Downstream Processing and Structure Confirmation of Chemoenzymatically Produced Macrocycles

Macrocycles, in particular modified cyclic peptides (CPs), are promising compounds that have great potential to hit complex targets in human disease such as protein-protein interactions (PPIs) which are common in diseases such as cancer and inflammation.1 These targets cannot be modulated using traditional small-molecule chemistry but by using computational design and synthetic and/or enzymatic chemistry processes CPs can be designed and made to inhibit these PPIs. CP production can be carried out in parallel using automation, but there is an industrial need to improve downstream processes to isolate and carry out structure confirmation and provide quality assurance for CPs. The main aim of this project is therefore to use computational and data mining methods on chromatographic and spectroscopic data at each stage of the process to develop tools to predict physicochemical parameters of the CPs to assist their isolation and to automatically confirm their successful synthesis. The objectives are:
1.) To accurately calculate physicochemical parameters (e.g. logP and PSA) of linear precursors and CPs and use these to optimise compound isolation processes.
2.) To analyse and understand unique MS fragmentations occurring in linear precursors and CPs and use these to develop a tool to predict the most likely fragmentations.
3.) To develop a tool that can analyse MS fragmentation data from linear precursors and CPs and compare this to the predicted fragments to confirm successful synthesis.