{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T20:01:56Z","timestamp":1776369716853,"version":"3.51.2"},"posted":{"date-parts":[[2025,3,14]]},"group-title":"Biophysics","reference-count":46,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T00:00:00Z","timestamp":1741910400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,3,14]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                <jats:p>\n                  Viral antigen-antibody (Ag-Ab) interactions shape immune responses, drive pathogen neutralization, and inform vaccine strategies. Understanding their structural basis is crucial for predicting immune recognition, optimizing immunogen design to induce broadly neutralizing antibodies (bnAbs), and developing antiviral therapeutics. However, curated structural benchmarks for viral Ag-Ab interactions remain scarce. To address this, we present\n                  <jats:bold>VASCO<\/jats:bold>\n                  (Viral Antibody-antigen Structural COmplex dataset), a high-resolution, non-redundant collection of \u223c1225 viral Ag-Ab complexes sourced from the Protein Data Bank (PDB) and refined via energy minimization. Spanning Coronaviruses, Influenza, Ebola, HIV, and others, VASCO provides a comprehensive structural reference for viral immune recognition. By comparing VASCO against general protein-protein interactions (GPPI), we identify distinct sequence and structural features that define viral Ag-Ab binding. While conventional descriptors show broad similarities across datasets, deeper analyses reveal key sequence-space interactions, secondary structure preferences, and manifold-derived latent features that distinguish viral complexes. These insights highlight the limitations of GPPI-trained predictive models and the need for specialized computational frameworks. VASCO serves as a critical resource for advancing viral immunology, improving predictive modeling, and guiding immunogen design to elicit protective antibody responses. By bridging sequence and structural immunological datasets, VASCO should enable better docking, affinity prediction, and antiviral therapeutic development\u2014key to pandemic preparedness and emerging pathogen response.\n                <\/jats:p>","DOI":"10.1101\/2025.03.11.642737","type":"posted-content","created":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T12:20:18Z","timestamp":1741954818000},"source":"Crossref","is-referenced-by-count":1,"title":["Unveiling Interaction Signatures Across Viral Pathogens through VASCO: Viral Antigen-Antibody Structural COmplex dataset"],"prefix":"10.64898","author":[{"given":"Kenny","family":"Wong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ishaan","family":"Subramanian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emma","family":"Stevens","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7155-2764","authenticated-orcid":false,"given":"Srirupa","family":"Chakraborty","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2025031911484412000_2025.03.11.642737v1.1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-41769-7_19"},{"key":"2025031911484412000_2025.03.11.642737v1.2","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-022-01582-x"},{"key":"2025031911484412000_2025.03.11.642737v1.3","doi-asserted-by":"publisher","DOI":"10.1042\/BCJ20180670"},{"key":"2025031911484412000_2025.03.11.642737v1.4","doi-asserted-by":"crossref","unstructured":"Stanfield, R.L. and I.A. 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