8fez: Difference between revisions

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== Structural highlights ==
== Structural highlights ==
<table><tr><td colspan='2'>[[8fez]] is a 3 chain structure with sequence from [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=8FEZ OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=8FEZ FirstGlance]. <br>
<table><tr><td colspan='2'>[[8fez]] is a 3 chain structure with sequence from [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=8FEZ OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=8FEZ FirstGlance]. <br>
</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=8fez FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=8fez OCA], [https://pdbe.org/8fez PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=8fez RCSB], [https://www.ebi.ac.uk/pdbsum/8fez PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=8fez ProSAT]</span></td></tr>
</td></tr><tr id='method'><td class="sblockLbl"><b>[[Empirical_models|Method:]]</b></td><td class="sblockDat" id="methodDat">Electron Microscopy, [[Resolution|Resolution]] 3.72&#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=8fez FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=8fez OCA], [https://pdbe.org/8fez PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=8fez RCSB], [https://www.ebi.ac.uk/pdbsum/8fez PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=8fez ProSAT]</span></td></tr>
</table>
</table>
== Function ==
== Function ==
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<div style="background-color:#fffaf0;">
<div style="background-color:#fffaf0;">
== Publication Abstract from PubMed ==
== Publication Abstract from PubMed ==
Many pathogenic viruses, including influenza virus, Ebola virus, coronaviruses, and Pneumoviruses, rely on class I fusion proteins to fuse viral and cellular membranes. To drive the fusion process, class I fusion proteins undergo an irreversible conformational change from a metastable prefusion state to an energetically more favorable and stable postfusion state. An increasing amount of evidence exists highlighting that antibodies targeting the prefusion conformation are the most potent. However, many mutations have to be evaluated before identifying prefusion-stabilizing substitutions. We therefore established a computational design protocol that stabilizes the prefusion state while destabilizing the postfusion conformation. As a proof of concept, we applied this principle to the fusion protein of the RSV, hMPV, and SARS-CoV-2 viruses. For each protein, we tested less than a handful of designs to identify stable versions. Solved structures of designed proteins from the three different viruses evidenced the atomic accuracy of our approach. Furthermore, the immunological response of the RSV F design compared to a current clinical candidate in a mouse model. While the parallel design of two conformations allows identifying and selectively modifying energetically less optimized positions for one conformation, our protocol also reveals diverse molecular strategies for stabilization. We recaptured many approaches previously introduced manually for the stabilization of viral surface proteins, such as cavity-filling, optimization of polar interactions, as well as postfusion-disruptive strategies. Using our approach, it is possible to focus on the most impacting mutations and potentially preserve the immunogen as closely as possible to its native version. The latter is important as sequence re-design can cause perturbations to B and T cell epitopes. 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.
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.


A general computational design strategy for stabilizing viral class I fusion proteins.,Gonzalez KJ, Huang J, Criado MF, Banerjee A, Tompkins S, Mousa JJ, Strauch EM bioRxiv. 2023 Mar 17:2023.03.16.532924. doi: 10.1101/2023.03.16.532924. Preprint. PMID:36993551<ref>PMID:36993551</ref>
A general computational design strategy for stabilizing viral class I fusion proteins.,Gonzalez KJ, Huang J, Criado MF, Banerjee A, Tompkins SM, Mousa JJ, Strauch EM Nat Commun. 2024 Feb 13;15(1):1335. doi: 10.1038/s41467-024-45480-z. PMID:38351001<ref>PMID:38351001</ref>


From MEDLINE&reg;/PubMed&reg;, a database of the U.S. National Library of Medicine.<br>
From MEDLINE&reg;/PubMed&reg;, a database of the U.S. National Library of Medicine.<br>
</div>
</div>
<div class="pdbe-citations 8fez" style="background-color:#fffaf0;"></div>
<div class="pdbe-citations 8fez" style="background-color:#fffaf0;"></div>
==See Also==
*[[Spike protein 3D structures|Spike protein 3D structures]]
== References ==
== References ==
<references/>
<references/>

Latest revision as of 09:51, 24 July 2024

Prefusion-stabilized SARS-CoV-2 spike proteinPrefusion-stabilized SARS-CoV-2 spike protein

Structural highlights

8fez is a 3 chain structure with sequence from Severe acute respiratory syndrome coronavirus 2. Full crystallographic information is available from OCA. For a guided tour on the structure components use FirstGlance.
Method:Electron Microscopy, Resolution 3.72Å
Resources:FirstGlance, OCA, PDBe, RCSB, PDBsum, ProSAT

Function

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][1] [2] [3] 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]

Publication Abstract from PubMed

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.

A general computational design strategy for stabilizing viral class I fusion proteins.,Gonzalez KJ, Huang J, Criado MF, Banerjee A, Tompkins SM, Mousa JJ, Strauch EM Nat Commun. 2024 Feb 13;15(1):1335. doi: 10.1038/s41467-024-45480-z. PMID:38351001[4]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

See Also

References

  1. Wrapp D, Wang N, Corbett KS, Goldsmith JA, Hsieh CL, Abiona O, Graham BS, McLellan JS. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science. 2020 Feb 19. pii: science.abb2507. doi: 10.1126/science.abb2507. PMID:32075877 doi:http://dx.doi.org/10.1126/science.abb2507
  2. Hoffmann M, Kleine-Weber H, Schroeder S, Kruger N, Herrler T, Erichsen S, Schiergens TS, Herrler G, Wu NH, Nitsche A, Muller MA, Drosten C, Pohlmann S. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor. Cell. 2020 Apr 16;181(2):271-280.e8. doi: 10.1016/j.cell.2020.02.052. Epub 2020, Mar 5. PMID:32142651 doi:http://dx.doi.org/10.1016/j.cell.2020.02.052
  3. Walls AC, Park YJ, Tortorici MA, Wall A, McGuire AT, Veesler D. Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein. Cell. 2020 Mar 6. pii: S0092-8674(20)30262-2. doi: 10.1016/j.cell.2020.02.058. PMID:32155444 doi:http://dx.doi.org/10.1016/j.cell.2020.02.058
  4. Gonzalez KJ, Huang J, Criado MF, Banerjee A, Tompkins SM, Mousa JJ, Strauch EM. A general computational design strategy for stabilizing viral class I fusion proteins. Nat Commun. 2024 Feb 13;15(1):1335. PMID:38351001 doi:10.1038/s41467-024-45480-z

8fez, resolution 3.72Å

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