{"entity": "researcher", "timestamp": "2026-08-08T16:10:20.357Z", "family": "Li", "given": "Feiran", "initials": "F", "orcid": "0000-0001-9155-5260", "affiliations": ["Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg SE-412 96, Sweden.", "Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg SE-412 96, Sweden."], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/249bec020dae419caad38538e87331f2.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/249bec020dae419caad38538e87331f2"}}, "publications": [{"entity": "publication", "iuid": "822a69d3b0ec4aa3a59daedca9d107c8", "links": {"self": {"href": "https://publications.scilifelab.se/publication/822a69d3b0ec4aa3a59daedca9d107c8.json"}, "display": {"href": "https://publications.scilifelab.se/publication/822a69d3b0ec4aa3a59daedca9d107c8"}}, "title": "The role of metabolism in shaping enzyme structures over 400 million years.", "authors": [{"family": "Lemke", "given": "Oliver", "initials": "O", "orcid": "0000-0002-5104-1836", "researcher": {"href": "https://publications.scilifelab.se/researcher/1ea9f0d77148491fa18aaa7330268348.json"}}, {"family": "Heineike", "given": "Benjamin Murray", "initials": "BM"}, {"family": "Viknander", "given": "Sandra", "initials": "S"}, {"family": "Cohen", "given": "Nir", "initials": "N", "orcid": "0000-0002-5634-1643", "researcher": {"href": "https://publications.scilifelab.se/researcher/897f1026754d4934956ca3024635d936.json"}}, {"family": "Li", "given": "Feiran", "initials": "F", "orcid": "0000-0001-9155-5260", "researcher": {"href": "https://publications.scilifelab.se/researcher/249bec020dae419caad38538e87331f2.json"}}, {"family": "Steenwyk", "given": "Jacob Lucas", "initials": "JL", "orcid": "0000-0002-8436-595X", "researcher": {"href": "https://publications.scilifelab.se/researcher/b3c9d722f73b46f8a34cca4938cf2d5c.json"}}, {"family": "Spranger", "given": "Leonard", "initials": "L", "orcid": "0000-0002-4316-2961", "researcher": {"href": "https://publications.scilifelab.se/researcher/e7e784debe4c419194c7e85cc05c4ddf.json"}}, {"family": "Agostini", "given": "Federica", "initials": "F", "orcid": "0000-0002-4255-4867", "researcher": {"href": "https://publications.scilifelab.se/researcher/311b5e1b9fbb423f94855e86642bd1e3.json"}}, {"family": "Lee", "given": "Cory Thomas", "initials": "CT"}, {"family": "Aulakh", "given": "Simran Kaur", "initials": "SK"}, {"family": "Berman", "given": "Judith", "initials": "J", "orcid": "0000-0002-8577-0084", "researcher": {"href": "https://publications.scilifelab.se/researcher/749d11eaff8d4a50affd2711bfe85700.json"}}, {"family": "Rokas", "given": "Antonis", "initials": "A", "orcid": "0000-0002-7248-6551", "researcher": {"href": "https://publications.scilifelab.se/researcher/c31b5f559903407bb94fc180e9aaff61.json"}}, {"family": "Nielsen", "given": "Jens", "initials": "J"}, {"family": "Gossmann", "given": "Toni Ingolf", "initials": "TI", "orcid": "0000-0001-6609-4116", "researcher": {"href": "https://publications.scilifelab.se/researcher/50c218f57a5b4dc9b33d846db03cef53.json"}}, {"family": "Zelezniak", "given": "Aleksej", "initials": "A", "orcid": "0000-0002-3098-9441", "researcher": {"href": "https://publications.scilifelab.se/researcher/4328a7ff130a44cc90e5282e4a18a2d7.json"}}, {"family": "Ralser", "given": "Markus", "initials": "M", "orcid": "0000-0001-9535-7413", "researcher": {"href": "https://publications.scilifelab.se/researcher/254766a4f72a4223a719f1341daed59f.json"}}], "type": "journal article", "published": "2025-08-00", "journal": {"title": "Nature", "issn": "1476-4687", "volume": "644", "issue": "8075", "pages": "280-289", "issn-l": "0028-0836"}, "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.", "doi": "10.1038/s41586-025-09205-6", "pmid": "40634610", "labels": {"Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12328220"}, {"db": "pii", "key": "10.1038/s41586-025-09205-6"}], "notes": [], "created": "2025-11-28T10:46:32.237Z", "modified": "2025-11-28T10:46:32.679Z"}, {"entity": "publication", "iuid": "d9528bf8ef3e42c590e45cc2d0baf8ac", "links": {"self": {"href": "https://publications.scilifelab.se/publication/d9528bf8ef3e42c590e45cc2d0baf8ac.json"}, "display": {"href": "https://publications.scilifelab.se/publication/d9528bf8ef3e42c590e45cc2d0baf8ac"}}, "title": "GotEnzymes: an extensive database of enzyme parameter predictions.", "authors": [{"family": "Li", "given": "Feiran", "initials": "F", "orcid": "0000-0001-9155-5260", "researcher": {"href": "https://publications.scilifelab.se/researcher/249bec020dae419caad38538e87331f2.json"}}, {"family": "Chen", "given": "Yu", "initials": "Y", "orcid": "0000-0003-3326-9068", "researcher": {"href": "https://publications.scilifelab.se/researcher/36c1db44b0634b5ea85f45a5dba020e7.json"}}, {"family": "Anton", "given": "Mihail", "initials": "M"}, {"family": "Nielsen", "given": "Jens", "initials": "J", "orcid": "0000-0002-9955-6003", "researcher": {"href": "https://publications.scilifelab.se/researcher/7a596e289be4438a8a2653b1f25fea8b.json"}}], "type": "journal article", "published": "2023-01-06", "journal": {"title": "Nucleic Acids Res.", "issn": "1362-4962", "volume": "51", "issue": "D1", "pages": "D583-D586", "issn-l": "0305-1048"}, "abstract": "Enzyme parameters are essential for quantitatively understanding, modelling, and engineering cells. However, experimental measurements cover only a small fraction of known enzyme-compound pairs in model organisms, much less in other organisms. Artificial intelligence (AI) techniques have accelerated the pace of exploring enzyme properties by predicting these in a high-throughput manner. Here, we present GotEnzymes, an extensive database with enzyme parameter predictions by AI approaches, which is publicly available at https://metabolicatlas.org/gotenzymes for interactive web exploration and programmatic access. The first release of this data resource contains predicted turnover numbers of over 25.7 million enzyme-compound pairs across 8099 organisms. We believe that GotEnzymes, with the readily-predicted enzyme parameters, would bring a speed boost to biological research covering both experimental and computational fields that involve working with candidate enzymes.", "doi": "10.1093/nar/gkac831", "pmid": "36169223", "labels": {"Bioinformatics Support, Infrastructure and Training": "Technology development", "Bioinformatics Support and Infrastructure": "Collaborative", "Systems Biology": "Technology development", "Bioinformatics (NBIS)": "Collaborative"}, "xrefs": [{"db": "pmc", "key": "PMC9825421"}, {"db": "pii", "key": "6725766"}], "notes": [], "created": "2022-11-25T08:13:46.214Z", "modified": "2023-05-17T11:36:45.867Z"}]}