Multipolar scattering models, such as the transferable aspherical atom model, account for atomic chemical interactions and provide a more accurate representation of experimental data. However, the simpler independent atom model (IAM), which assumes non-interacting atoms, is the only model available in the most widely used macromolecular refinement programs. This is primarily because IAM offers a hard-to-beat combination of computational efficiency and modelling power at typical macromolecular resolutions. By contrast, more accurate multipolar modelling has historically been limited due to its computational cost and the absence of an interface between software capable of calculating structure factors and gradients based on multipolar models and software designed for macromolecular refinement. This work introduces pyDiSCaMB, a Python software package designed to integrate between the computational crystallography toolbox (cctbx) and the quantum crystallography library DiSCaMB (Densities in Structural Chemistry and Molecular Biology), thus enabling multipolar scattering models in Phenix's toolkit. The implementation, features and capabilities of pyDiSCaMB are presented, the runtimes for the calculation of structure factor and target gradients with respect to atomic parameters are explored, and Fourier images of electrostatic potential, electron density and deformation maps are computed as illustrative examples. The pyDiSCaMB library will make multipolar modelling widely available to the structural biology community, potentially transforming refinement and model-building for both crystallography and cryogenic electron microscopy (cryoEM).

Many proteins rely on metal ions for function, with their oxidation states (OS) playing a crucial role in enzymatic reactions. Determining OS alongside structural information enables more detailed studies of metalloenzyme reaction mechanisms. Electron crystallography techniques, specifically three-dimensional electron diffraction (3D ED/MicroED) and serial electron diffraction (SerialED), offer a unique approach for OS determination with structural detail, as electrons are particularly sensitive to charge distributions by probing the electrostatic potential. However, accurately inferring OS from electrostatic potential maps remains challenging due to limitations in data collection and processing protocols, as well as constraints in available atomic scattering models used for refinement. This thesis investigates the challenges and feasibility of OS determination from iron complexes and iron-containing enzymes using electron diffraction data.

To improve the resolution and accuracy of the electrostatic potential maps, 3D ED data acquisition and processing protocols were optimised for microcrystals of two proteins. Increasing data redundancy and using smaller overlapping wedges with high electron flux significantly improved signal-to-noise ratio, completeness, and resolution if the data.

To study the impact of different atomic scattering models, both independent atom model (IAM) and transferable aspherical atom model (TAAM) were evaluated for refinement of an iron complex against 3D ED data. The results demonstrated that IAM significantly overestimates the impact of different OS on the atomic scattering amplitude. In contrast, TAAM significantly improved refinement accuracy and reduced map noise, highlighting the importance of accurate atomic scattering models for interpreting the electrostatic potential map.

A new SerialED protocol improved the resolution of the diffraction data of an iron-containing protein from 2.4 Å to 1.3 Å. More importantly, it minimized site-specific radiation damage at the iron site. This protocol was then used for experimental and theoretical analyses of another iron-containing protein in two different redox states. Isomorphous difference maps between the two redox states revealed a signal residing at the iron positions. Model-derived structure factors using TAAM indicated that changes in iron OS significantly contribute to the isomorphous difference map and cause up to a 50% change in specific reflection intensities. These findings suggest that differences in structure factor amplitudes due to OS changes are already detectable within the current precision of the data.

This thesis lays the foundation for using electron crystallography to investigate metal-ion OS in metalloenzymes by optimising 3D ED data acquisition, developing a SerialED protocol that generates high-resolution data while minimizing radiation damage, assessing different methods for modelling metals of various OS, and evaluating the theoretical impact of changes in OS on electrostatic potential maps in a model protein. These advancements enhance electrostatic potential map accuracy and OS determination, paving the way for future mechanistic studies of redox reactions in metalloenzymes.

Understanding the structure of an active pharmaceutical ingredient is essential for gaining insights into its physicochemical properties. Sodium valproate, one of the most effective antiepileptic drugs, was first approved for medical use in 1967. However, the structure of its anhydrous form has remained unresolved. This is because it was difficult to grow crystals of sufficient size for single-crystal X-ray diffraction (SCXRD). Although 3D electron diffraction (3D ED) can be used for studying crystals that are too small for SCXRD, the crystals of anhydrous sodium valproate are extremely sensitive to both humidity and electron beams. They degrade quickly both in air and under an electron beam at room temperature. In this study, we developed a glovebox-assisted cryo-transfer workflow for the preparation of EM grids in a protected atmosphere to overcome the current challenges for studying air- and beam-sensitive samples using 3D ED. Using this technique, we successfully determined the structure of anhydrous sodium valproate, revealing the formation of Na-valproate polyhedral chains. Our results provide a robust framework for the 3D ED analysis of air-sensitive crystals, greatly enhancing its utility across various scientific disciplines.

Extracting high-performance nanomaterials from waste presents a promising avenue for valorization. This study presents two methods for extracting cellulose nanofibrils (CNFs) from discarded textiles. Post-consumer cotton fabrics are chemically treated through either cationization with (2,3-epoxypropyl)trimethylammonium chloride or TEMPO/NaBr-catalyzed oxidation, followed by fibrillation to produce Cat-CNFs and TO-CNFs, respectively. Molecular models indicate variations in the effective volume of each grafted group, influencing the true densities of the functionalized fibers. Significant differences in the morphology of the CNFs arise from each functionalization route. Both CNF types exhibit high surface charge (>0.9 mmol g⁻¹), small cross-sections (<10 nm), and high aspect ratios (>35). TO-CNFs have a higher surface charge, whereas Cat-CNFs exhibit a higher aspect ratio and greater colloidal stability across a broader pH range. Cat-CNFs exhibit cross-sections at the elementary fibril level, highlighting the steric impact of the grafted surface groups on fibrillation efficiency. Nanopapers from these CNFs demonstrate high optical transmittance and haze, whereas anisotropic foams show mechanical properties comparable to foams made from wood-based CNFs. This work highlights the potential of post-consumer cotton textiles as a CNF source and the impact of chemical treatment on the properties of the fibers, CNFs, and resulting lightweight materials.

X-ray protein crystallography has predominantly centred on growing large (> 5 µm) single crystals for structural analysis. While fragments of these large-grown, as well as small-grown crystals have been utilized in electron diffraction (3D ED/MicroED), a universal method for protein crystallisation tailored to sub-micrometre thickness is missing. In this study, we present a method wherein rapid mixing and fragmentation of initial crystals yield well-diffracting nanocrystals in seconds or minutes. In suitable space groups, these nanocrystals can form thin plates, providing ideal samples for (3D ED/MicroED) without requiring focused ion beam milling. The large number of suitably sized crystals also allows for the preparation of densely populated grids suitable for serial ED. We further introduce a streamlined manual grid preparation protocol using polysorbate 20 as a wetting agent, eliminating the need for glow discharging or plunge freezers. By applying these methods, micro- to nano-sized crystals of four different protein samples were generated and the resolution of each sample reached beyond 1.5 Å. Our high-resolution diffraction data demonstrate that slow and undisturbed growth is not necessary for obtaining well-diffracting protein crystals. This study offers a general and feasible sample preparation approach that enables high-resolution protein structure determination by electron diffraction.