Understanding immobilised enzymes by NMR spectroscopy

Enzyme immobilisation is the conversion of a soluble enzyme molecule into a solid particle form. This allows the recovery of the enzyme catalyst for its re-use and avoids protein contamination of the product streams. A better understanding of immobilised enzymes is necessary for their rational development. A more rational design can help enormously in the applicability of these systems in different areas, from biosensors to chemical industry. Immobilised enzymes are challenging systems to study and very little information is given by conventional biochemical analysis such as catalytic activity and amount of protein. Here, solid-state NMR has been applied as the main technique to study these systems and evaluate them more precisely. Various approaches are presented for a better understanding of immobilised enzymes, which is the aim of this thesis. Firstly, the requirements of a model system of study will be discussed. The selected systems will be comprehensibly characterised by a variety of techniques but mainly by solid-state NMR. The chosen system will essentially be the enzyme α-chymotrypsin covalently immobilised on two functionalised inorganic supports – epoxide silica and epoxide alumina – and an organic support – Eupergit®. The study of interactions of immobilised enzymes with other species is vital for understanding the macromolecular function and for predicting and engineering protein behaviour. The study of water, ions and inhibitors interacting with various immobilised enzyme systems is covered here. The interactions of water and sodium ions were studied by 17O and 23Na multiple-quantum techniques, respectively. Various pore sizes of the supports were studied for the immobilised enzyme in the presence of labelled water and sodium cations. Finally, interactions between two fluorinated inhibitors and the active site of the enzyme will be explored using 19F NMR, offering a unique approach to evaluate catalytic behaviour. These interactions will be explored by solution-state NMR firstly, then by solid-state NMR. NMR has the potential to give information about the state of the protein in the solid support, but the precise molecular interpretation is a difficult task.

Physicochemical complexity in complex chemical systems

Self-replication and compartmentalization are two central properties thought to be essential for minimal life, and understanding how such processes interact in the emergence of complex reaction networks is crucial to exploring the development of complexity in chemistry and biology. Autocatalysis can emerge from multiple different mechanisms such as formation of an initiator, template self-replication and physical autocatalysis (where micelles formed from the reaction product solubilize the reactants, leading to higher local concentrations and therefore higher rates). Amphiphiles are also used in artificial life studies to create protocell models such as micelles, vesicles and oil-in-water droplets, and can increase reaction rates by encapsulation of reactants. So far, no template self-replicator exists which is capable of compartmentalization, or transferring this molecular scale phenomenon to micro or macro-scale assemblies. Here a system is demonstrated where an amphiphilic imine catalyses its own formation by joining a non-polar alkyl tail group with a polar carboxylic acid head group to form a template, which was shown to form reverse micelles by Dynamic Light Scattering (DLS). The kinetics of this system were investigated by 1H NMR spectroscopy, showing clearly that a template self-replication mechanism operates, though there was no evidence that the reverse micelles participated in physical autocatalysis. Active oil droplets, composed from a mixture of insoluble organic compounds in an aqueous sub-phase, can undergo processes such as division, self-propulsion and chemotaxis, and are studied as models for minimal cells, or protocells. Although in most cases the Marangoni effect is responsible for the forces on the droplet, the behaviour of the droplet depends heavily on the exact composition. Though theoretical models are able to calculate the forces on a droplet, to model a mixture of oils on an aqueous surface where compounds from the oil phase are dissolving and diffusing through the aqueous phase is beyond current computational capability. The behaviour of a droplet in an aqueous phase can only be discovered through experiment, though it is determined by the droplet's composition. By using an evolutionary algorithm and a liquid handling robot to conduct droplet experiments and decide which compositions to test next, entirely autonomously, the composition of the droplet becomes a chemical genome capable of evolution. The selection is carried out according to a fitness function, which ranks the formulation based on how well it conforms to the chosen fitness criteria (e.g. movement or division). Over successive generations, significant increases in fitness are achieved, and this increase is higher with more components (i.e. greater complexity). Other chemical processes such as chemiluminescence and gelation were investigated in active oil droplets, demonstrating the possibility of controlling chemical reactions by selective droplet fusion. Potential future applications for this might include combinatorial chemistry, or additional fitness goals for the genetic algorithm. Combining the self-replication and the droplet protocells research, it was demonstrated that the presence of the amphiphilic replicator lowers the interfacial tension between droplets of a reaction mixture in organic solution and the alkaline aqueous phase, causing them to divide. Periodic sampling by a liquid handling robot revealed that the extent of droplet fission increased as the reaction progressed, producing more individual protocells with increased self-replication. This demonstrates coupling of the molecular scale phenomenon of template self-replication to a macroscale physicochemical effect.