struct. Biol., 136, 190, 10.1006/jsbi.2002.4435 · DOI
  41. Rupp, B. (2009). Biomolecular Crystallography. Principles, Practice, and Applications to Structural Biology, p. 453. New York: Garland Science. · DOI
  42. Sayre, 1951, Acta Cryst., 4, 362, 10.1107/S0365110X51001124 · DOI
  43. Simonetti, 2013, Acta Cryst. D, 69, 925, 10.1107/S0907444913006422 · DOI
  44. Sorzano, 2015, AIMS Biophys., 2, 8, 10.3934/biophy.2015.1.8 · DOI
  45. Ten Eyck, 1977, Acta Cryst. A, 33, 486, 10.1107/S0567739477001211 · DOI
  46. Tickle, 2012, Acta Cryst. D, 68, 454, 10.1107/S0907444911035918 · DOI
  47. Urzhumtsev, 2014, Acta Cryst. D, 70, 2593, 10.1107/S1399004714016289 · DOI
  48. Urzhumtsev, 2022, IUCrJ, 9, 728, 10.1107/S2052252522008260 · DOI
  49. Urzhumtsev, 2022, Int. J. Mol. Sci., 23, 12101, 10.3390/ijms232012101 · DOI
  50. Urzhumtsev, 2001, Acta Cryst. A, 57, 451, 10.1107/S0108767301003397 · DOI
  51. Urzhumtsev, 2019, Crystallogr. Rev., 25, 164, 10.1080/0889311X.2019.1631817 · DOI
  52. Urzhumtsev, 1989, Acta Cryst. A, 45, 34, 10.1107/S0108767388008955 · DOI
  53. Urzhumtseva, 2013, Acta Cryst. D, 69, 1921, 10.1107/S0907444913016673 · DOI
  54. Urzhumtseva, L., Lunin, V. Y. & Urzhumtsev, A. (2022). arXiv:2206.08935. · arXiv
  55. Vilas, 2018, Structure, 26, 337, 10.1016/j.str.2017.12.018 · DOI
  56. Waasmaier, 1995, Acta Cryst. A, 51, 416, 10.1107/S0108767394013292 · DOI

Metadata

Authors
Urzhumtsev, A. G., Urzhumtseva, L. M., & Lunin, V. Y.
Affiliations
  • Centre National de la Recherche Scientifique (FR)
  • Institute of Mathematical Problems of Biology (RU)
Corresponding author
Urzhumtsev, Alexandre G.
Venue
Acta Crystallographica Section D Structural Biology
Published
2022-11-25
Volume
78
Issue
12
Pages
1451-1468
ISSN
2059-7983 (ISSN-L)
OpenAlex
W4310054998
Cited by
9
References
4
Citations by year
2026: 1 · 2025: 3 · 2023: 3 · 2022: 2
FWCI
0.99
Type
journal article
Language
en
Open access
Locations
  • Acta Crystallographica Section D Structural Biology (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • PubMed (publishedVersion)
  • HAL (submittedVersion)
Funders
French Infrastructure for Integrated Structural Biology (ANR-10-INBS-05)
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
real-space refinement, atomic displacement parameters, cryo-electron microscopy, X-ray crystallography, neutron crystallography, map distortion
MeSH terms
Crystallography, Neutrons, Cryoelectron Microscopy

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