8T6E

Crystal structure of T33-28.3: Deep-learning sequence design of co-assembling tetrahedron protein nanoparticles

8T6E の概要

• エントリーDOI: 10.2210/pdb8t6e/pdb
• 分子名称: T33-28.3: A, T33-28.3: B (3 entities in total)
• 機能のキーワード: deep-learning, de novo design, proteinmpnn, rosetta, tetrahedrons, de novo protein
• 由来する生物種: synthetic construct; 詳細
• タンパク質・核酸の鎖数: 24
• 化学式量合計: 374478.58

構造登録者

Bera, A.K.,de Haas, R.J.,Kang, A.,Sankaran, B.,King, N.P. (登録日: 2023-06-15, 公開日: 2024-04-24)

主引用文献

de Haas, R.J.,Brunette, N.,Goodson, A.,Dauparas, J.,Yi, S.Y.,Yang, E.C.,Dowling, Q.,Nguyen, H.,Kang, A.,Bera, A.K.,Sankaran, B.,de Vries, R.,Baker, D.,King, N.P.
Rapid and automated design of two-component protein nanomaterials using ProteinMPNN.
Proc.Natl.Acad.Sci.USA, 121:e2314646121-e2314646121, 2024

PubMed Abstract: The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

PubMed: 38502697
DOI: 10.1073/pnas.2314646121

実験手法

X-RAY DIFFRACTION (2.48 Å)