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Robust indexing & automatic data collection at the Advanced Light Source

Abstract

Structural genomics programs and drug discovery efforts that investigate large sets of crystalline samples are placing increased demands on synchrotron beamlines. To facilitate high-throughput work, beamlines 5.0.1, 5.0.2, and 5.0.3 at the ALS have been equipped with robotic arms [Structure (2004) 12:537-545] to transfer cryocooled samples to the goniometer. High-level graphical controls allow the user to conduct experiments with minimal input, while much of the work is performed by underlying software modules. The AutoScreen module rapidly evaluates 96 samples, centering each cryoloop on the beam position by analyzing videomicrographs. Two diffraction snapshots are acquired for each crystal, and then the Lawrence Berkeley Indexing Toolbox (LABELIT) autoindexes the diffraction pattern and determines the Bravais symmetry. LABELIT implements new methods to treat three common failure modes experienced during indexing: 1) non-primitive basis, 2) incorrect beam center, and 3) faulty symmetry. Correcting these problems allows images to be indexed rapidly without the need for interactive visual inspection. An AutoCollect module is now under development to deduce and set the optimal data collection parameters, while an AutoProcess module will reduce the diffraction data in real time and determine the space group. We anticipate that these tools will increase experimental efficiency for both individual users and large-scale efforts alike.

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