Author

H. Bunzel

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Open access Sep 2026

Evolution promotes transition-state-like conformations with enhanced basicity and electric fields in the substrate complex of a designer enzyme

Enzymes can be computationally designed for an increasing range of reactions, yet the catalytic efficiencies achieved are typically well below those of natural biocatalysts. Directed evolution can narrow this gap, often improving activity through mutations with non-obvious effects on catalysis. Here, we dissect how dir...

Abbie Lear, H. Bunzel, Adrian J. Mulholland · bioRxiv · 0 citations

#diffusion models Review Open access Sep 2026

What deep learning can and cannot (yet) do for enzyme design.

Deep learning has substantially advanced structure-based enzyme design, yet reliably creating highly efficient enzymes remains out of reach. One emerging enzyme design strategy combines diffusion-based scaffold generation around active-site models with sequence design. Such structure-based approaches have expanded the...

Judith A. Ahr, Moor de Waal, Tudor-Stefan Cotet et al. · Current Opinion in Chemical... · 1 citation

Open access Sep 2026

Machine learned potentials with electrostatic embedding accurately capture Kemp eliminase reactivity

Kemp elimination has become a benchmark for de novo enzyme design due to its simplicity and detailed mechanistic understanding but accurate barrier calculations are required to understand the difference in activity between designed Kemp eliminases. QM/MM MD simulations are capable of calculating reaction barriers, but...

Abbie Lear, E. Chan, Kirill Zinovjev et al. · bioRxiv · 0 citations