@misc{indiciaeac197867312d,
  title = {Sequence-based generative AI design of versatile tryptophan synthases},
  author = {Lambert, Théophile [California Institute of Technology (CalTech), Pasadena, CA (United States); Univ. Paris-Saclay, Orsay (France)] (ORCID:0009000584858729) and Tavakoli, Amin [California Institute of Technology (CalTech), Pasadena, CA (United States)] and Dharuman, Gautham [Argonne National Laboratory (ANL), Argonne, IL (United States)] and Yang, Jason [California Institute of Technology (CalTech), Pasadena, CA (United States)] (ORCID:0000000331841550) and Bhethanabotla, Vignesh [California Institute of Technology (CalTech), Pasadena, CA (United States)] (ORCID:0000000194016967) and Kaur, Sukhvinder [Elegen Corp, San Carlos, CA (United States)] and Hill, Matthew [Elegen Corp, San Carlos, CA (United States)] and Ramanathan, Arvind [Argonne National Laboratory (ANL), Argonne, IL (United States)] (ORCID:0000000216225488) and Anandkumar, Anima [California Institute of Technology (CalTech), Pasadena, CA (United States)] (ORCID:0000000269746797) and Arnold, Frances H. [California Institute of Technology (CalTech), Pasadena, CA (United States)] (ORCID:000000024027364X)},
  year = {2026},
  doi = {10.1038/s41467-026-68384-6},
  url = {https://www.osti.gov/biblio/3014231},
  note = {Source identifier: 3014231}
}