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Professor David Wales ScD, FRSC, FRS

Portrait of dw34

The self-assembly of complex mesoscopic structures, the folding of proteins, and the complicated phenomenology of glasses are all manifestations of the underlying potential energy surface (PES). In each of these fields related ideas have emerged to explain and predict chemical and physical properties in terms of the PES. In studies of clusters and glasses the PES itself is often investigated directly, whereas for proteins and other biomolecules it is also common to define free energy surfaces, as the figure below illustrates for lysozyme.

Applications of energy landscape theory in my group range from studies of tunnelling splitting patterns in small molecules to computer simulation of protein folding and misfolding, including aggregation of misfolded proteins. Other active research topics include global optimisation and investigation of how the thermodynamic and dynamic properties of glasses are related to the underlying PES.

Two recent advances are now providing new insight into larger systems. Discrete path sampling enables dynamical properties to be obtained efficiently, and is being used to calculate folding rates for proteins. Unexpected connections between dynamics and thermodynamics have also been revealed by the application of catastrophe theory to energy landscapes, and new results are now being obtained to characterize phase transitions.


Stochastic surface walking reaction sampling for resolving heterogeneous catalytic reaction network: A revisit to the mechanism of water-gas shift reaction on Cu
XJ Zhang, C Shang, ZP Liu
– The Journal of Chemical Physics
Exploiting sparsity in free energy basin-hopping
KH Sutherland-Cash, RG Mantell, DJ Wales
– Chemical Physics Letters
Prediction of early unplanned intensive care unit readmission in a UK tertiary-care hospital: A cross-sectional machine learning approach
T Desautels, R Das, J Calvert, M Trivedi, C Summers, DJ Wales, A Ercole
– BMJ Open
Energy landscapes and dynamics of glycine on Cu(110)
M Sacchi, DJ Wales, SJ Jenkins
– Phys. Chem. Chem. Phys.
Exploring biomolecular energy landscapes.
JA Joseph, K Röder, D Chakraborty, RG Mantell, DJ Wales
– Chemical communications (Cambridge, England)
Machine learning landscapes and predictions for patient outcomes.
R Das, DJ Wales
– Royal Society open science
Decoupled Associative and Dissociative Processesin Strong yet Highly Dynamic Host-Guest Complexes
EA Appel, F Biedermann, D Hoogland, J Del Barrio, MD Driscoll, S Hay, DJ Wales, OA Scherman
– Journal of the American Chemical Society
Energy landscapes for machine learning
AJ Ballard, R Das, S Martiniani, D Mehta, L Sagun, JD Stevenson, DJ Wales
– Physical chemistry chemical physics : PCCP
Improving Computational Predictions of Single-Stranded RNA Tetramers with Revised α/γ Torsional Parameters for the Amber Force Field
DJ Wales, I Yildirim
– J Phys Chem B
Defining and quantifying frustration in the energy landscape: Applications to atomic and molecular clusters, biomolecules, jammed and glassy systems
VK de Souza, JD Stevenson, SP Niblett, JD Farrell, DJ Wales
– The Journal of chemical physics
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01223 336354

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