PhD Studentship in Biomimetic Colloid Science

The interactions between macromolecules in aqueous solutions are complex phenomena that govern many important chemical and biological processes. For example, the intermolecular interactions of proteins dictate their spatio-temporal distributions, such as cluster formation, aggregation and liquid-liquid phase separation. Although the percentage of non-polar residues on protein surfaces may be as high as 70%, the cellular concentrations of proteins are maintained at extremely high level, i.e. up to 40% in volume fraction. In comparison, most synthetic colloidal systems precipitate at such high concentrations due to various attractive interactions and electrolyte screening of Coulomb repulsion. One of the most important forces in water-based chemical and biological environments is the hydrophobic interaction as displayed in lipid bilayer organisation and protein folding. Although vital at the bionano interface, its underlying principles have not been fully understood.

In our group, we have developed a modular platform, which is based on the synthesis of gold nanoparticles with a labile capping agent followed by subsequent functionalization with prescribed mixtures of target thiol ligands. This approach not only caters for tailored nanoscale colloids with tunable ligand shells but also offers the investigation of colloidal phenomena by small angle X-ray scattering (SAXS) due to the pronounced scattering length density of the Au core. The obtained scattering profiles can then be used to extract colloidal interaction terms via machine learning algorithms (carried out in collaboration). Based on some preliminary work (and in combination with complimentary techniques), this model system offers unique opportunities to unravel colloidal phenomena found in nature with relevance for fundamental science but also various industrial applications (e.g. in drug delivery, biosensing, food science and personal care).

The project will build on these preliminary studies to establish an integrated synthetic and analytical approach to mimic colloidal interactions found in nature and unravel their unusual properties. To this end, the work will be carried out in 4 stages:

Stage 1. Platform development (Month 1-12). The first year until the viva upgrade will be dedicated to platform development, i.e.
- synthesis of suitable gold nanoparticles with low dispersity, tunable core size and adaptable ligand shell
- investigation of colloidal stability by SAXS
- implementation of machine learning algorithms to interpret SAXS data with advanced models (extended DLVO theory)
Training will be critically important, with extended stays envisioned with collaborators (data science: Dr Keith Butler, QMUL; SAXS: Prof Stefan Förster) as well as participation in summer / winter schools to engage with the community. This phase will completed with the drafting and defense of the upgrade viva.

Stage 2. Unravelling protein solubility (Month 13-24).
Knowledge acquired in stage 1 will serve to create accurate mimics of natural proteins by matching of size and ligand composition. Amphiphilic molecules will serve as hydroptropes in order to study critical factors for colloidal stability and implement these for novel records of gold nanoparticle solubility. Findings will serve for collaborations with computational colleagues, such as Dr Seishi Shimidzu from the University of York.

Stage 3. Triggered molecular recognition phenomena (Month 25-36).
The final experimental stage of the PhD is currently envisioned to be used for the study of molecular recognition in native environments. The experimental tool-kit developed herein will be complemented by studies of interfacial adsorption phenomena using quartz crystal microbalance with dissipation monitoring. Synergies are expected with other PhD studies in my group, e.g. on automation and high throughput characterisation.