About the Project
Cell surface transporters and not diffusion is responsible for the transfer of metabolites across a cell’s membrane. Many types of drugs are structurally very similar to natural metabolites and as a consequence they are treated by the cell as though they are the natural homologue. Therefore, the uptake mechanisms used by cells for the natural metabolite can be exploited in drug development to be taken into the cell; however, this is rarely the case. We have used the Tanimoto Index to relate the structure of drugs to their nearest fit natural substances and determined which cell surface transporters are likely to recognise the drug as a substrate for uptake. The planned study is intended to continue initial studies to profile transporters as signatures of differentiated cell types, and then to design substrates to cell specific transporters to use as carriers of drug payloads.
Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area / subject. Candidates with experience in molecular biology, chemical biology, directed evolution and computational biology are encouraged to apply.
For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (https://www.bmh.manchester.ac.uk/study/research/apply/). Informal enquiries may be made directly to the primary supervisor. On the online application form select PhD Bioinformatics.
For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit www.internationalphd.manchester.ac.uk
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website View Website
2. GeneGini: assessment via the Gini coefficient of reference 'housekeeping' genes and highly heterogeneous human transporter expression profiles. O’Hagan S, Wright Muelas M, Day P, Lundberg E, Kell D. Cell Syst. 2018 Feb 28;6(2):230-244. https://doi.org/10.1101/155697.
3. The role and robustness of the Gini coefficient as an unbiased tool for the selection of Gini genes for normalising expression profiling data. Wright Muelas M, Mughal F, O'Hagan S, Day PJ, Kell DB. Sci Rep. Nov 29;9(1):17960. 2019.
4.Enhancing drug efficacy and therapeutic index through cheminformatics-based selection of small molecule binary weapons that improve transporter-mediated targeting: a cytotoxic system based on gemcitabine. Grixti GM, O’ Hagan S, Day PJR, Kell DB. Front Pharmacol Mar 27;8:155, 2017.
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