Protein structure models obtained from X-ray crystallography are subject to radiation damage. The resulting specific alterations to protein structures can be mistaken for biological features, or may obscure actual protein mechanisms, leading to misidentification or obscuration of biological insight. The radiation chemistry behind this site-specific damage is not well understood. Radiation damage processes progress in proportion to the dose absorbed by the crystal in the diffraction experiment. Doses can be estimated using existing software, but these assume idealised experimental conditions. To simulate complex diffraction experiments, including treatment of imperfect X-ray beam profiles and inhomogeneous dose distributions, a new program, RADDOSE-3D, was developed. RADDOSE-3D can be integrated into beamline software to provide convenient, more accurate, comparative, and publishable dose figures, also facilitating informed data collection decisions. There is currently no method to automatically detect specific radiation damage in protein structure models in the absence of an 'undamaged' reference model. Radiation damage research therefore generally relies on detailed observation of a few model proteins. A new metric, B<sub>Damage</sub>, is designed and used to identify and quantify specific radiation damage in the first large-scale statistical survey of 2,704 published protein models, which are examined for the effects of local environments on site-specific radiation damage susceptibility. A significant positive correlation between susceptibility and solvent accessibility is identified. Current understanding of radiation damage progression is mostly based on a few consecutive structure model 'snapshots' at coarse dose intervals. The low sampling rate considerably limits the ability to identify varying site susceptibility and its causes. Real space electron density data are obtained for crystals of different mutants of a RhoGDI protein with very high sequence identity, to determine sensitising and stabilising factors for radiation induced structural changes. Utilising a newly developed data collection and analysis protocol, these changes could be tracked with unprecedented time resolution.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:655029 |
| Date | January 2014 |
| Creators | Gerstel, Markus |
| Contributors | Garman, Elspeth F.; Deane, Charlotte M. |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:be55baee-19b7-4a34-8694-fb9c3606a19c |
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