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Department of Chemistry


The fast and reliable folding of proteins has been described as a consequence of the principle of minimal frustration [1], leading to the commonly employed description of folding based on folding funnels [2]. Importantly, this description may be extended to nucleic acids [3], and forms part of our understanding of any molecular in terms of energy landscapes [4]. While only a single funnel on the potential energy landscape is required to allow for fast folding, a number of systems do not conform with this simple description. Exploration of the energy landscapes for these systems show landscapes exhibiting multiple funnels associated with distinct functions. This observation might be understood as an extension to the principle of minimal frustration, as landscapes will exhibits the number of funnels required to fulfil multiple functions [5]. These multifunctional systems can be manipulated using small perturbations, such as sequence mutations [6].

In this talk, I will present recent algorithmic advances that allow the study of these biological systems, discuss a number of example systems, and highlight how computational approaches lead to an improved understanding of biological systems and offer explanations for experimental observations.

[1] Bryngelson and Wolynes, PNAS, 1987
[2] Leopold, Montal and Onuchic, PNAS, 1992
[3] (a) Thirumalai, PNAS, 1998; (b) Chen and Dill, RNAS, 2000
[4] "Energy landscapes", Wales, CUP, 2003
[5] Röder and Wales, JPCB, 2018
[6] (a) Röder and Wales, JCTC, 2017; (b) Röder and Wales, Biochemistry, 2018; (c) Röder et al, NAR, 2020

Further information


Nov 18th 2020
14:30 to 15:30


Zoom - link to be announced


Theory - Chemistry Research Interest Group