SARS-CoV-2 Orf3a Protein Interaction Mapping Using Unnatural Amino Acid Incorporation
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ID: 326815
2026
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Abstract
Mapping transient protein-protein interactions remain a major challenge in studying viral host-pathogen interfaces. While some virus-host interactions are stable and readily captured, the majority are highly dynamic, reflecting the need for a small number of viral proteins to engage distinct host factors at different stages of the life cycle. Here, we employ a protein engineering strategy based on the site-specific incorporation of the non-canonical amino acid p-azido-L-phenylalanine (AzF) to enable photo-crosslinking proteomic analysis of the SARS-CoV-2 accessory protein Orf3a in live cells. Genetic installation of AzF at residue K198 of Orf3a permitted UV-induced covalent capture of proximal host interacting proteins, overcoming challenges associated with membrane localization and limited protein abundance. A total of 248 high-confidence Orf3a-interacting proteins were reproducibly identified and subjected to gene ontology analysis, revealing enrichment in innate immune signaling, antiviral defense, RNA processing, and viral replication-associated pathways. Orf3a is an accessory protein that functions as a viroporin and traffics across multiple cellular compartments, and was found to interact with host RNA helicases, RNA-binding proteins, immune regulators, and metabolic enzymes implicated in SARS-CoV-2 infection. Together, these results demonstrate that genetically encoded, site-specific photo-crosslinking enables selective capture of transient interactions that are often missed by nonspecific 254nm UV crosslinking approaches and highlights Orf3a as a multifunctional protein that engages diverse host pathways. More broadly, this study establishes a generalizable framework for leveraging non-canonical amino acid-based protein engineering approaches to interrogate dynamic host-pathogen interactions.
| Reference Key |
openalex_W7204484331
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| Authors | Eryn Lundrigan, Noreen Ahmed, John Paul Pezacki |
| Journal | Protein Engineering Design and Selection |
| Year | 2026 |
| DOI |
10.1093/protein/gzag024
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| URL | |
| Keywords | Keywords not found |
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