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Errors in structural biology are not the exception.

Yunyun Gao1, Volker Thorn2, Andrea Thorn1

  • 1Insitut für Nanostruktur und Festkörperphysik, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany.

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Summary
This summary is machine-generated.

Structural biology research quickly addressed COVID-19 questions, but errors in macromolecular structures persist in the Protein Data Bank. Improving error detection and fostering an error-aware culture are crucial for reliable scientific interpretation.

Keywords:
errorsmodellingquality indicatorsstructural biologyvalidation

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Area of Science:

  • Structural biology
  • Macromolecular structure determination
  • Protein Data Bank (PDB)

Background:

  • The structural biology community rapidly determined macromolecular structures during the COVID-19 pandemic to address urgent research questions.
  • The Coronavirus Structural Task Force reviewed SARS-CoV-1 and SARS-CoV-2 structures.
  • Errors in measurement, data processing, and modeling are prevalent in deposited macromolecular structures.

Purpose of the Study:

  • To highlight the presence of errors in macromolecular structures within the Protein Data Bank.
  • To advocate for a change in error culture within the structural biology community.
  • To emphasize the need for early issue detection and root cause analysis to minimize the impact of errors.

Main Methods:

  • Evaluation of structures by the Coronavirus Structural Task Force.
  • Analysis of error types including measurement, data processing, and modeling.
  • Discussion on the interpretation of atomic models as representations of experimental data.

Main Results:

  • Errors are not limited to SARS-CoV structures but are widespread throughout the Protein Data Bank.
  • Identifying errors is the initial step; a cultural shift is necessary to mitigate their impact.
  • Published atomic models represent an interpretation of experimental measurements.

Conclusions:

  • A proactive error-aware culture is essential for the integrity of structural biology.
  • Minimizing risks involves early identification and investigation of error sources.
  • Improvements will benefit both experimental structural biologists and researchers utilizing structural models for biological and medical insights.