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8UKM

T33-ml30 - Designed Tetrahedral Protein Cage Using Machine Learning Algorithms

8UKM の概要
エントリーDOI10.2210/pdb8ukm/pdb
EMDBエントリー42355
分子名称T33-ml30-redesigned-tandem-BMC-T-fold, T33-ml30-redesigned-4-OT-fold (2 entities in total)
機能のキーワードnanohedra, protein cage, tetrahedral, de novo protein interface, machine learning, two components, proteinmpnn, nanoparticle, de novo protein
由来する生物種synthetic construct
詳細
タンパク質・核酸の鎖数2
化学式量合計34849.69
構造登録者
Castells-Graells, R.,Meador, K.,Sawaya, M.R.,Yeates, T.O. (登録日: 2023-10-14, 公開日: 2024-03-06, 最終更新日: 2024-06-19)
主引用文献Meador, K.,Castells-Graells, R.,Aguirre, R.,Sawaya, M.R.,Arbing, M.A.,Sherman, T.,Senarathne, C.,Yeates, T.O.
A suite of designed protein cages using machine learning and protein fragment-based protocols.
Structure, 32:751-765.e11, 2024
Cited by
PubMed Abstract: Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, but their creation remains challenging. Here, we apply computational approaches to design a suite of tetrahedrally symmetric, self-assembling protein cages. For the generation of docked conformations, we emphasize a protein fragment-based approach, while for sequence design of the de novo interface, a comparison of knowledge-based and machine learning protocols highlights the power and increased experimental success achieved using ProteinMPNN. An analysis of design outcomes provides insights for improving interface design protocols, including prioritizing fragment-based motifs, balancing interface hydrophobicity and polarity, and identifying preferred polar contact patterns. In all, we report five structures for seven protein cages, along with two structures of intermediate assemblies, with the highest resolution reaching 2.0 Å using cryo-EM. This set of designed cages adds substantially to the body of available protein nanoparticles, and to methodologies for their creation.
PubMed: 38513658
DOI: 10.1016/j.str.2024.02.017
主引用文献が同じPDBエントリー
実験手法
ELECTRON MICROSCOPY (4.2 Å)
構造検証レポート
Validation report summary of 8ukm
検証レポート(詳細版)ダウンロードをダウンロード

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件を2025-12-31に公開中

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