{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/diffbind-a-se-3-equivariant-network-for","title":"DiffBindFR: An SE(3) Equivariant Network for Flexible Protein-Ligand Docking","arxiv_id":"2311.15201","date":"2023-11-26","proceeding":null,"authors":["Jintao Zhu","Zhonghui Gu","Jianfeng Pei","Luhua Lai"],"abstract":"Molecular docking, a key technique in structure-based drug design, plays pivotal roles in protein-ligand interaction modeling, hit identification and optimization, in which accurate prediction of protein-ligand binding mode is essential. Conventional docking approaches perform well in redocking tasks with known protein binding pocket conformation in the complex state. However, in real-world docking scenario without knowing the protein binding conformation for a new ligand, accurately modeling the binding complex structure remains challenging as flexible docking is computationally expensive and inaccurate. Typical deep learning-based docking methods do not explicitly consider protein side chain conformations and fail to ensure the physical plausibility and detailed atomic interactions. In this study, we present DiffBindFR, a full-atom diffusion-based flexible docking model that operates over the product space of ligand overall movements and flexibility and pocket side chain torsion changes. We show that DiffBindFR has higher accuracy in producing native-like binding structures with physically plausible and detailed interactions than available docking methods. Furthermore, in the Apo and AlphaFold2 modeled structures, DiffBindFR demonstrates superior advantages in accurate ligand binding pose and protein binding conformation prediction, making it suitable for Apo and AlphaFold2 structure-based drug design. DiffBindFR provides a powerful flexible docking tool for modeling accurate protein-ligand binding structures.","url_abs":"https://arxiv.org/abs/2311.15201v3","url_pdf":"https://arxiv.org/pdf/2311.15201v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"diffbind-a-se-3-equivariant-network-for","repo_url":"https://github.com/HBioquant/DiffBindFR","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"BSD-3-Clause-Clear"}}],"tasks":[{"task_slug":"drug-design","task_name":"Drug Design"},{"task_slug":"molecular-docking","task_name":"Molecular Docking"},{"task_slug":"pose-prediction","task_name":"Pose Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2311.15201","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.15201"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/HBioquant/DiffBindFR","reach":{"status":"ok","spdx":"BSD-3-Clause-Clear"}}],"summary":{"ran":13,"unverified":2},"by_repo_kind":{"official":{"samples":15,"ran":13,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":15,"samples":[{"code_sha256_prefix":"5aed22b3a33e13ce","entry":"add_center_pos","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/common/inference_dataset.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/common/inference_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"5aed22b3a33e13ce"}},{"code_sha256_prefix":"9f1aef578f0778fc","entry":"angular_difference","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/metrics/angbin.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/metrics/angbin.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"9f1aef578f0778fc"}},{"code_sha256_prefix":"f62c7873515fc861","entry":"base64_decode","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/common/args.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/common/args.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"f62c7873515fc861"}},{"code_sha256_prefix":"91418bd31f876e21","entry":"base64_encode","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/common/args.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/common/args.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"91418bd31f876e21"}},{"code_sha256_prefix":"756aa3698a3f26f5","entry":"expand_font_dim","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/metrics/angbin.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/metrics/angbin.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"756aa3698a3f26f5"}},{"code_sha256_prefix":"3f60a2bf0504e918","entry":"expand_font_fn","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/metrics/angbin.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/metrics/angbin.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"3f60a2bf0504e918"}},{"code_sha256_prefix":"c87f1ecab1e054e0","entry":"get_traj_id","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/evaluation/export.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/evaluation/export.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"c87f1ecab1e054e0"}},{"code_sha256_prefix":"b3142b74300622c0","entry":"input_csv","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/common/dataframe.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/common/dataframe.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"b3142b74300622c0"}},{"code_sha256_prefix":"10003e839c7bd512","entry":"input_object","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/common/dataframe.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/common/dataframe.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"10003e839c7bd512"}},{"code_sha256_prefix":"bdff5e6c328601ff","entry":"make_jobs_tstest","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/evaluation/file_utils.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/evaluation/file_utils.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"bdff5e6c328601ff"}},{"code_sha256_prefix":"fe4a9c5c7b8ef28c","entry":"rmsd_to_str","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/evaluation/export.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/evaluation/export.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"fe4a9c5c7b8ef28c"}},{"code_sha256_prefix":"91de50a80f2cdd89","entry":"single_path","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/common/dataframe.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/common/dataframe.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"91de50a80f2cdd89"}},{"code_sha256_prefix":"20ba4c3dfb4004e4","entry":"split_top1_flex_pdbqt","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/utils/vinafr_remodel.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/utils/vinafr_remodel.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"20ba4c3dfb4004e4"}},{"code_sha256_prefix":"a6525f67ac56091a","entry":"parse_top_flex_pdbqt","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/utils/vinafr_remodel.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/utils/vinafr_remodel.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"a6525f67ac56091a"}},{"code_sha256_prefix":"e6ac03bbafd7ddcd","entry":"report_enrichment","repo":"HBioquant/DiffBindFR","repo_kind":"official","path":"DiffBindFR/evaluation/reporter.py","file_url":"https://github.com/HBioquant/DiffBindFR/blob/HEAD/DiffBindFR/evaluation/reporter.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause-Clear","inline_ok":false,"mcp_get_code":{"code_sha256":"e6ac03bbafd7ddcd"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}