A genetic optimization strategy with generality in asymmetric organocatalysis as primary target

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{
  "revision": 5, 
  "id": "1958", 
  "created": "2023-10-31T14:33:31.548655+00:00", 
  "metadata": {
    "doi": "10.24435/materialscloud:z7-ev", 
    "status": "published", 
    "title": "A genetic optimization strategy with generality in asymmetric organocatalysis as primary target", 
    "mcid": "2023.164", 
    "license_addendum": null, 
    "_files": [
      {
        "description": "Compressed folder of csv files and XYZ structures, contains a README.txt file", 
        "key": "Generality_Genetic_Optimization.zip", 
        "size": 4834012, 
        "checksum": "md5:548b845a82e28fe6655cc69fe7556b50"
      }
    ], 
    "owner": 1180, 
    "_oai": {
      "id": "oai:materialscloud.org:1958"
    }, 
    "keywords": [
      "catalysis", 
      "organocatalysis", 
      "generality", 
      "genetic optimization", 
      "organic molecules", 
      "enantioselectivity", 
      "machine learning", 
      "NCCR Catalysis"
    ], 
    "conceptrecid": "1957", 
    "is_last": false, 
    "references": [
      {
        "type": "Preprint", 
        "citation": "S. Gallarati, P. van Gerwen, R. Laplaza, L. Brey, A. Makaveev, C. Corminboeuf, To be submitted, 2023"
      }
    ], 
    "publication_date": "Nov 02, 2023, 17:23:41", 
    "license": "Creative Commons Attribution 4.0 International", 
    "id": "1958", 
    "description": "A catalyst possessing a broad substrate scope, in terms of both turnover and enantioselectivity, is sometimes called \u201cgeneral\u201d. Despite their great utility in asymmetric synthesis, truly general catalysts are difficult or expensive to discover via traditional high-throughput screening and are, therefore, rare. Existing computational tools accelerate the evaluation of reaction conditions from a pre-defined set of experiments to identify the most general ones, but cannot generate entirely new catalysts with enhanced substrate breadth. For these reasons, we report an inverse design strategy based on the open-source genetic algorithm NaviCatGA and on the OSCAR database of organocatalysts to simultaneously probe the catalyst and substrate scope and optimize generality as primary target. We apply this strategy to the Pictet\u2013Spengler condensation, for which we curate a database of 820 reactions, used to train statistical models of selectivity and activity. Starting from OSCAR, we define a combinatorial space of millions of catalyst possibilities, and perform evolutionary experiments on a diverse substrate scope that is representative of the whole chemical space of tetrahydro-\u03b2-carboline products. While privileged catalysts emerge, we show how genetic optimization can address the broader question of generality in asymmetric synthesis, extracting structure\u2013performance relationships from the challenging areas of chemical space.", 
    "version": 1, 
    "contributors": [
      {
        "email": "simone.gallarati@epfl.ch", 
        "affiliations": [
          "Laboratory for Computational Molecular Design, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland"
        ], 
        "familyname": "Gallarati", 
        "givennames": "Simone"
      }, 
      {
        "email": "puck.vangerwen@epfl.ch", 
        "affiliations": [
          "Laboratory for Computational Molecular Design, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland", 
          "National Center for Competence in Research \u2013 Catalysis (NCCR-Catalysis), Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland"
        ], 
        "familyname": "van Gerwen", 
        "givennames": "Puck"
      }, 
      {
        "email": "ruben.laplazasolanas@epfl.ch", 
        "affiliations": [
          "Laboratory for Computational Molecular Design, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland", 
          "National Center for Competence in Research \u2013 Catalysis (NCCR-Catalysis), Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland"
        ], 
        "familyname": "Laplaza", 
        "givennames": "Ruben"
      }, 
      {
        "email": "lucien.brey@epfl.ch", 
        "affiliations": [
          "Laboratory for Computational Molecular Design, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland"
        ], 
        "familyname": "Brey", 
        "givennames": "Lucien"
      }, 
      {
        "email": "alexander.n.makaveev@gmail.com", 
        "affiliations": [
          "Laboratory for Computational Molecular Design, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland"
        ], 
        "familyname": "Makaveev", 
        "givennames": "Alexander"
      }, 
      {
        "email": "clemence.corminboeuf@epfl.ch", 
        "affiliations": [
          "Laboratory for Computational Molecular Design, Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland", 
          "National Center for Competence in Research \u2013 Catalysis (NCCR-Catalysis), Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland", 
          "National Center for Computational Design and Discovery of Novel Materials (MARVEL), Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Vaud, Switzerland"
        ], 
        "familyname": "Corminboeuf", 
        "givennames": "Clemence"
      }
    ], 
    "edited_by": 576
  }, 
  "updated": "2023-11-15T11:00:32.522641+00:00"
}