Protein design and variant prediction using autoregressive generative models

Autor: Jung-Eun Shin, Adam J. Riesselman, Aaron W. Kollasch, Conor McMahon, Elana Simon, Chris Sander, Aashish Manglik, Andrew C. Kruse, Debora S. Marks
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Nature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/s41467-021-22732-w
Popis: The ability to design functional sequences is central to protein engineering and biotherapeutics. Here the authors introduce a deep generative alignment-free model for sequence design applied to highly variable regions and design and test a diverse nanobody library with improved properties for selection experiments.
Databáze: Directory of Open Access Journals