{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:QH66CIWV5T3PSSPVUOBOD3UBEE","short_pith_number":"pith:QH66CIWV","schema_version":"1.0","canonical_sha256":"81fde122d5ecf6f949f5a382e1ee812120fbd5ba8d554b061c36e5fa82dacb96","source":{"kind":"arxiv","id":"2507.03318","version":2},"attestation_state":"computed","paper":{"title":"Structure-Aware Compound-Protein Affinity Prediction via Graph Neural Network with Group Lasso Regularization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Jie Zhang, Kun Huang, Pathum Weerawarna, Timothy Richardson, Yang Wang, Yijie Wang, Zanyu Shi","submitted_at":"2025-07-04T06:12:18Z","abstract_excerpt":"Explainable artificial intelligence (XAI) approaches have been increasingly applied in drug discovery to learn molecular representations and identify substructures driving property predictions. However, building end-to-end explainable models for structure-activity relationship (SAR) modeling for compound property prediction faces many challenges, such as the limited number of compound-protein interaction activity data for specific protein targets, and plenty of subtle changes in molecular configuration sites significantly affecting molecular properties. We exploit pairs of molecules with activ"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2507.03318","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-04T06:12:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ac5f7f2d90a7d73b3c1c3d3887df942e274eb2d60647b544e3c416e29a92e3ab","abstract_canon_sha256":"cd0aad52ec61fe9373d2b6e1a928a5b4cf9f052f0ad11b134258b5fcf9046dc2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T01:04:35.396186Z","signature_b64":"lRoRnR5JNHrmEbmCp80PXpB8ngjuCRpXtvWCDY0ePXAIpDctHIFL+kyRkXbrjnsLEoeTbAwsR6Z21hMnDGeBAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"81fde122d5ecf6f949f5a382e1ee812120fbd5ba8d554b061c36e5fa82dacb96","last_reissued_at":"2026-05-29T01:04:35.395682Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T01:04:35.395682Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Structure-Aware Compound-Protein Affinity Prediction via Graph Neural Network with Group Lasso Regularization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Jie Zhang, Kun Huang, Pathum Weerawarna, Timothy Richardson, Yang Wang, Yijie Wang, Zanyu Shi","submitted_at":"2025-07-04T06:12:18Z","abstract_excerpt":"Explainable artificial intelligence (XAI) approaches have been increasingly applied in drug discovery to learn molecular representations and identify substructures driving property predictions. However, building end-to-end explainable models for structure-activity relationship (SAR) modeling for compound property prediction faces many challenges, such as the limited number of compound-protein interaction activity data for specific protein targets, and plenty of subtle changes in molecular configuration sites significantly affecting molecular properties. We exploit pairs of molecules with activ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.03318","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.03318/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2507.03318","created_at":"2026-05-29T01:04:35.395739+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.03318v2","created_at":"2026-05-29T01:04:35.395739+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.03318","created_at":"2026-05-29T01:04:35.395739+00:00"},{"alias_kind":"pith_short_12","alias_value":"QH66CIWV5T3P","created_at":"2026-05-29T01:04:35.395739+00:00"},{"alias_kind":"pith_short_16","alias_value":"QH66CIWV5T3PSSPV","created_at":"2026-05-29T01:04:35.395739+00:00"},{"alias_kind":"pith_short_8","alias_value":"QH66CIWV","created_at":"2026-05-29T01:04:35.395739+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE","json":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE.json","graph_json":"https://pith.science/api/pith-number/QH66CIWV5T3PSSPVUOBOD3UBEE/graph.json","events_json":"https://pith.science/api/pith-number/QH66CIWV5T3PSSPVUOBOD3UBEE/events.json","paper":"https://pith.science/paper/QH66CIWV"},"agent_actions":{"view_html":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE","download_json":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE.json","view_paper":"https://pith.science/paper/QH66CIWV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.03318&json=true","fetch_graph":"https://pith.science/api/pith-number/QH66CIWV5T3PSSPVUOBOD3UBEE/graph.json","fetch_events":"https://pith.science/api/pith-number/QH66CIWV5T3PSSPVUOBOD3UBEE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE/action/storage_attestation","attest_author":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE/action/author_attestation","sign_citation":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE/action/citation_signature","submit_replication":"https://pith.science/pith/QH66CIWV5T3PSSPVUOBOD3UBEE/action/replication_record"}},"created_at":"2026-05-29T01:04:35.395739+00:00","updated_at":"2026-05-29T01:04:35.395739+00:00"}