Decision-making in serial crystallography: a simple test to quickly determine whether sufficient data have been...

Area of Science:

• Structural Biology
• Crystallography
• Biophysics

Background:

• Standard rotational crystallography has established data quality metrics.
• Serial crystallography presents challenges in quickly assessing data sufficiency.
• Incomplete datasets can yield misleading, low-signal electron-density maps.

Purpose of the Study:

• To develop a reliable method for assessing data adequacy in serial crystallography.
• To implement this method within an automated data processing pipeline.
• To guide experimental decisions regarding data collection.

Main Methods:

• Established a novel electron-density-based test.
• Implemented the perturbed model real-space difference density (PMRDD) test.
• Integrated the test into the autoprocessing pipeline at the T-REXX endstation, beamline P14, PETRA III.

Main Results:

• The PMRDD test provides a robust assessment of data completeness and signal quality.
• This method helps differentiate between datasets with genuine experimental signal and those dominated by phasing models.
• The test effectively guides decisions on whether to collect more data or proceed with analysis.

Conclusions:

• The PMRDD test is a valuable tool for optimizing data collection strategies in serial crystallography.
• It ensures the collection of high-quality data, leading to more accurate structural determination.
• This method enhances the efficiency and reliability of serial crystallography experiments.