Overcoming the limitations of high-resolution structural biology
For over 50 years, X-ray crystallography has been the primary method to determine the structures of biological macromolecules, thus defining modern molecular biology. Even with over 100 000 known structures, countless improvements, such as new phasing methods , solvent models  and investments such as the 3.4 km long European X-Ray Free Electron Laser (EuXFEL) in Hamburg , it still has limitations: Some biological questions – for example whether a certain ligand is bound – cannot be answered, as the electron density map gives no clear indication; some structures, such as membrane proteins and large complexes cannot be solved; and worst of all, published and seemingly correct structure solutions can have integral flaws that might even bring about complete retraction of a structure and the associated publications. The problem is aggravated as downstream applications, such as biophysical calculations, molecular dynamics and target-based drug design, depend on crystallographic models as a basis.
There is a fundamental problem underlining all of these problems: the large discrepancy between the measured X-ray diffraction data and the molecular models we employ to interpret these data. This discrepancy is typically measured as a percentage called the R (or residual) value. While small molecule structures routinely reach R-values of 5%, macromolecular structures typically are at 20%-25% . What causes this gap?
In this talk, I will describe our search for an answer to this question, which led to the development of new data quality diagnostics for XFEL and other diffraction data (AUSPEX, http://www.auspex.de<http://www.auspex.de> ), to better background estimation during data integration from detector images , and finally to the realization that something might be fundamentally missing from the atomic models we employ to interpret diffraction data.
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Sprecherin: Dr. Andrea Thorn, Universität Würzburg
Kontakt: Prof. N. Lindlein