8E15

A computationally stabilized hMPV F protein

8E15 の概要

• エントリーDOI: 10.2210/pdb8e15/pdb
• 分子名称: F2 protein, F1 protein with Fibritin peptide, beta-D-mannopyranose-(1-4)-2-acetamido-2-deoxy-beta-D-glucopyranose-(1-4)-2-acetamido-2-deoxy-beta-D-glucopyranose, ... (5 entities in total)
• 機能のキーワード: human metapneumovirus, fusion protein, computational stabilization, viral protein
• 由来する生物種: Human metapneumovirus; 詳細
• タンパク質・核酸の鎖数: 2
• 化学式量合計: 58715.36

構造登録者

Huang, J.,Gonzalez, K.,Mousa, J.,Strauch, E. (登録日: 2022-08-09, 公開日: 2023-04-12, 最終更新日: 2024-11-13)

主引用文献

Gonzalez, K.J.,Huang, J.,Criado, M.F.,Banerjee, A.,Tompkins, S.M.,Mousa, J.J.,Strauch, E.M.
A general computational design strategy for stabilizing viral class I fusion proteins.
Nat Commun, 15:1335-1335, 2024

PubMed Abstract: Many pathogenic viruses rely on class I fusion proteins to fuse their viral membrane with the host cell membrane. To drive the fusion process, class I fusion proteins undergo an irreversible conformational change from a metastable prefusion state to an energetically more stable postfusion state. Mounting evidence underscores that antibodies targeting the prefusion conformation are the most potent, making it a compelling vaccine candidate. Here, we establish a computational design protocol that stabilizes the prefusion state while destabilizing the postfusion conformation. With this protocol, we stabilize the fusion proteins of the RSV, hMPV, and SARS-CoV-2 viruses, testing fewer than a handful of designs. The solved structures of these designed proteins from all three viruses evidence the atomic accuracy of our approach. Furthermore, the humoral response of the redesigned RSV F protein compares to that of the recently approved vaccine in a mouse model. While the parallel design of two conformations allows the identification of energetically sub-optimal positions for one conformation, our protocol also reveals diverse molecular strategies for stabilization. Given the clinical significance of viruses using class I fusion proteins, our algorithm can substantially contribute to vaccine development by reducing the time and resources needed to optimize these immunogens.

PubMed: 38351001
DOI: 10.1038/s41467-024-45480-z

実験手法

X-RAY DIFFRACTION (2.41 Å)