(BBSRC DTP) Cysteine reactivity: learning from natural variation to construct a tool for biotechnology

Cysteine reactivity is known to be a key factor in several well-studied pathways, for example disulphide regulation and redox homeostasis with the thioredoxin system. Generally, more reactive cysteine sidechains are associated with prevalence of the thiolate form (over the thiol), and structure-based prediction methods have been developed [1]. In more recent years, high throughput proteomics allows us to study various cysteine modifications and show how little is understood of what controls them. Indeed, one report argues that biophysical properties, as currently estimated, have little to do with reactivity [2]. Our own unpublished work is somewhat more optimistic, particularly when amino acid sequence data is leveraged (as opposed to using only the more limited structural annotations). We find that different types of cysteine modification are enriched for opposite properties in terms of predicted thiolate/thiol status, and we are now asking how this could relate to the underlying chemical mechanisms of these modifications. This is the PhD starting point, with the Supervisory team of bioinformatics (JW) and chemical mechanism (SdV), leading to experimental reduction potential determination (CB) to test and validate models for cysteine reactivity, and ultimately make them available as predictive tools, to the research community. The project is a combination of biology/bioinformatics, chemistry and biotechnology, with a projected equal split between computational and experimental work. In terms of the biology, establishing that protein sequence and structure modulates type (and degree) of cysteine modification will inform areas such as cellular redox homeostasis and targeting of proteins to membranes. There are parallels with protein phosphorylation (at Ser, Thr and Tyr), where mass spectrometric data has complemented studies of kinases to fill in the picture [3]. Cysteine modification, though, is less well understood. Chemically, little is known about mechanisms of cysteine post-translational modification and the student will use the experience of the SdV group in working with cysteine-based enzymes. A key target for the project is to deliver predictive tools that can be used to design functional cysteine sites for biotechnology, for example in localising proteins to membranes, potentially in a scheme that is switchable by pH, redox potential, or ligand binding. The project seeks to learn from nature and apply those lessons to synthetic biology.

http://personalpages.manchester.ac.uk/staff/j.warwicker/
http://www.manchester.ac.uk/research/sam.devisser/research
http://www.manchester.ac.uk/research/christopher.blanford/

Contact for further Information
For more details contact Dr J Warwicker ([Email Address Removed])