8XYU
De novo designed protein GPX4-3
8XYU の概要
エントリーDOI | 10.2210/pdb8xyu/pdb |
分子名称 | De novo designed GPX4-3 (2 entities in total) |
機能のキーワード | 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 | 20261.25 |
構造登録者 | |
主引用文献 | Liu, J.,Guo, Z.,You, H.,Zhang, C.,Lai, L. All-Atom Protein Sequence Design Based on Geometric Deep Learning. Angew.Chem.Int.Ed.Engl., :e202411461-e202411461, 2024 Cited by PubMed Abstract: Designing sequences for specific protein backbones is a key step in creating new functional proteins. Here, we introduce GeoSeqBuilder, a deep learning framework that integrates protein sequence generation with side chain conformation prediction to produce the complete all-atom structures for designed sequences. GeoSeqBuilder uses spatial geometric features from protein backbones and explicitly includes three-body interactions of neighboring residues. GeoSeqBuilder achieves native residue type recovery rate of 51.6%, comparable to ProteinMPNN and other leading methods, while accurately predicting side chain conformations. We first used GeoSeqBuilder to design sequences for thioredoxin and a hallucinated three-helical bundle protein. All the 15 tested sequences expressed as soluble monomeric proteins with high thermal stability, and the 2 high-resolution crystal structures solved closely match the designed models. The generated protein sequences exhibit low similarity (minimum 23%) to the original sequences, with significantly altered hydrophobic cores. We further redesigned the hydrophobic core of glutathione peroxidase 4, and 3 of the 5 designs showed improved enzyme activity. Although further testing is needed, the high experimental success rate in our testing demonstrates that GeoSeqBuilder is a powerful tool for designing novel sequences for predefined protein structures with atomic details. GeoSeqBuilder is available at https://github.com/PKUliujl/GeoSeqBuilder. PubMed: 39295564DOI: 10.1002/anie.202411461 主引用文献が同じPDBエントリー |
実験手法 | X-RAY DIFFRACTION (1.59 Å) |
構造検証レポート
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