7MCC

Crystal structure of an AI-designed TIM-barrel F2C

7MCC の概要

• エントリーDOI: 10.2210/pdb7mcc/pdb
• 分子名称: AI-designed TIM-barrel F2C, SULFATE ION (3 entities in total)
• 機能のキーワード: de novo protein, tim-barrel
• 由来する生物種: synthetic construct
• タンパク質・核酸の鎖数: 1
• 化学式量合計: 20973.93

構造登録者

Mathews, I.I.,Anand-Achim, N.,Perez, C.P.,Huang, P.S. (登録日: 2021-04-02, 公開日: 2022-01-19, 最終更新日: 2024-04-03)

主引用文献

Anand, N.,Eguchi, R.,Mathews, I.I.,Perez, C.P.,Derry, A.,Altman, R.B.,Huang, P.S.
Protein sequence design with a learned potential.
Nat Commun, 13:746-746, 2022

PubMed Abstract: The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network model to automate design of sequences onto protein backbones, having learned directly from crystal structure data and without any human-specified priors. The model generalizes to native topologies not seen during training, producing experimentally stable designs. We evaluate the generalizability of our method to a de novo TIM-barrel scaffold. The model produces novel sequences, and high-resolution crystal structures of two designs show excellent agreement with in silico models. Our findings demonstrate the tractability of an entirely learned method for protein sequence design.

PubMed: 35136054
DOI: 10.1038/s41467-022-28313-9

実験手法

X-RAY DIFFRACTION (1.46 Å)