Nature Communications (Dec 2022)

Prediction of designer-recombinases for DNA editing with generative deep learning

  • Lukas Theo Schmitt,
  • Maciej Paszkowski-Rogacz,
  • Florian Jug,
  • Frank Buchholz

DOI
https://doi.org/10.1038/s41467-022-35614-6
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 12

Abstract

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Design of recombinases with new target sites is usually achieved through cycles of directed molecular evolution. Here the authors report Recombinase Generator, RecGen, an algorithm for generation of designer-recombinases; they perform experimental validation to show that this can predict recombinase sequences.