{"data":{"event":{"id":"04df1d5a-0819-4173-8134-3e022dce6fbd","slug":"structure-based-antibody-renumbering-83325c57fb","title":"\n\nStructure-based Antibody Renumbering \n\n","short_summary":"Antibody numbering schemes like IMGT and Chothia assign each residue in the variable domain a consistent index based on substructural position. These annotations standardize sequences with different lengths, facilitating tasks ranging from engineering of individual molecules during drug development to large-scale curation of training data for de novo antibody design. Yet existing algorithms for performing this annotation process, termed renumbering, rely exclusively on amino acid sequence for inference. Consequently, these can fail when presented with unnatural or unusual features such as long","full_description":"Antibody numbering schemes like IMGT and Chothia assign each residue in the variable domain a consistent index based on substructural position. These annotations standardize sequences with different lengths, facilitating tasks ranging from engineering of individual molecules during drug development to large-scale curation of training data for de novo antibody design. Yet existing algorithms for performing this annotation process, termed renumbering, rely exclusively on amino acid sequence for inference. Consequently, these can fail when presented with unnatural or unusual features such as long CDRs or engineered insertions. To address this gap, this work introduces Structure-based Antibody Renumbering, abbreviated SAbR, a method that assigns these annotations from structure alone. SAbR shows comparable performance to sequence-based renumbering methods on held-out expert-annotated structures, as well as high agreement with sequence-based methods in a larger benchmark of diverse structures. It also outperforms peer methods on de novo-designed molecules, and shows higher success rates than renumbering by structural alignment. However, limited generalization performance is observed in more distantly related systems. Overall, these results establish structure-based renumbering as a robust alternative for natural and engineered antibodies when such data is available. Code and model weights are available on GitHub.\n\nUpdate (2026-09-24): \n\nZika virus sequence and secondary structure analysis using VADR \n\n. Zika virus is a mosquito-borne flavivirus that caused a major epidemic in the Americas in 2015 and 2016 and is associated with congenital birth defects and neurological disease. Like other flaviviruses, it depends on conserved sequence and RNA structural elements that carry out essential steps in its life cycle and in evading host immune defenses. Public sequence databases and annotation tools give free access to Zika sequence data, but comparable structural information is sparse. We built a computational model of Zika sequence and secondary structure for use with the VADR software package, which validates and annotates Zika sequences for GenBank submission and assigns each sequence to a genetic lineage following a published classification scheme. On a test set of 1254 Zika sequences, 97.2% passed validation, and the model's annotations agreed with those of an existing annotation tool (VIGOR4) for 99.3% of the sequences compared. We also extended VADR to draw secondary structure diagrams of each sequence's structural elements in its linear and circular conformations using R2DT, and we submi","ledger_type":"benefit","primary_domain_id":"8f1af1b9-7302-4b51-aae9-fdfac04d158a","event_status":"provisional","event_date":"2026-09-20T00:00:00.000Z","discovery_date":"2026-09-20T00:00:00.000Z","first_published_date":"2026-09-20T00:00:00.000Z","last_reviewed_date":"2026-09-24T00:00:00.000Z","geographic_scope":"International","affected_population":null,"base_impact_tier":1,"base_score":"1.00","attribution_multiplier":"0.7500","evidence_multiplier":"0.4500","realization_multiplier":"0.4000","durability_multiplier":"0.5000","current_event_score":"0.067500","confidence_level":"low","score_explanation":"Ingest update: independent source raised evidence; added a follow-up source. Score remains provisional until review.","methodology_version_id":"8745541b-0f8e-4d5a-9b47-5291d3813a8d","original_methodology_version_id":"8745541b-0f8e-4d5a-9b47-5291d3813a8d","published_at":"2026-09-21T04:01:13.229Z","created_at":"2026-09-21T04:01:13.229Z","updated_at":"2026-09-24T16:01:01.689Z","flags":[],"domain_name":"Biology","domain_slug":"biology","methodology_version":"0.2"},"contributions":[{"id":"308ff459-d25b-420c-ae9a-984d078e1eae","event_id":"04df1d5a-0819-4173-8134-3e022dce6fbd","model_id":"535014f7-c941-4d39-aa9b-8f9c1d3d07b7","role_description":"Unspecified system mentioned or implied by a news item. Remap to a named release when identified.","attribution_multiplier":"0.7500","credit_share":"1.0000","contribution_score":"0.067500","attribution_rationale":"News ingest does not infer a named model from the publisher alone. Attribution stays unspecified until a release is identified.","attribution_confidence":"medium","first_used_date":"2026-09-20T00:00:00.000Z","model_version_if_known":null,"review_status":"approved","created_at":"2026-09-21T04:01:13.240Z","model_slug":"unspecified-ai-system","model_name":"Unspecified AI system","identity_class":"unknown","is_internal":false,"family_name":"Unspecified","family_slug":"unknown-unspecified","organization_name":"Unknown","organization_slug":"unknown"}],"sources":[{"id":"e4a32825-435b-46da-9041-f03ee580dda9","event_id":"04df1d5a-0819-4173-8134-3e022dce6fbd","url":"\nhttps://www.biorxiv.org/content/10.64898/2026.09.16.751788v1?rss=1\n","canonical_url":"\nhttps://www.biorxiv.org/content/10.64898/2026.09.16.751788v1?rss=1\n","source_type":"preprint","publisher":"bioRxiv","author":null,"publication_date":"2026-09-20T00:00:00.000Z","retrieved_at":"2026-09-21T04:01:13.247Z","title":"\n\nStructure-based Antibody Renumbering \n\n","excerpt":"Antibody numbering schemes like IMGT and Chothia assign each residue in the variable domain a consistent index based on substructural position. These annotations standardize sequences with different lengths, facilitating tasks ranging from engineering of individual molecules during drug development to large-scale curation of training data for de novo antibody design. Yet existing algorithms for performing this annotation process, termed renumbering, rely exclusively on amino acid sequence for in","content_hash":null,"source_reliability_class":"medium","is_primary_source":true,"is_independent":true,"is_peer_reviewed":false,"archived_url":null,"created_at":"2026-09-21T04:01:13.247Z"},{"id":"bcf1cc5d-6c1c-474d-a6e6-135830272a2b","event_id":"04df1d5a-0819-4173-8134-3e022dce6fbd","url":"\nhttps://www.biorxiv.org/content/10.64898/2026.09.21.753218v1?rss=1\n","canonical_url":"\nhttps://www.biorxiv.org/content/10.64898/2026.09.21.753218v1?rss=1\n","source_type":"preprint","publisher":"bioRxiv","author":null,"publication_date":"2026-09-24T00:00:00.000Z","retrieved_at":"2026-09-24T16:01:01.673Z","title":"\n\nZika virus sequence and secondary structure analysis using VADR \n\n","excerpt":"Zika virus is a mosquito-borne flavivirus that caused a major epidemic in the Americas in 2015 and 2016 and is associated with congenital birth defects and neurological disease. Like other flaviviruses, it depends on conserved sequence and RNA structural elements that carry out essential steps in its life cycle and in evading host immune defenses. Public sequence databases and annotation tools give free access to Zika sequence data, but comparable structural information is sparse. We built a com","content_hash":null,"source_reliability_class":"medium","is_primary_source":false,"is_independent":false,"is_peer_reviewed":false,"archived_url":null,"created_at":"2026-09-24T16:01:01.673Z"}],"claims":[{"id":"164b84f8-d5ab-49e0-8e9c-d42049ce29fb","event_id":"04df1d5a-0819-4173-8134-3e022dce6fbd","claim_text":"\n\nStructure-based Antibody Renumbering \n\n","claim_type":"outcome","claim_status":"supported","confidence_score":null,"created_at":"2026-09-21T04:01:13.252Z","updated_at":"2026-09-21T04:01:13.252Z"}],"revisions":[{"id":"36fb3c10-50a4-42a3-bb32-e8c87c48b88e","event_id":"04df1d5a-0819-4173-8134-3e022dce6fbd","model_id":null,"previous_score":"0.000000","new_score":"0.052500","previous_factors":{},"new_factors":{"tier":1,"evidence":0.35,"base_score":1,"durability":0.5,"attribution":0.75,"realization":0.4},"change_reason":"Auto-published from news ingest.","trigger_type":"news_ingest","trigger_source_ids":null,"reviewer_id":null,"review_status":"published","created_at":"2026-09-21T04:01:13.259Z"},{"id":"3fb892dd-db04-42e2-9365-0c7240ccc93e","event_id":"04df1d5a-0819-4173-8134-3e022dce6fbd","model_id":null,"previous_score":"0.052500","new_score":"0.067500","previous_factors":{"tier":1,"evidence":0.35,"base_score":1,"durability":0.5,"attribution":0.75,"realization":0.4},"new_factors":{"tier":1,"models":["535014f7-c941-4d39-aa9b-8f9c1d3d07b7"],"evidence":0.45,"base_score":1,"durability":0.5,"attribution":0.75,"realization":0.4},"change_reason":"Ingest update: independent source raised evidence; added a follow-up source.","trigger_type":"ingest_update","trigger_source_ids":["bcf1cc5d-6c1c-474d-a6e6-135830272a2b"],"reviewer_id":null,"review_status":"published","created_at":"2026-09-24T16:01:01.732Z"}],"secondary":[]},"methodology_version":"0.1"}