Challenge data set for macromolecular multi-microcrystallography.

Area of Science:

• Crystallography
• Materials Science
• Data Science

Background:

• Indexing ambiguity poses a significant challenge in crystallographic structure solution, particularly with radiation-damaged samples.
• Current single-crystal methods may be insufficient for complex or damaged datasets.

Purpose of the Study:

• To generate a synthetic dataset that specifically demonstrates challenging indexing ambiguity in the context of radiation damage.
• To establish a standard benchmark for evaluating new methods in robust structure solution.

Main Methods:

• Generation of a synthetic dataset comprising 100 short wedges of crystallographic data.
• Demonstration of structure solution using a 'cheating' method with a known reference structure (first 36 wedges).

Main Results:

• The synthetic dataset effectively highlights indexing ambiguity issues relevant to radiation damage.
• A subset of the data (36 wedges) is sufficient for structure solution when a reference is available.

Conclusions:

• The developed synthetic dataset serves as a crucial benchmark for advancing structure solution methodologies.
• Proposed metrics (wall-clock time, crystal count) can assess the efficiency of multi-crystal automation pipelines for challenging datasets.