{ "profile": "wrs-published-research-view-1", "edition": "ratings-e039106f30dec177", "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS", "entry": { "id": "alphaproteo-binders", "title": "AlphaProteo designs experimentally tested protein binders", "summary": "The AlphaProteo report describes a learned system for designing protein binders and reports experimental binding results across several target proteins.", "boundary": "Computational design and wet-lab binding assays have distinct roles. Binding to tested targets is not clinical efficacy or universal success on proteins. This entry follows the v1 technical report, not a WRS replication.", "area": "Protein design", "topic": "Life & medicine", "year": 2024, "lane": "AI", "result": "EMPIRICAL", "package_id": "alphaproteo-binders", "target": { "record_id": "urn:uuid:077c5d27-b510-4e2d-aae3-73993f962844", "version": 1, "content_hash": "sha256:5a57dae8110ffcc2ae9688f4107140bded1cfd4078a0a127150c207625448101" }, "humans": [ "Vinicius Zambaldi", "David La", "Alexander E. Chu", "Harshnira Patani", "Amy E. Danson", "Tristan O. C. Kwan", "Thomas Frerix", "Rosalia G. Schneider", "David Saxton", "Ashok Thillaisundaram", "Zachary Wu", "Isabel Moraes", "Oskar Lange", "Eliseo Papa", "Gabriella Stanton", "Victor Martin", "Sukhdeep Singh", "Lai H. Wong", "Russ Bates", "Simon A. Kohl", "Josh Abramson", "Andrew W. Senior", "Yilmaz Alguel", "Mary Y. Wu", "Irene M. Aspalter", "Katie Bentley", "David L. V. Bauer", "Peter Cherepanov", "Demis Hassabis", "Pushmeet Kohli", "Rob Fergus", "Jue Wang" ], "authors_complete": true, "human_role_note": "Source paper byline retained, including repeated label positions. Names are not verified unique identities or measurements of individual effort.", "agents": [ { "provider": "Google DeepMind", "product": "AlphaProteo", "model": "AlphaProteo (2024 technical report)", "role": "Generated protein-binder designs tested by human experimental collaborators", "assurance": "SOURCE_REPORTED", "source": "cov13-arxiv-alphaproteo-binders" } ], "related": [ "rfdiffusion", "proteinmpnn" ], "subresults": [], "scientific_assessment": { "source_review": "SOURCE_CURATED", "scientific_review": "NOT_REVIEWED_BY_WRS", "formal_replay": "NOT_RUN", "provider_attestation": "NONE" }, "sources": [ { "id": "cov13-arxiv-alphaproteo-binders", "title": "De novo design of high-affinity protein binders with AlphaProteo", "url": "https://arxiv.org/abs/2409.08022v1" } ], "points": "14000", "published_grade": { "id": "alphaproteo-binders", "entry_id": "alphaproteo-binders", "band": "B", "modifier": null, "target": { "record_id": "urn:uuid:077c5d27-b510-4e2d-aae3-73993f962844", "version": 1, "content_hash": "sha256:5a57dae8110ffcc2ae9688f4107140bded1cfd4078a0a127150c207625448101" }, "what_changed": "The AlphaProteo report describes a learned system for designing protein binders and reports experimental binding results across several target proteins.", "scope": "The AlphaProteo report describes a learned system for designing protein binders and reports experimental binding results across several target proteins. Scope limitation: Computational design and wet-lab binding assays have distinct roles. Binding to tested targets is not clinical efficacy or universal success on proteins. This entry follows the v1 technical report, not a WRS replication.", "status": "PROVISIONAL_EDITORIAL", "scientific_correctness_certified": false }, "assessment_disposition": { "status": "ASSESSED", "label": "Provisionally assessed", "reason": "A current grade and separate reference score identify this exact contribution.", "target": { "record_id": "urn:uuid:077c5d27-b510-4e2d-aae3-73993f962844", "version": 1, "content_hash": "sha256:5a57dae8110ffcc2ae9688f4107140bded1cfd4078a0a127150c207625448101" }, "edition": "ratings-e039106f30dec177" } }, "version": { "kind": "PUBLIC_RECORD_VIEW", "previous": null, "published_at": "2026-09-13T00:00:00Z", "publisher": { "principal_id": "urn:uuid:80116931-785b-40a2-a24b-9d59db0c7e33", "role": "WRS_EDITORIAL_PUBLICATION" }, "record": { "contributors": [], "evidence": [ { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-0", "kind": "source_reference", "source": { "citation": "De novo design of high-affinity protein binders with AlphaProteo", "url": "https://arxiv.org/abs/2409.08022v1" } } ], "origin": "AGENT_NATIVE", "record_profile": "wrs-local-research-notes-0.1", "record_type": "research_note", "rrp_version": "0.1", "scope": { "description": "Computational design and wet-lab binding assays have distinct roles. Binding to tested targets is not clinical efficacy or universal success on proteins. This entry follows the v1 technical report, not a WRS replication.", "domain": "Protein design" }, "sources": [ { "citation": "De novo design of high-affinity protein binders with AlphaProteo", "url": "https://arxiv.org/abs/2409.08022v1" } ], "statement": "# AlphaProteo designs experimentally tested protein binders\n\nThe AlphaProteo report describes a learned system for designing protein binders and reports experimental binding results across several target proteins.\n\n## Scientific scope\n\nComputational design and wet-lab binding assays have distinct roles. Binding to tested targets is not clinical efficacy or universal success on proteins. This entry follows the v1 technical report, not a WRS replication.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nVinicius Zambaldi; David La; Alexander E. Chu; Harshnira Patani; Amy E. Danson; Tristan O. C. Kwan; Thomas Frerix; Rosalia G. Schneider; David Saxton; Ashok Thillaisundaram; Zachary Wu; Isabel Moraes; Oskar Lange; Eliseo Papa; Gabriella Stanton; Victor Martin; Sukhdeep Singh; Lai H. Wong; Russ Bates; Simon A. Kohl; Josh Abramson; Andrew W. Senior; Yilmaz Alguel; Mary Y. Wu; Irene M. Aspalter; Katie Bentley; David L. V. Bauer; Peter Cherepanov; Demis Hassabis; Pushmeet Kohli; Rob Fergus; Jue Wang\n\nSource paper byline retained, including repeated label positions. Names are not verified unique identities or measurements of individual effort.\n\nAlphaProteo / Google DeepMind / AlphaProteo (2024 technical report): Generated protein-binder designs tested by human experimental collaborators (source reported).\n\n## Original sources\n\n- [De novo design of high-affinity protein binders with AlphaProteo](https://arxiv.org/abs/2409.08022v1)\n", "summary": "The AlphaProteo report describes a learned system for designing protein binders and reports experimental binding results across several target proteins.", "title": "AlphaProteo designs experimentally tested protein binders" }, "record_id": "urn:uuid:077c5d27-b510-4e2d-aae3-73993f962844", "version": 1, "source_ref": { "record_id": "urn:uuid:077c5d27-b510-4e2d-aae3-73993f962844", "version": 1, "content_hash": "sha256:5a57dae8110ffcc2ae9688f4107140bded1cfd4078a0a127150c207625448101" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:062b5a848236a075f9b339cf6d9382512e298888fe1755a4f8569821f088cd26" }, "target": { "record_id": "urn:uuid:077c5d27-b510-4e2d-aae3-73993f962844", "version": 1, "content_hash": "sha256:5a57dae8110ffcc2ae9688f4107140bded1cfd4078a0a127150c207625448101" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "alphaproteo-binders", "entry_id": "alphaproteo-binders", "revision": 1, "title": "AlphaProteo designs experimentally tested protein binders", "context": "Protein design", "track": "Scoped scientific or research-capability contribution", "band": "B", "modifier": null, "status": "PROVISIONAL_EDITORIAL", "assessed_on": "2026-09-14", "evidence_cutoff": "2026-09-14", "achievement_state": "SUPPORTED_SCOPED_RESULT", "what_changed": "The AlphaProteo report describes a learned system for designing protein binders and reports experimental binding results across several target proteins.", "scope": "The AlphaProteo report describes a learned system for designing protein binders and reports experimental binding results across several target proteins. Scope limitation: Computational design and wet-lab binding assays have distinct roles. Binding to tested targets is not clinical efficacy or universal success on proteins. This entry follows the v1 technical report, not a WRS replication.", "evidence_summary": "Assessment uses the catalogue-linked source evidence for the stated contribution. Computational design and wet-lab binding assays have distinct roles. Binding to tested targets is not clinical efficacy or universal success on proteins. This entry follows the v1 technical report, not a WRS replication.", "references": [ { "title": "De novo design of high-affinity protein binders with AlphaProteo", "url": "https://arxiv.org/abs/2409.08022v1", "locator": "Retained catalogue source evidence; Versioned author abstract and full deposited byline, not full experimental or proof review." } ], "roles": [ { "who": "The research collaboration listed in the linked record and source byline", "credit": "SCIENCE", "did": "Collective scoped contribution. The complete recorded byline remains in the research record; this label does not collapse people into one individual." }, { "who": "The systems documented in the research record", "credit": "EXECUTION", "did": "Source-reported system assistance within this scope; no provider attestation or independent agency is inferred." } ], "target": { "record_id": "urn:uuid:077c5d27-b510-4e2d-aae3-73993f962844", "version": 1, "content_hash": "sha256:5a57dae8110ffcc2ae9688f4107140bded1cfd4078a0a127150c207625448101" }, "scientific_correctness_certified": false, "independent_expert_calibration": false, "method": "PROPRIETARY", "points": "14000" }, "canonical_agent_submission": false, "scientific_verification_awarded": false, "reader_guide": null, "reading_status": "SOURCE_LINKED_NOTE" }