Robust error calibration for serial crystallography

Serial crystallography is an important technique with unique abilities to resolve enzymatic transition states, minimize radiation damage to sensitive metalloenzymes and perform de novo structure determination from micrometre-sized crystals. This technique requires the merging of data from thousands of crystals, making manual identification of errant crystals unfeasible. cctbx.xfel.merge uses filtering to remove problematic data. However, this process is imperfect, and data reduction must be robust to outliers. We add robustness to cctbx.xfel.merge at the step of uncertainty determination for reflection intensities. This step is a critical point for robustness because it is the first step where the data sets are considered as a whole, as opposed to individual lattices. Robustness is conferred by reformulating the error-calibration procedure to have fewer and less stringent statistical assumptions and incorporating the ability to down-weight low-quality lattices. We then apply this method to five macromolecular XFEL data sets and observe the improvements to each. The appropriateness of the intensity uncertainties is demonstrated through internal consistency. This is performed through theoretical CC<sub>1/2</sub> and I/σ relationships and by weighted second moments, which use Wilson's prior to connect intensity uncertainties with their expected distribution. This work presents new mathematical tools to analyze intensity statistics and demonstrates their effectiveness through the often underappreciated process of uncertainty analysis.

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Publication Details

Journal
Acta Crystallographica Section D Structural Biology
Published
2025-04-29
DOI
https://doi.org/10.1107/s2059798325002852
Citations
1
Primary Topic
Enzyme Structure and Function
Type
article
Field-Weighted Citation Impact
0.52

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article

Robust error calibration for serial crystallography

Aaron S. Brewster, Jan F Kern, Vanessa Oklejas, Romie C. Nguyen et al.
1 citations
Acta Crystallographica Section D Structural Biology
Enzyme Structure and Function
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article

Robust error calibration for serial crystallography

Aaron S. Brewster, Jan F Kern, Vanessa Oklejas, Romie C. Nguyen, Aimin Liu, David Moreau, Nicholas K. Sauter, Asmit Bhowmick, Daniel W. Paley⧓
article en
1 citations

Abstract

Serial crystallography is an important technique with unique abilities to resolve enzymatic transition states, minimize radiation damage to sensitive metalloenzymes and perform de novo structure determination from micrometre-sized crystals. This technique requires the merging of data from thousands of crystals, making manual identification of errant crystals unfeasible. cctbx.xfel.merge uses filtering to remove problematic data. However, this process is imperfect, and data reduction must be robust to outliers. We add robustness to cctbx.xfel.merge at the step of uncertainty determination for reflection intensities. This step is a critical point for robustness because it is the first step where the data sets are considered as a whole, as opposed to individual lattices. Robustness is conferred by reformulating the error-calibration procedure to have fewer and less stringent statistical assumptions and incorporating the ability to down-weight low-quality lattices. We then apply this method to five macromolecular XFEL data sets and observe the improvements to each. The appropriateness of the intensity uncertainties is demonstrated through internal consistency. This is performed through theoretical CC<sub>1/2</sub> and I/σ relationships and by weighted second moments, which use Wilson's prior to connect intensity uncertainties with their expected distribution. This work presents new mathematical tools to analyze intensity statistics and demonstrates their effectiveness through the often underappreciated process of uncertainty analysis.

Acta Crystallographica Section D Structural BiologyVol. 81(5)
Lawrence Berkeley National Laboratory (US), The University of Texas at San Antonio (US)
U.S. Department of Energy, National Institutes of Health
Openalex Percentile: Top 39%
Enzyme Structure and Function
0.52
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