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S C I E N T I F I C H I G H L I G H T S

S T R U C T U R A L B I O L O G Y

2022 has witnessed another frenetic year for the Structural Biology (SB) group. Inevitably, COVID-19 restrictions have still had a major impact on the operation of the post-Extremely Brilliant Source (EBS) Structural Biology beamlines, with users being mostly virtual. This challenge has been met successfully thanks to the joint efforts of the Structural Biology group and the long-standing collaboration with the EMBL Grenoble (through the Grenoble Joint Structural Biology Group), the Institut de Biologie Structurale (IBS), the Commissariat à l Energie Atomique et aux énergies alternatives (CEA) and the Institut Laue Langevin (ILL), in addition to the ESRF support groups and services, who have been key in ensuring the efficient running of computational operating systems for the remote control of experiments.

Remotely or onsite, all our beamlines are now operational and take full advantage of the new EBS, facilitating the collection of high-quality X-ray diffraction (MX) and solution X-ray scattering (BioSAXS) data for structural biology research. In particular, the refurbishment of the fully automatic ID30A-1 beamline has increased its capacity for fragment/ligand-based screening towards the development of new drugs. Additionally, the newly constructed ID29/EBSL8 beamline for room-temperature and time-resolved serial crystallography (TR-SSX), hosted the first users in September. In combination with the refurbishment of the microfocus beamlines ID30A-3 and ID23-2 and the in crystallo optical spectroscopy icOS facility, the ESRF now provides a unique ensemble of cutting-edge technology for the structural study of complex biological molecular processes across a range of timescales and sample sizes at ambient and cryogenic temperatures. Alternative trapping technologies are also evolving at the HPMX facility, with the design of new high-pressure cells to analyse cryo-trapped intermediate processes and the introduction of gases in macromolecular crystals.

With the recent release of the AlphaFold protein structure database, machine-learning and artificial intelligence approaches have offered the possibility in many cases to solve the challenge of phasing macromolecular data. In the Structural Biology group, with the help of the Software group, we are exploiting this new era with the implementation of these computational approaches in our automatic processing workflows. Using ISPyB as a hub for SB data, users can easily specify one or multiple sequence identifiers, which are used for automatic molecular replacement phasing. Efforts are also underway to use machine-learning techniques to mine data already in ISPyB in order to develop better data collection strategies on our MX beamlines (ID23-1, ID23-2, ID30A-1, ID30A-3, ID30B and ID29) and improve structural