Evolution of dynamical networks enhances catalysis in a designer enzyme

Adrian A Bunzel*, J L R Anderson, Donald Hilvert, Vickery L Arcus, Marc W Van Der Kamp, Adrian J Mulholland*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

60 Citations (Scopus)
235 Downloads (Pure)


Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by non-Arrhenius behaviour of many natural enzymes1,2. However, its physical origin and relationship to evolution of catalytic activity remain uncertain. Here, we show that directed evolution of a computationally designed Kemp eliminase introduces dynamical changes that give rise to an activation heat capacity absent in the original design3. Extensive molecular dynamics simulations show that evolution results in the closure of solvent exposed loops and better packing of the active site with transition state stabilising residues. Remarkably, these changes give rise to a correlated dynamical network involving the transition state and large parts of the protein. This network tightens the transition state ensemble, which induces an activation heat capacity and thereby nonlinearity in the temperature dependence. Our results have implications for understanding enzyme evolution (e.g. in explaining the role of distal mutations and evolutionary tuning of dynamical responses) and suggest that integrating dynamics with design and evolution will accelerate the development of efficient novel enzymes.
Original languageEnglish
Pages (from-to)1017-1022
Number of pages6
JournalNature Chemistry
Issue number10
Early online date19 Aug 2021
Publication statusPublished - Oct 2021

Bibliographical note

Funding Information:
H.A.B. and A.J.M. thank EPSRC (EP/M013219/1 and EP/M022609/1) and, along with J.L.R.A., the BBSRC (BB/R016445/1) for funding. H.A.B. thanks the Swiss National Science Foundation (Postdoc.Mobility fellowship) for support. M.W.v.d.K. thanks BBSRC for support (David Phillips Fellowship, BB/M026280/1). V.L.A. and A.J.M. thank the Marsden Fund of New Zealand (16-UOW-027). V.L.A. is a James Cook Research Fellow (Royal Society of New Zealand). D.H. thanks the Swiss National Science Foundation. This work was conducted using the computational facilities of the Advanced Computing Research Centre, University of Bristol. We thank R. Crean and S. Osuna for help with and providing a script to perform the shortest-path analysis.

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature Limited.


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