Scaffolding protein functional sites using deep learning | Zendy

Jue Wang | Zendy; Sidney Lisanza | Zendy; David Juergens | Zendy; Doug Tischer | Zendy; Joseph L. Watson | Zendy; Karla M. Castro | Zendy; Robert J. Ragotte | Zendy; Amijai Saragovi | Zendy; Lukas F. Milles | Zendy; Minkyung Baek | Zendy; Ivan Anishchenko | Zendy; Wei Yang | Zendy; Derrick R. Hicks | Zendy; Marc Expòsit | Zendy; Thomas Schlichthaerle | Zendy; Jung-Ho Chun | Zendy; Justas Dauparas | Zendy; Nathaniel R. Bennett | Zendy; Basile I. M. Wicky | Zendy; Andrew Muenks | Zendy; Frank DiMaio | Zendy; Bruno E. Correia | Zendy; Sergey Ovchinnikov | Zendy; David Baker | Zendy

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Scaffolding protein functional sites using deep learning

Author(s) -

Jue Wang,

Sidney Lisanza,

David Juergens,

Doug Tischer,

Joseph L. Watson,

Karla M. Castro,

Robert J. Ragotte,

Amijai Saragovi,

Lukas F. Milles,

Minkyung Baek,

Ivan Anishchenko,

Wei Yang,

Derrick R. Hicks,

Marc Expòsit,

Thomas Schlichthaerle,

Jung-Ho Chun,

Justas Dauparas,

Nathaniel R. Bennett,

Basile I. M. Wicky,

Andrew Muenks,

Frank DiMaio,

Bruno E. Correia,

Sergey Ovchinnikov,

David Baker

Publication year - 2022

Publication title -

science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 12.556

H-Index - 1186

eISSN - 1095-9203

pISSN - 0036-8075

DOI - 10.1126/science.abn2100

Subject(s) - scaffold , in silico , computational biology , scaffold protein , functional analysis , protein design , protein secondary structure , sequence (biology) , computer science , protein structure , artificial intelligence , biology , biochemistry , signal transduction , gene , database

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