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In protein crystallography the ultimate goal is to determine the 3D structure of a protein of interest to potentially study its working mechanism and to identify reasons why it may be malfunctioning. To determine the structure, a crystal of a protein of interest is exposed to X-rays and its diffraction recorded on a 2D photon counting detector as intensities. In the following data reduction step these insities are assigned some indices according to their location in reciprocal space and multiple observations of the same reflection are combined to a single intensity with an error flag attached to it.
During this step a fair judgment of the data quality is attempted. However, the intensities on their own are not sufficient to determine a protein structure. Due to the way the diffraction data has been obtained, the phase information of the diffracted X-rays has been lost. These phases are the more important component in the structure solution process and are usually "borrowed" from a related protein structure in a process called molecular replacement or are determined experimentally by way of introducing heavy atoms to crystals of the same protein and compare their diffraction to the one of untreated crystals.
This project will be based on an already existing SQLite database which currently stores general information from automated data processing and phasing pipelines. This information needs to be expanded to accommodate more details from the phasing step including images taken of electron density maps of different phasing solutions. The aim is to find a machine learning algorithm suitable to automatically classify "good" and "bad" electron density maps from initial phases as a potential user tool to increase the chances of solving a protein structure This placement represents preliminary work, proof-of-principle, for a joint project between Diamond and CCP4, where the former provides the data and the latter is a group of software developers providing a suite of programs for the protein crystallography community.
Suitable Subjects: Physics, Chemistry, Mathematics, Computing, Other Statistics
Project duration: 12 weeks
TO APPLY PLEASE FOLLOW THE LINK BELOW
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