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Atomic model validation using the CCP-EM software suite

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Author(s)

  • Agnel Praveen Joseph
  • Mateusz Olek
  • Sony Malhotra
  • Peijun Zhang
  • Kevin Cowtan
  • Tom Burnley
  • Martyn D. Winn

Department/unit(s)

Publication details

JournalActa Crystallographica Section D: Structural Biology
DateAccepted/In press - 1 Dec 2021
DatePublished (current) - 1 Feb 2022
Volume78
Number of pages10
Pages (from-to)152-161
Original languageEnglish

Abstract

Recently, there has been a dramatic improvement in the quality and quantity of data derived using cryogenic electron microscopy (cryo-EM). This is also associated with a large increase in the number of atomic models built. Although the best resolutions that are achievable are improving, often the local resolution is variable, and a significant majority of data are still resolved at resolutions worse than 3 Å. Model building and refinement is often challenging at these resolutions, and hence atomic model validation becomes even more crucial to identify less reliable regions of the model. Here, a graphical user interface for atomic model validation, implemented in the CCP-EM software suite, is presented. It is aimed to develop this into a platform where users can access multiple complementary validation metrics that work across a range of resolutions and obtain a summary of evaluations. Based on the validation estimates from atomic models associated with cryo-EM structures from SARS-CoV-2, it was observed that models typically favor adopting the most common conformations over fitting the observations when compared with the model agreement with data. At low resolutions, the stereochemical quality may be favored over data fit, but care should be taken to ensure that the model agrees with the data in terms of resolvable features. It is demonstrated that further re-refinement can lead to improvement of the agreement with data without the loss of geometric quality. This also highlights the need for improved resolution-dependent weight optimization in model refinement and an effective test for overfitting that would help to guide the refinement process.

Bibliographical note

Funding Information:
This work was supported by the Wellcome Trust (research grants 208398/Z/17/Z and 206422/Z/17/Z), MRC Partnership grants (MR/N009614/1 and MR/V000403/1), a BBSRC grant (BB/T012935/1) and a PhD studentship from the University of York and Diamond (eBIC).

Publisher Copyright:
© 2022.

    Research areas

  • CCP-EM, Cryo-EM, Model geometry, Model validation, SARS-CoV-2

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