View source for 9gdx


==SARS-CoV-2 Spike protein Beta Variant at 4C structural flexibility / heterogeneity analyses==
<StructureSection load='9gdx' size='340' side='right'caption='[[9gdx]], [[Resolution|resolution]] 2.80&Aring;' scene=''>
== Structural highlights ==
<table><tr><td colspan='2'>[[9gdx]] is a 3 chain structure with sequence from [https://en.wikipedia.org/wiki/Escherichia_virus_T4 Escherichia virus T4] and [https://en.wikipedia.org/wiki/Severe_acute_respiratory_syndrome_coronavirus_2 Severe acute respiratory syndrome coronavirus 2]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=9GDX OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=9GDX FirstGlance]. <br>
</td></tr><tr id='method'><td class="sblockLbl"><b>[[Empirical_models|Method:]]</b></td><td class="sblockDat" id="methodDat">Electron Microscopy, [[Resolution|Resolution]] 2.8&#8491;</td></tr>
<tr id='resources'><td class="sblockLbl"><b>Resources:</b></td><td class="sblockDat"><span class='plainlinks'>[https://proteopedia.org/fgij/fg.htm?mol=9gdx FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=9gdx OCA], [https://pdbe.org/9gdx PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=9gdx RCSB], [https://www.ebi.ac.uk/pdbsum/9gdx PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=9gdx ProSAT]</span></td></tr>
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== Function ==
[https://www.uniprot.org/uniprot/WAC_BPT4 WAC_BPT4] Chaperone responsible for attachment of long tail fibers to virus particle. Forms the fibrous structure on the neck of the virion called whiskers. During phage assembly, 6 fibritin molecules attach to each virion neck through their N-terminal domains, to form a collar with six fibers ('whiskers').[https://www.uniprot.org/uniprot/SPIKE_SARS2 SPIKE_SARS2] attaches the virion to the cell membrane by interacting with host receptor, initiating the infection (By similarity). Binding to human ACE2 receptor and internalization of the virus into the endosomes of the host cell induces conformational changes in the Spike glycoprotein (PubMed:32142651, PubMed:32075877, PubMed:32155444). Uses also human TMPRSS2 for priming in human lung cells which is an essential step for viral entry (PubMed:32142651). Proteolysis by cathepsin CTSL may unmask the fusion peptide of S2 and activate membranes fusion within endosomes.[HAMAP-Rule:MF_04099]<ref>PMID:32075877</ref> <ref>PMID:32142651</ref> <ref>PMID:32155444</ref>   mediates fusion of the virion and cellular membranes by acting as a class I viral fusion protein. Under the current model, the protein has at least three conformational states: pre-fusion native state, pre-hairpin intermediate state, and post-fusion hairpin state. During viral and target cell membrane fusion, the coiled coil regions (heptad repeats) assume a trimer-of-hairpins structure, positioning the fusion peptide in close proximity to the C-terminal region of the ectodomain. The formation of this structure appears to drive apposition and subsequent fusion of viral and target cell membranes.[HAMAP-Rule:MF_04099]  Acts as a viral fusion peptide which is unmasked following S2 cleavage occurring upon virus endocytosis.[HAMAP-Rule:MF_04099]
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== Publication Abstract from PubMed ==
Single-particle analysis by Cryo-electron microscopy (CryoEM) provides direct access to the conformation of each macromolecule. However, the image's signal-to-noise ratio is low, and some form of classification is usually performed at the image processing level to allow structural modeling. Classical classification methods imply the existence of a discrete number of structural conformations. However, new heterogeneity algorithms introduce a novel reconstruction paradigm, where every state is represented by a lower number of particles, potentially just one, allowing the estimation of conformational landscapes representing the different structural states a biomolecule explores. In this work, we present a novel deep learning-based method called HetSIREN. HetSIREN can fully reconstruct or refine a CryoEM volume in real space based on the structural information summarized in a conformational latent space. The unique characteristics that set HetSIREN apart start with the definition of the approach as a real space-based only method, a fact that allows spatially focused analysis, but also the introduction of a novel network architecture specifically designed to make use of meta-sinusoidal activations, with proven high analytics capacities. Continuing with innovations, HetSIREN can also refine the pose parameters of the images at the same time that it conditions the network with prior information/constraints on the maps, such as Total Variation and L1 denoising, ultimately yielding cleaner volumes with high-quality structural features. Finally, but very importantly, HetSIREN addresses one of the most confusing issues in heterogeneity analysis, as it is the fact that real structural heterogeneity estimation is entangled with pose estimation (and to a lesser extent with CTF estimation), in this way, HetSIREN introduces a novel encoding architecture able to decouple pose and CTF information from the conformational landscape, resulting in more accurate and interpretable conformational latent spaces. We present results on computer-simulated data, public data from EMPIAR, and data from experimental systems currently being studied in our laboratories. An important finding is the sensitivity of the structure and dynamics of the SARS-CoV-2 Spike protein on the storage temperature.

Real-space heterogeneous reconstruction, refinement, and disentanglement of CryoEM conformational states with HetSIREN.,Herreros D, Mata CP, Noddings C, Irene D, Krieger J, Agard DA, Tsai MD, Sorzano COS, Carazo JM bioRxiv [Preprint]. 2024 Sep 19:2024.09.16.613176. doi: , 10.1101/2024.09.16.613176. PMID:39345408<ref>PMID:39345408</ref>

From MEDLINE&reg;/PubMed&reg;, a database of the U.S. National Library of Medicine.<br>
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== References ==
<references/>
__TOC__
</StructureSection>
[[Category: Escherichia virus T4]]
[[Category: Large Structures]]
[[Category: Severe acute respiratory syndrome coronavirus 2]]
[[Category: Agard DA]]
[[Category: Carazo JM]]
[[Category: Herreros D]]
[[Category: Irene D]]
[[Category: Mata CP]]
[[Category: Noddings C]]
[[Category: Sorzano COS]]
[[Category: Tsai M-D]]