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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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A general computational design strategy for stabilizing viral class I fusion proteins
Karen J Gonzalez1, Jiachen Huang2,3, Miria F Criado2,4
1Institute of Bioinformatics, Franklin College of Arts and Sciences, University of Georgia; Athens, GA 30602, USA.
Biorxiv : the Preprint Server for Biology
|March 30, 2023
Summary
A new computational protocol stabilizes viral prefusion proteins, crucial for potent antibody responses against viruses like RSV and SARS-CoV-2. This method accelerates vaccine development by efficiently identifying stabilizing mutations.
Area of Science:
- Virology
- Structural Biology
- Immunology
Background:
- Class I fusion proteins mediate viral entry for many pathogens, including influenza, Ebola, coronaviruses, and pneumoviruses.
- These proteins transition from a metastable prefusion state to a stable postfusion state, with prefusion-specific antibodies showing higher potency.
- Identifying mutations that stabilize the prefusion conformation is critical but challenging.
Conclusions:
- The computational protocol efficiently identifies stabilizing mutations for viral fusion proteins, reducing development time and resources for vaccines.
- This method allows for the selective modification of viral immunogens while preserving native epitopes.
- The approach has broad applicability for developing vaccines against viruses utilizing class I fusion proteins.
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