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Designed active-site library reveals thousands of functional GFP variants

Author

Listed:
  • Jonathan Yaacov Weinstein

    (Weizmann Institute of Science)

  • Carlos Martí-Gómez

    (Cold Spring Harbor Laboratory)

  • Rosalie Lipsh-Sokolik

    (Weizmann Institute of Science)

  • Shlomo Yakir Hoch

    (Weizmann Institute of Science)

  • Demian Liebermann

    (Weizmann Institute of Science)

  • Reinat Nevo

    (Weizmann Institute of Science)

  • Haim Weissman

    (Weizmann Institute of Science)

  • Ekaterina Petrovich-Kopitman

    (Weizmann Institute of Science)

  • David Margulies

    (Weizmann Institute of Science)

  • Dmitry Ivankov

    (Skolkovo Institute of Science and Technology)

  • David M. McCandlish

    (Cold Spring Harbor Laboratory)

  • Sarel J. Fleishman

    (Weizmann Institute of Science)

Abstract

Mutations in a protein active site can lead to dramatic and useful changes in protein activity. The active site, however, is sensitive to mutations due to a high density of molecular interactions, substantially reducing the likelihood of obtaining functional multipoint mutants. We introduce an atomistic and machine-learning-based approach, called high-throughput Functional Libraries (htFuncLib), that designs a sequence space in which mutations form low-energy combinations that mitigate the risk of incompatible interactions. We apply htFuncLib to the GFP chromophore-binding pocket, and, using fluorescence readout, recover >16,000 unique designs encoding as many as eight active-site mutations. Many designs exhibit substantial and useful diversity in functional thermostability (up to 96 °C), fluorescence lifetime, and quantum yield. By eliminating incompatible active-site mutations, htFuncLib generates a large diversity of functional sequences. We envision that htFuncLib will be used in one-shot optimization of activity in enzymes, binders, and other proteins.

Suggested Citation

  • Jonathan Yaacov Weinstein & Carlos Martí-Gómez & Rosalie Lipsh-Sokolik & Shlomo Yakir Hoch & Demian Liebermann & Reinat Nevo & Haim Weissman & Ekaterina Petrovich-Kopitman & David Margulies & Dmitry I, 2023. "Designed active-site library reveals thousands of functional GFP variants," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38099-z
    DOI: 10.1038/s41467-023-38099-z
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    References listed on IDEAS

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    3. Frank J. Poelwijk & Michael Socolich & Rama Ranganathan, 2019. "Learning the pattern of epistasis linking genotype and phenotype in a protein," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    4. Sarel J Fleishman & Andrew Leaver-Fay & Jacob E Corn & Eva-Maria Strauch & Sagar D Khare & Nobuyasu Koga & Justin Ashworth & Paul Murphy & Florian Richter & Gordon Lemmon & Jens Meiler & David Baker, 2011. "RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-10, June.
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