The role of metabolism in shaping enzyme structures over 400 million years

Oliver Lemke, Benjamin Murray Heineike, Sandra Viknander, Nir Cohen, Feiran Li, Jacob Lucas Steenwyk, Leonard Spranger, Federica Agostini, Cory Thomas Lee, Simran Kaur Aulakh, Judith Berman, Antonis Rokas, Jens Nielsen, Toni Ingolf Gossmann, Aleksej Zelezniak and Markus Ralser ()
Additional contact information
Oliver Lemke: Charité-Universitätsmedizin Berlin
Benjamin Murray Heineike: Charité-Universitätsmedizin Berlin
Sandra Viknander: Chalmers University of Technology
Nir Cohen: Charité-Universitätsmedizin Berlin
Feiran Li: Chalmers University of Technology
Jacob Lucas Steenwyk: University of California Berkeley
Leonard Spranger: Charité-Universitätsmedizin Berlin
Federica Agostini: Charité-Universitätsmedizin Berlin
Cory Thomas Lee: Charité-Universitätsmedizin Berlin
Simran Kaur Aulakh: University of Oxford
Judith Berman: Tel Aviv University
Antonis Rokas: Vanderbilt University
Jens Nielsen: Chalmers University of Technology
Toni Ingolf Gossmann: TU Dortmund University
Aleksej Zelezniak: Chalmers University of Technology
Markus Ralser: Charité-Universitätsmedizin Berlin

Nature, 2025, vol. 644, issue 8075, 280-289

Abstract: Abstract Advances in deep learning and AlphaFold2 have enabled the large-scale prediction of protein structures across species, opening avenues for studying protein function and evolution1. Here we analyse 11,269 predicted and experimentally determined enzyme structures that catalyse 361 metabolic reactions across 225 pathways to investigate metabolic evolution over 400 million years in the Saccharomycotina subphylum2. By linking sequence divergence in structurally conserved regions to a variety of metabolic properties of the enzymes, we reveal that metabolism shapes structural evolution across multiple scales, from species-wide metabolic specialization to network organization and the molecular properties of the enzymes. Although positively selected residues are distributed across various structural elements, enzyme evolution is constrained by reaction mechanisms, interactions with metal ions and inhibitors, metabolic flux variability and biosynthetic cost. Our findings uncover hierarchical patterns of structural evolution, in which structural context dictates amino acid substitution rates, with surface residues evolving most rapidly and small-molecule-binding sites evolving under selective constraints without cost optimization. By integrating structural biology with evolutionary genomics, we establish a model in which enzyme evolution is intrinsically governed by catalytic function and shaped by metabolic niche, network architecture, cost and molecular interactions.

Date: 2025
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DOI: 10.1038/s41586-025-09205-6

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