Development of Serial Crystallography Methods for Synchrotrons and X-ray Free-Electron Lasers

X-ray crystallography of proteins is a well-established method to identify atomic level molecular arrangement, however when exposing crystalline proteins to ionising radiation, damage can occur to their overall molecular structure (global damage), while solvated electrons generated by X-rays can induce changes to metal sites within a protein (site-specific damage) (Garman & Weik, 2015). These changes occur quickly, at doses much lower than required to obtain a complete dataset, meaning there may be many metalloproteins deposited in the Protein Data Bank that are incorrect (Bowman, Bridwell-Rabb, & Drennan, 2016). The advent of X-ray free-electron lasers (XFELs) that produce femtosecond pulses of extremely high quality (brilliance) X-ray beams, allows data to be collected before radiation damage has the time to occur (Schlichting, 2015). This thesis will describe the development of novel ‘chip’ based serial data collection and processing strategies, applied at Diamond Light Source microfocus beamline I24, and at BL3 EH2 at the SACLA XFEL, Japan. A technique coined ‘multiple serial structures’ (MSS) has been developed and used in this thesis to assess how crystalline proteins change as a function of X-ray dose, as enzyme reactivity can be driven in crystals by exploiting X- ray generated solvated electrons to drive redox reactions (Horrell et al., 2016). By performing a near identical data collection strategy at the SACLA XFEL, we have been able to directly compare the effects of accumulated dose in MSS datasets to ‘damage free’ XFEL structures, using the same target protein. Chip methods have also been examined and developed in this thesis as a tool to assess the ‘dark progression’ of radiation damage, a technique we have coined ‘dark progression series’ (DPS). Further, we present a data processing technique that possesses the ability to identify protein-ligand complexes from extremely small subsets of synchrotron and XFEL diffraction data, whereby only a few hundred diffraction images may be needed.

Name dc:type.qualificationname

phd

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of Essex

Year dc:date.issued

2020

Author dc:creator

• Ebrahim, Ali

• QH301 Biology

Language dc:language

en