My research is focussed on reducing the burden of infectious disease by improving antibiotics. If you are interested in doing a DPhil, rotation project or Part II project please get in touch.

  1. Predicting antibiotic resistance

My primary project at present is to develop computational methods able to predict antibiotic resistance by considering the structures of the target protein, the antibiotic and how they dynamically interact  with one another.

The Modernising Medical Microbiology group in Oxford, of which I am a part, is pioneering genetics-based clinical microbiology. The central idea is to infer which antibiotics can be used to treat an infection by examining the mutations in the genome and looking up their effect in a catalogue of previously-seen cases. Here predictive methods are essential if we are to deal with cases that have novel or rare mutations. Alternatively, predictive methods could be used in the development of new antibiotics (or the modification of existing ones) to determine how many mutations allow the bacteria to escape the action of the drug. Minimising this number should, I hope, prolong the lifespan of an antibiotic.

My hypothesis is that mutations in an open-reading frame that cause resistance do so by reducing how well the antibiotic binds to its target protein, whilst not altering how well the natural substrate binds. Prediction is therefore a matter of determining how the binding free energies of both molecules change upon introduction of the protein mutation. Calculating small molecule-protein binding free energies is a mature field. Probably the best-known approach is computational docking which uses a simple heuristic functional to estimate how well a small molecule binds in a specific orientation to a protein. Whilst fast, these methods take no account of the dynamics of either protein or drug are not accurate for a problem of this subtlety. Instead I am applying a class of methods derived from statistical mechanics over sixty years ago. They require, however, 4-5 orders of magnitude more computational resource than simple computational docking and, as a result, have only recently begun to find application outside of theoretical physical chemistry.

My research will benefit from the large amount of genomic and drug susceptibility data being collected by the CRyPTIC project, which is lead by the University of Oxford. I also have interests in distributed computing and citizen science and will be launching a project, called, in 2017. For more information please see this poster in Figshare. I am collaborating with Derrick Crook, Tim Peto, Sarah Walker and other members of the CRyPTIC project.


My preliminary study examined the effect of mutations on the binding of trimethoprim, an antibiotic, to DHFR, an essential protein in S.aureus. I chose seven mutations that were identified by a previous study which sequenced the genomes of a S.aureus infections from two hospitals in the UK. Three of these cause resistance (coloured red above) and four have no effect on the action of the antibiotic (coloured green).

Using sophisticated alchemical free energy methods I was able to not only predict which mutations caused resistance and which did not, but also get good quantitative agreement with experimental measurements of how the binding free energy changes upon mutation (for the F99Y mutant) and also with measured minimum inhibitory concentrations. This work is currently under review and I will update this text when it is published.

These methods work by calculating the work required to change one amino acid side-chain into another as shown in the movie below. The movie zooms in on Leu41 and shows how first the cost of removing the partial electrical charges are calculated, before the sidechain is “alchemically” change to a phenylalanine and lastly, the partial electrical charges are added back.


This technique is derived from classical statistical mechanics and has been known for over sixty years, however, it is only comparatively recently that computers have got fast enough to allow us to try using these approaches on real-world problems, like antibiotic resistance.

2. Improving the oral bioavailability of antibiotics 

Drugs taken orally must either passively diffuse across the membranes of the epithelial cells that line the gut, in which case they must be lipophilic. Or they must  be shuttled across by an endogenous transporter, in which case they must resemble a nutrient.  Little has been known about the endogenous transporters until recently. As a consequence drugs have been optimised to be as lipophilic as possible, restricting the development of naturally-derived drugs, including antibiotics, which tend to be hydrophilic.

Here I am focussing on the human nutrient transporter PepT1 which transports di- and tri-peptides across the lining of the small intestine. PepT1 also happens to recognise and transport many beta-lactam antibiotics and a range of other hydrophilic drugs, thereby ensuring they have high oral bioavailabilities.

The aim of this project is to computationally predict chemical modifications for a range of antibiotics (and other drugs) that will improve their transport by hPepT1 (a peptide transporter found in the human gut) and hence improve their oral bioavailability and clinical effectiveness. We have demonstrated that a combination of free energy methods can accurately predict which di- and tri-peptides are transported by a bacterial homolog of PepT1.

I am mainly collaborating with Simon Newstead (Biochemistry, Oxford), and am also working with Lucy Forrest (NIH), Anthony Watts (Biochemistry, Oxford) and David Meredith (Biological and Medical Sciences, Oxford Brookes).

I co-supervised Firdaus Samsudin, a DPhil student, who worked on this problem and successfully defended his thesis in Nov 2015..


3. Distributed computing, open science and volunteer computing

I have had a long interest in developing novel methods for accelerating calculations using grid computing which goes back to my PhD at UCL when I was a part of the EPSRC RealityGrid project which ran several highly ambitious cross-continental calculations in the fields of material science and molecular biology. More recently, I am in the process of launching an open science project,

4. Membranes and membrane proteins

I have a long-standing interest in how membrane proteins, especially ion channels and transporters, functions. For more information please see my publications.