ARPHA Preprints, doi: 10.3897/arphapreprints.e116671
Tracing bio-structures with serial crystallography: Facilitating the access to high-throughput macromolecular x-ray crystallography techniques.
expand article infoMiguel Angel Gonzalez‡, Rudolf Dimper§, Patrick Fuhrmann|, Gianluca Santoni§, Jordi Bodera§, Jayesh Wagh§, Irina Safiulina‡, Arianna D'Angelo‡, Paolo Mutti‡, Paul Millar|, Krisztian Pozsa, Leonardo Sala, Alun Ashton, Giuseppe La Rocca#
‡ Institut Laue-Langevin, Grenoble, France§ European Synchrotron Radiation Facility, Grenoble, France| DESY, Hamburg, Germany¶ Paul Scherrer Institut, Villigen, Switzerland# EGI, Amsterdam, Netherlands

Corresponding author: Miguel Angel Gonzalez ( gonzalezm@ill.fr )

© Miguel Angel Gonzalez, Rudolf Dimper, Patrick Fuhrmann, Gianluca Santoni, Jordi Bodera, Jayesh Wagh, Irina Safiulina, Arianna D'Angelo, Paolo Mutti, Paul Millar, Krisztian Pozsa, Leonardo Sala, Alun Ashton, Giuseppe La Rocca.
This is an open access preprint distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Gonzalez MA, Dimper R, Fuhrmann P, Santoni G, Bodera J, Wagh J, Safiulina I, D'Angelo A, Mutti P, Millar P, Pozsa K, Sala L, Ashton A, La Rocca G (2023) Tracing bio-structures with serial crystallography: Facilitating the access to high-throughput macromolecular x-ray crystallography techniques. ARPHA Preprints. https://doi.org/10.3897/arphapreprints.e116671
Open Access
Abstract
Serial (femtosecond) X-ray-Crystallography (SFX) is a special variant of macromolecular X-ray crystallography aiming at rapid structural studies at room temperature. This highly innovative technology permits investigation of bio-structures not tractable with conventional X-ray crystallography, and is capable of studying fast in-situ biochemical processes. The method is still relatively new, but it is already one of the most prominent applications of free-electron lasers (FELs), and increasingly also of very brilliant synchrotron radiation sources. One of the unique characteristics of this type of experiments is the extremely high repetition rate combined with a quite moderate success rate. A crucial task in the rather complex data processing pipeline is the rapid and accurate classification of images: typically, only a few percent of the images contain a diffraction pattern suitable for subsequent integration and structure refinement. AI-supported image classification is hence particularly suited for drastic data reduction, saving precious storage space, compute cycles and processing time. The experimental techniques and methodologies are rapidly evolving, and the integration of emerging tools into the processing pipeline is an essential task. SFX data sets are big, require substantial storage, and computational power. The main goal of this SP is to establish and develop a data processing platform, which integrates services and developments from PaNOSC/ExPaNDS. The platform should provide integrated processing pipelines for well-established and cutting-edge applications, so that cross-disciplinary users with modest expertise gain rapid and convenient access to tools and documentation of newest developments. On the other hand, it should also provide convenient access to FAIR SFX-data, to foster developments and strengthen collaboration between experimentalists and developers of new algorithms and software implementations. This approach is of very high relevance for all PaN synchrotron and FEL facilities and their users.
Keywords
EOSC Future, Science Clusters, Science Projects, PaNOSC, Macromolecular Serial Crystallography