structure-solution-fluorescent-protein-cerulean-using

Structure Solution of the Fluorescent Protein Cerulean Using MeshAndCollect

X-ray crystallography is the major technique used to obtain high resolution information concerning the 3-dimensional structures of biological ...

Structural Biology Group

Recent advances in macromolecular crystallography have made it practical to rapidly collect hundreds of sub-data sets consisting of small oscillations of incomplete data. This approach, generally referred to as serial crystallography, has many uses, including an increased effective dose per data set, the collection of data from crystals without harvesting (in situ data collection) and studies of dynamic events such as catalytic reactions. However, selecting which data sets from this type of experiment should be merged can be challenging and new methods are required. Here, it is shown that a genetic algorithm can be used for this purpose, and five case studies are presented in which the merging statistics are significantly improved compared with conventional merging of all data.

Merging of synchrotron serial crystallographic data by a genetic algorithm.

Specific radiation damage can be used to determine phases de novo from macromolecular crystals. This method is known as radiation-damage-induced phasing (RIP). One limitation of the method is that the dose of individual data sets must be minimized, which in turn leads to data sets with low multiplicity. A solution to this problem is to use data from multiple crystals. However, the resulting signal can be degraded by a lack of isomorphism between crystals. Here, it is shown that serial synchrotron crystallography in combination with selective merging of data sets can be used to determine high-quality phases for insulin and thaumatin, and that the increased multiplicity can greatly enhance the success rate of the experiment.

X-ray and UV radiation-damage-induced phasing using synchrotron serial crystallography.

Single-wavelength anomalous diffraction (SAD) phasing from multiple crystals can be especially challenging in samples with weak anomalous signals and/or strong non-isomorphism. Here, advantage is taken of the combinatorial diversity possible in such experiments to study the relationship between merging statistics and downstream metrics of phasing signals. It is furthermore shown that a genetic algorithm (GA) can be used to optimize the grouping of data sets to enhance weak anomalous signals based on these merging statistics.

Article	Year
Merging of synchrotron serial crystallographic data by a genetic algorithm. Acta crystallographica. Section D, Structural biology\| PubMed ID: 27599735	2016
X-ray and UV radiation-damage-induced phasing using synchrotron serial crystallography. Acta crystallographica. Section D, Structural biology\| PubMed ID: 29652263	2018
Choosing your (Friedel) mates wisely: grouping data sets to improve anomalous signal. Acta crystallographica. Section D, Structural biology\| PubMed ID: 30821708	2019

Nicolas Foos

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