Mapping the glycosyltransferase fold landscape using interpretable deep learning

Glycosyltransferases (GT) are proteins that display extensive sequence and functional variation on a subset of 3D folds. Here, the authors use interpretable deep learning to predict 3D folds from sequence without the need for sequence alignment, which also enables the prediction of GTs with new fold...

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Auteurs principaux: Rahil Taujale, Zhongliang Zhou, Wayland Yeung, Kelley W. Moremen, Sheng Li, Natarajan Kannan
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/f5c17c58d05e4400857aec9c85fdb18c
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