AutoLEI: An XDS-based pipeline with graphical user interface for automated real-time and offline batch 3D ED/microED...

Area of Science:

• Crystallography
• Materials Science
• Structural Biology

Background:

• Three-dimensional electron diffraction (3D ED), or microcrystal electron diffraction (microED), is a powerful technique for analyzing submicron-sized crystals.
• Rapid data collection in 3D ED/microED now allows for dozens of datasets to be acquired in a single session.
• Efficient processing of numerous datasets is crucial for accelerating structure determination.

Purpose of the Study:

• To develop a fast and automated workflow for processing, scaling, and merging large numbers of 3D ED/microED datasets.
• To present AutoLEI, an XDS-based pipeline with a graphical user interface for automated batch data processing.
• To demonstrate the pipeline's functionality and versatility across various sample types and data processing modes (real-time and offline).

Main Methods:

• Development of an XDS-based computational pipeline named AutoLEI.
• Implementation of a graphical user interface for user-friendly operation.
• Testing and validation using diverse datasets including small organic molecules, metal-organic frameworks (MOFs), and proteins.

Main Results:

• AutoLEI enables automated, real-time, and offline batch processing of 3D ED/microED data.
• The pipeline successfully processed datasets from various materials, demonstrating its broad applicability.
• Functionality was showcased through four distinct examples, highlighting efficiency and versatility.

Conclusions:

• AutoLEI significantly accelerates the structure determination process by automating data handling.
• The pipeline is a versatile tool applicable to a wide range of samples in 3D ED/microED studies.
• The developed workflow enhances the efficiency of structural analysis using microcrystal electron diffraction.