Insights into the design and synthesis of artificial enzymes

This thesis is divided into three parts. The first part is an introduction to the design and synthesis of artificial enzymes and details some of the more recent developments in this area, with an emphasis on emerging 'selection approaches' to artificial enzymes. The introduction concludes with a short review on the synthesis of artificial receptors using dynamic combinatorial libraries (DCLs), and discusses the relevance of such a strategy in the design and synthesis of artificial enzymes. The second part is a discussion of our investigations into the design and synthesis of an artificial enzyme which is able to induce selectivity in the acid catalysed ring opening reaction of pinene oxide to afford trans-carveol as the major product. The research is based on the molecular imprinting approach to artificial enzymes and begins with the synthesis of polystyrene-divinylbenzene molecularly imprinted polymers (MIPs), using the crude transition state analogue (1R, 5R)-trans-carvyl amine as the imprint molecule. Binding studies confirmed the successful imprinting of a range of MIPs with various crosslinker to monomer ratios and loadings. The influence of the MIPs on the product distribution of the ring opening reaction of pinene oxide was investigated. The development and synthesis of a second generation transition state analogue (TSA), N-methyl isonipecotic acid N-oxide is then described. The TSA was used in molecular modelling studies to select three tri-peptide 'functional monomers' which established favourable binding interactions with the ligand TSA. The peptides were synthesised and pulsed field gradient NMR experiments were used to study the change in the observed rate of translational diffusion on complex formation between the TSA and the three tripeptides. Research into the development of polyacrylamides as MIPs is then presented. Binding studies were carried out to establish the effectiveness of imprinting of a range of polyacrylamide MIPs. Part three is an account of the experimental work and procedures used throughout this work

Accelerating BRPF1b hit identification with BioPhysical and Active Learning Screening (BioPALS)

We report the development of BioPhysical and Active Learning Screening (BioPALS); a rapid and versatile hit identification protocol combining AI‐powered virtual screening with a GCI‐driven biophysical confirmation workflow. Its application to the BRPF1b bromodomain afforded a range of novel micromolar binders with favorable ADMET parameters. In addition to the excellent in silico/in vitro confirmation rate demonstrated with BRPF1b, binding kinetics are determined, and binding topologies predicted for all hits. BioPALS is a lean, data‐rich, and standardized approach to hit identification applicable to wide range of biological targets