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VH-NG-19-02
Working with RoPE: Representation of Protein Entities
| Coordinator | Ginn, Helen |
| Grant period | 2023-02-01 - |
| Funding body | Helmholtz Gemeinschaft Deutscher Forschungszentren |
| HGF | |
| Identifier | G:(DE-HGF)2023_IVF-VH-NG-19-02 |
⇧ Impuls- und Vernetzungsfonds ⇧
Note: Proteins are the workhorses of biology. Some of these drive chemical reactions; many interact with other proteins to communicate changes of priority in cellular activity. Fundamental to their operation is their flexibility and adoption of subtly different structures (conformations). Structural biology strives to understand how biological mechanisms are driven on a molecular level, to deliver clinical therapies and biotechnological breakthroughs. However, the ambition of structural biology is rapidly outpacing the scope of existing software for interpreting data, as we become more experimentally competent and delve deeper into the processes underpinning biology. Although current research questions often involve multiple datasets, our computational methods still treat them as isolated sources of information. We therefore lose subtle shifts between biological states, often crucial to changes in protein activity. This limits us, not only in the specific research question, but also in the fundamental understanding of protein function. We propose a concept for unifying all observations of a protein under one conformational space, called Representation of Protein Entities (RoPE). This will parametrise the subtleties to reveal exactly what we need to know: how and in what directions proteins flex, and how these conformational states relate to function.All known publications ...
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Journal Article
Robust and automatic beamstop shadow outlier rejection: combining crystallographic statistics with modern clustering under a semi-supervised learning strategy
Acta crystallographica / Section D 80(10), 722-732 (2024) [10.1107/S2059798324008519]
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Journal Article
An expanded trove of fragment-bound structures for the allosteric enzyme PTP1B from computational reanalysis of large-scale crystallographic data
Structure 32(8), 1231-1238.e4 (2024) [10.1016/j.str.2024.05.010]
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