8KAC

De novo design protein -NX1

8KAC の概要

• エントリーDOI: 10.2210/pdb8kac/pdb
• 分子名称: De novo design protein -NX1 (2 entities in total)
• 機能のキーワード: de novo design protein, de novo protein
• 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: 13943.16

構造登録者

Wang, S.,Liu, Y. (登録日: 2023-08-02, 公開日: 2024-08-07, 最終更新日: 2025-05-07)

主引用文献

Liu, Y.,Wang, S.,Dong, J.,Chen, L.,Wang, X.,Wang, L.,Li, F.,Wang, C.,Zhang, J.,Wang, Y.,Wei, S.,Chen, Q.,Liu, H.
De novo protein design with a denoising diffusion network independent of pretrained structure prediction models.
Nat.Methods, 21:2107-2116, 2024

PubMed Abstract: The recent success of RFdiffusion, a method for protein structure design with a denoising diffusion probabilistic model, has relied on fine-tuning the RoseTTAFold structure prediction network for protein backbone denoising. Here, we introduce SCUBA-diffusion (SCUBA-D), a protein backbone denoising diffusion probabilistic model freshly trained by considering co-diffusion of sequence representation to enhance model regularization and adversarial losses to minimize data-out-of-distribution errors. While matching the performance of the pretrained RoseTTAFold-based RFdiffusion in generating experimentally realizable protein structures, SCUBA-D readily generates protein structures with not-yet-observed overall folds that are different from those predictable with RoseTTAFold. The accuracy of SCUBA-D was confirmed by the X-ray structures of 16 designed proteins and a protein complex, and by experiments validating designed heme-binding proteins and Ras-binding proteins. Our work shows that deep generative models of images or texts can be fruitfully extended to complex physical objects like protein structures by addressing outstanding issues such as the data-out-of-distribution errors.

PubMed: 39384986
DOI: 10.1038/s41592-024-02437-w

実験手法

X-RAY DIFFRACTION (1.75 Å)