Chem/Bioinformatic Modelling of Peptide Solubility in Water and Organic Solvents to Enable Greener Peptide Production

About the Project

New modalities in medicine present unique challenges for sustainable manufacturing. In particular, current peptide purification relies on expensive, low throughput methods developed for discovery rather than production, and closing this technological gap is one of the major challenges in both healthcare and green chemistry. A growing consensus in peptide manufacturing is that synthesis of short peptides, either in solid phase or solution phase, followed by their ligation will be the most effective strategy, but this approach depends on reliable prediction of the solubility of short peptides in water and organic solvents, including those containing non natural amino acids.

This project will address this critical need by integrating bioinformatics with the Nguyen group’s existing solubility prediction models for small molecules to develop a systematic model for the prediction of small peptide solubility. The student will synthesise, measure solubility, and curate the first comprehensive database for solubility of short peptides, guided by an active learning AI algorithm to maximise the learning rate and minimise the number of peptides you will need to synthesise using automated microwave synthesis. The predictive models will be developed for natural peptides, before expansion to longer peptides including non-natural amino acids using literature data.

The students will benefit from expertise in Nguyen group in catalysis, high-throughput computational chemistry and AI/Machine Learning in chemistry. In addition, the student will benefit from working in the highly interdisciplinary research environment in the iPRD (iprd.leeds.ac.uk). A seminar programme, where aspects of green chemistry, AI and process engineering are discussed on a monthly basis, will be provided. Opportunities to present work and to network will be provided through the iPRD industrial club meetings, CheM62 meetings and RSC events in addition to inter/national green chemistry and AI conferences.

Please visit the Institute of Process Research and Development website to find out more about our current Research activities.

Funding Notes

A highly competitive EPSRC Doctoral Landscape Award Studentship, based in the School of Chemistry, providing the award of full academic fees, together with a tax-free maintenance grant of £21,805 per year for 3.5 years. Training and support will also be provided. This opportunity is open to UK applicants only. All candidates will be placed into the EPSRC Doctoral Landscape Award Studentship Competition and selection is based on academic merit.