Solubility and Crystallisation of Peptides
Lead Research Organisation:
Imperial College London
Department Name: Chemical Engineering
Abstract
This project aims to develop digital twins for crystallisation processes of amino acids and peptides, with the goal of producing robust, accurate models which can mimic experimental setups. From this, it will be possible to perform in-silico experimentation to predict and optimise critical quality attributes of the process, such as crystal size and yield. As well as this, the project also aims to assess the efficacy of automation in assisting crystallisation processes, while reducing
the amount of manual experimental work required. This report begins with a comprehensive literature review of the solubility, nucleation, and growth of peptide crystals, as well as a comparison of currently employed methods for peptide crystallisation control and modelling. The key research gap identified is the lack of development of robust peptide crystallisation models, with much of the reported data being correlated empirically, and therefore specific to individual processes. This prompts the development of robust crystallisation models which can predict the outcomes of changes in operating conditions, and be used as optimisation tools.
the amount of manual experimental work required. This report begins with a comprehensive literature review of the solubility, nucleation, and growth of peptide crystals, as well as a comparison of currently employed methods for peptide crystallisation control and modelling. The key research gap identified is the lack of development of robust peptide crystallisation models, with much of the reported data being correlated empirically, and therefore specific to individual processes. This prompts the development of robust crystallisation models which can predict the outcomes of changes in operating conditions, and be used as optimisation tools.
Organisations
People |
ORCID iD |
| Jerry Heng (Primary Supervisor) | |
| Hamish Mitchell (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/T518207/1 | 05/10/2020 | 30/09/2025 | |||
| 2715169 | Studentship | EP/T518207/1 | 01/10/2020 | 31/03/2024 | Hamish Mitchell |
| Description | Peptides are a unique class of pharmaceutical for the treatment of many chronic diseases. However, they are costly to produce, primarily due to expensive separation and purification steps (mostly chromatographic methods). Crystallisation is therefore an attractive alternative for the purification of synthetic peptides, but little is known on their crystallisation behaviour. The work funded through this award has focused on studying the crystallisation behaviour of model peptides. One system of choice is the family of peptides composed of only the simplest amino acid, glycine. The crystallisation behaviour of glycine (Gly), diglycine (Gly-Gly) and triglycine (Gly-Gly-Gly) has been studied experimentally. Through this, it was found that the addition of silica, a common additive in the manufacture of tablets, improved the rate of crystallisation of these peptides in water. Accompanying computational studies reveal that this may be due to favourable interactions between the peptide molecule and the surface chemistry of the additives. As these peptides are commonly synthesised step-by-step (e.g. Gly->Gly-Gly->Gly-Gly-Gly), this has elucidated further pertinent research on the interactions between glycine peptides of different lengths, and any impact the presence of a glycine-based impurity might have on the crystallisation of these peptides. Another peptide which has been studied is a model peptide provided by industrial collaborators. This peptide is much longer than the aforementioned glycine peptides, and as had not been crystallised previously to the start of the award. Work here has been focused on a) obtaining successful crystallisation conditions for the peptide, b) optimising the crystallisation conditions, c) increasing the scale of crystallisation from nanolitre trials to microlitres, and d) the use of robotics to assist with menial liquid handling steps. Further work will focus on the continued scale-up of the crystallisation of this peptide to the millilitre scale. Finally, computational work associated with this award has been focused on the usage of conventional crystallisation models to describe the crystallisation behaviour of a model protein, lysozyme, and a model peptide, insulin. Through this, it was found that certain crystallisation equations provided a superior fit to experimental data, and these equations were also adapted to include important variables such as the pH of the system. The development of these models will be used in parallel to scale-up studies on all of the aforementioned peptides, as peptides are costly to produce and therefore any experiments which can be conducted digitally will be invaluable. |
| Exploitation Route | As this work is focused on the establishment of crystallisation behaviour of a vast class of pharmaceuticals, it is hoped that the knowledge gained from the outcomes of this award will provide key insights into the successful adoption of crystallisation for the purification of peptides in industry. In turn, it is hoped that this will drive down production costs and hopefully increase the availability of peptide therapeutics to patients in need. It is also useful to note that regardless of the outcomes of the funding (e.g. whether crystallisation is a viable choice for the purification of longer peptides as well as shorter ones, or not) it is important that this research is conducted to ascertain the utility of peptide crystallisation. |
| Sectors | Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |