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

• 成果类型: Article
• 署名作者: Lemke, Oliver; Heineike, Benjamin Murray; Viknander, Sandra; Cohen, Nir; Li, Feiran; Steenwyk, Jacob Lucas; Spranger, Leonard; Agostini, Federica; Lee, Cory Thomas; Aulakh, Simran Kaur; Berman, Judith; Rokas, Antonis; Nielsen, Jens; Gossmann, Toni Ingolf; Zelezniak, Aleksej; Ralser, Markus
• 署名单位: Free University of Berlin; Humboldt University of Berlin; Charite Universitatsmedizin Berlin; Humboldt University of Berlin; Free University of Berlin; Charite Universitatsmedizin Berlin; Berlin Institute of Health; University of Oxford; Wellcome Centre for Human Genetics; Francis Crick Institute; Chalmers University of Technology; Howard Hughes Medical Institute; University of California System; University of California Berkeley; Vanderbilt University; University of California System; University of California Berkeley; Vanderbilt University; Tel Aviv University; Dortmund University of Technology; Vilnius University; University of London; King's College London; Max Planck Society
• 刊物名称: Nature
• ISSN/ISSBN: 0028-0860
• DOI: 10.1038/s41586-025-09205-6
• 发表日期: 2025-08-07
• 关键词: evolution; selection; coverage; COSTS

摘要

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.