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-Structure paper
| タイトル | Real-space heterogeneous reconstruction, refinement, and disentanglement of CryoEM conformational states with HetSIREN. |
|---|---|
| ジャーナル・号・ページ | Nat Commun, Vol. 16, Issue 1, Page 3751, Year 2025 |
| 掲載日 | 2025年4月22日 |
著者 | David Herreros / Carlos Perez Mata / Chari Noddings / Deli Irene / James Krieger / David A Agard / Ming-Daw Tsai / Carlos Oscar Sanchez Sorzano / Jose Maria Carazo / ![]() |
| PubMed 要旨 | Single-particle analysis by Cryo-electron microscopy (CryoEM) provides direct access to the conformations of macromolecules. Traditional methods assume discrete conformations, while newer algorithms ...Single-particle analysis by Cryo-electron microscopy (CryoEM) provides direct access to the conformations of macromolecules. Traditional methods assume discrete conformations, while newer algorithms estimate conformational landscapes representing the different structural states a biomolecule explores. This work presents HetSIREN, a deep learning-based method that can fully reconstruct or refine a CryoEM volume in real space based on the structural information summarized in a conformational latent space. HetSIREN is defined as an accurate space-based method that allows spatially focused analysis and the introduction of sinusoidal hypernetworks with proven high analytics capacities. Continuing with innovations, HetSIREN can also refine the images' pose while conditioning the network with additional constraints to yield cleaner high-quality volumes, as well as addressing one of the most confusing issues in heterogeneity analysis, as it is the fact that structural heterogeneity estimations are entangled with pose estimation (and to a lesser extent with CTF estimation) thanks to its decoupling architecture. |
リンク | Nat Commun / PubMed:40263313 / PubMed Central |
| 手法 | EM (単粒子) |
| 解像度 | 2.8 Å |
| 構造データ | EMDB-51279, PDB-9gdx: EMDB-51280, PDB-9gdy: |
| 由来 |
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キーワード | VIRAL PROTEIN / SARS-CoV-2 / Spike Protein / temperature dependence |
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