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AUTOMATION OF MACROMOLECULAR DATA COLLECTION - INTEGRATION OF DATA COLLECTION AND DATA PROCESSING

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AUTOMATION OF MACROMOLECULAR DATA COLLECTION - INTEGRATION OF DATA COLLECTION AND DATA PROCESSING

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  1. The primary objective of the DNA project is the provision of software that will allow fully automated collection and processing of diffraction data, including rapid crystal screening. Ultimately the project will be extended to include automated sample loading and a project management system, which will enable a large number of crystals from a number of different projects to be handled without any manual intervention. Three modules (data processing, beamline control and sample control) are linked together to provide a complete system for controlling data collection and processing. Communication between the three modules is handled by an expert system; this makes the crucial decisions about the data collection based on information provided by the data processing module and some basic parameters relating to the project supplied by the user. Direct communication between the Expert system and the different modules is through a server program which uses TCP/IP sockets and a command language conforming to XML standards. The server program has been developed to provide an extendable interface to a “next-generation” GUI for Mosflm. The modular nature of this system simplifies installation on different beamlines, while the open source communications protocol will allow the straightforward integration of other software into the system. beamline software to collect the required images, and the data processing software to process the images as they are collected. Automation of the data processing steps is possible because of improvements to Mosflm itself, which allow the appropriate sequence of operations to be carried out in a flexible and robust manner. Commands which were previously only available from the GUI are now accessible on the command line. All the features listed in the flowchart exist in Mosflm version 6.2.0. Key to division of labour start Expert system collect two images at 0º and 90º autoindex Mosflm estimate mosaicity CCP4 Phase I/II integrate single image determine effective resolution limit determine data collection strategy collect images for postrefinement Postrefine cell parameters collect next image in dataset Sample control module integrate image database Expert System Beamline control module Merge/Scale data Disk storage Data processing module data collection finished? y finish (okay) n Determine strategy for new point group • At present the system has been implemented as an additional button on the data collection GUIs (PXGEN++ at SRS, ProDC at ESRF) which gives a "characterize crystal" command. • The "characterize crystal" command issues instructions to • collect two images from a crystal (at 0º and 90º in phi) • autoindex each image individually and also both together • estimate the effective mosaicity • integrate the first image to determine the effective resolution limit • calculate a suitable data collection strategy to give maximum completeness for both unique and anomalous data. n crystal still okay? finish (error) y n point group changed? point group consistent? Merge/Scale data y y select next highest symmetry point group n Procedures involved in fully automated data collection and processing Implementation The project is divided into five phases and is intended to provide useful added functionality at all stages. Phase I and II functionality will be available at the ESRF (beamlines ID14 EH2, EH1) and SRS (beamline 14.2) in the next few months. Phase I. In this phase, the Expert System will simply provide a communication pathway between the data processing software and the beamline control software. Phase II. The parameters of the data collection will be presented to the user in a GUI where they can be edited. Phase III. An additional button will allow the user to integrate the images as they are collected. Information about the results of the integration (eg <I/s(I)> as a function of resolution or image) will be fed back to the GUI from the data processing. Results of merging the data will also be displayed. Phase IV. Implementation of fully automated data collection and processing. A single button will activate initial characterisation of the crystal, and providing that user-defined criteria regarding resolution, mosaicity etc. are met, the data will be collected and integrated without any user intervention. Phase V. Automated sample loading (including crystal centring in the beam) and a project management system will be integrated with the Expert System. This will allow rank ordering of multiple crystals based on their diffraction properties, and fully automated beamline operation. PXGEN++ (left) and ProDC (above) GUIs before and after characterizing crystal The success or failure of the autoindexing of one or more test images is used as the initial indicator of crystal quality. This will be judged by the rms error in predicted spot positions and the fraction of spots that are rejected from indexing or refinement. If the autoindexing is successful, the crystal mosaicity will be estimated and the test images will be integrated to obtain an indication of data quality and the effective resolution, deduced from the <I/s(I)> values as a function of resolution. A data collection strategy based on the deduced Laue group (with the lowest possible symmetry) will also be calculated. The Expert System uses this information to determine if the crystal is really suitable for data collection (for example, if the required resolution can be achieved) and to determine data collection parameters. It then instructs the Harold R. Powell1, Graeme Winter1, Andrew G.W. Leslie1, Colin Nave2, Elizabeth Duke2, Stephen H. Kinder2, Dave Love2, Sean McSweeney3, Olof Svensson3, Darren Spruce3, Solange Delageniere3 (1) MRC-LMB, Hills Road, Cambridge, UK (2) Daresbury Laboratory, Daresbury, Warrington, UK (3) ESRF, BP 220, F-38043, Grenoble Cedex, France AUTOMATION OF MACROMOLECULAR DATA COLLECTION - INTEGRATION OF DATA COLLECTION AND DATA PROCESSING In view of the limited availability of beamtime at synchrotron sources and the large number of projects requiring this resource, automation of both data collection and data processing has become increasingly important. Improvements in area detector technology (e.g. the introduction of fast readout devices such as CCDs) also emphasize the fact that human intervention at this stage and that of subsequent data processing is responsible for decreasing the possible levels of throughput attainable. With this in mind we have made considerable progress in integrating data collection and processing and in automating each of these two components. This work has been funded by CCP4 and the EU via the Autostruct initiative and the Max-Inf network. DNA stands for DNA’s Not Autostruct. For further information, visit http://www.dna.ac.uk

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