Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we will assume that you are happy to receive all cookies and you will not see this message again. Click 'Find out more' for information on how to change your cookie settings.

Research groups

Anthony Nash

PhD MRSC


Postdoctoral Research Associate

My original higher education was in Artificial Intelligence before working as a software engineer for five years at Motorola R&D. Then in 2013, I defended my PhD in Computational Chemistry and Chemical Biology at the University of Warwick in the centre for Molecular Organisation and Assembly in Cells (MOAC). My thesis focused on elucidating the unique free energy contributions from amino acids substitutions in low complexity scaffold transmembrane proteins during dimerisation.

After graduating, I worked as a postdoc between the main campus and the Royal National Orthopaedic Hospital, UCL. My research focused on quantum mechanical modelling of non-enzymatic glycation reactions of glucose-crosslinked human collagen and molecular dynamics of advanced glycation end products in collagen systems. During my three and a half years at UCL, I was also a visiting researcher for one year at St Mary's campus, Imperial College London. My time was spent supporting bioinformatics and genomic epidemiology technique with atomistic models of drug resistance mechanisms founds in pathogenic fungal organisms. My work at Imperial concluded with the releases of www.mardy.net, a database of resistance mechanisms found in pathogenic fungus.

I am now working at DPAG in Prof. Caleb Webber's group. My research comprises of clinical epidemiology over NHS data records, transcriptional analysis of pain models, and cheminformatics of drug structure and docking for the repurposing of medications for the treatment of migraine. I am particularly interested in understanding whether we can make predictions on headache outcome from drug-structure given a structure-transcriptional activity relationship.