Research
Living cells run on molecules that bind, bend and push on each other. I build computer models of those molecules (atomistic molecular dynamics, coarse-grained and network models, and machine learning) to explain how their structure determines what they do, and to predict what new molecules will do.
The themes below are the questions I keep coming back to. Each page lists the related papers.
Mechanics of the cytoskeleton
How microtubules bear and pass on mechanical forces, from the arrangement of their protofilaments to the way drugs such as taxol change their stiffness.
Anaesthetics at the molecular scale
What volatile anaesthetics do to tubulin, actin and lipid membranes, studied with long molecular dynamics simulations.
Predicting how molecules bind
Docking, molecular dynamics and machine learning to predict whether, how strongly and how long a molecule binds its target, with models whose predictions can be explained.
Taste receptors and food molecules
The structure and dynamics of bitter taste receptors such as TAS2R46, and computational tools that predict which molecules they recognise.
Nanocarriers and drug delivery
How dendrimers and dendrons bind and carry photosensitising drugs such as rose bengal, modelled at atomistic and coarse-grained resolution.
Proteins in neurodegeneration
Conformational dynamics of proteins linked to neurodegenerative disease, such as the MORN domains of Alsin and the way they assemble.
Data science in clinical research
Collaborations in which I contribute data analysis and machine learning to clinical and biomedical studies, from genetic risk to transplant outcomes.