{"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/a-3d-molecule-generative-model-for-structure","title":"A 3D Generative Model for Structure-Based Drug Design","arxiv_id":"2203.10446","date":"2022-03-20","proceeding":"NeurIPS 2021 12","authors":["Shitong Luo","Jiaqi Guan","Jianzhu Ma","Jian Peng"],"abstract":"We study a fundamental problem in structure-based drug design -- generating molecules that bind to specific protein binding sites. While we have witnessed the great success of deep generative models in drug design, the existing methods are mostly string-based or graph-based. They are limited by the lack of spatial information and thus unable to be applied to structure-based design tasks. Particularly, such models have no or little knowledge of how molecules interact with their target proteins exactly in 3D space. In this paper, we propose a 3D generative model that generates molecules given a designated 3D protein binding site. Specifically, given a binding site as the 3D context, our model estimates the probability density of atom's occurrences in 3D space -- positions that are more likely to have atoms will be assigned higher probability. To generate 3D molecules, we propose an auto-regressive sampling scheme -- atoms are sampled sequentially from the learned distribution until there is no room for new atoms. Combined with this sampling scheme, our model can generate valid and diverse molecules, which could be applicable to various structure-based molecular design tasks such as molecule sampling and linker design. Experimental results demonstrate that molecules sampled from our model exhibit high binding affinity to specific targets and good drug properties such as drug-likeness even if the model is not explicitly optimized for them.","url_abs":"https://arxiv.org/abs/2203.10446v2","url_pdf":"https://arxiv.org/pdf/2203.10446v2.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":"a-3d-molecule-generative-model-for-structure","repo_url":"https://github.com/luost26/3d-generative-sbdd","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"a-3d-molecule-generative-model-for-structure","repo_url":"https://github.com/guanjq/targetdiff","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"a-3d-molecule-generative-model-for-structure","repo_url":"https://github.com/pengxingang/pocket2mol","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"a-3d-molecule-generative-model-for-structure","repo_url":"https://github.com/yanliang3612/nucleusdiff","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"drug-design","task_name":"Drug Design"},{"task_slug":null,"task_name":"valid"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2203.10446","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.10446"}},"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/guanjq/targetdiff","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/pengxingang/pocket2mol","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/luost26/3d-generative-sbdd","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/yanliang3612/nucleusdiff","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran_draft_wrong":4},"by_repo_kind":{"official":{"samples":4,"ran":4,"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":0,"samples":[{"code_sha256_prefix":"b45191024f7c9733","entry":"concat_tensors_to_batch","repo":"luost26/3d-generative-sbdd","repo_kind":"official","path":"models/sample.py","file_url":"https://github.com/luost26/3d-generative-sbdd/blob/HEAD/models/sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b45191024f7c9733"}},{"code_sha256_prefix":"468257593ef53102","entry":"random_roll_back","repo":"luost26/3d-generative-sbdd","repo_kind":"official","path":"sample.py","file_url":"https://github.com/luost26/3d-generative-sbdd/blob/HEAD/sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"468257593ef53102"}},{"code_sha256_prefix":"41162e2f12e0b028","entry":"sample_init","repo":"luost26/3d-generative-sbdd","repo_kind":"official","path":"models/sample.py","file_url":"https://github.com/luost26/3d-generative-sbdd/blob/HEAD/models/sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"41162e2f12e0b028"}},{"code_sha256_prefix":"c8e6ed243dd0c66b","entry":"split_tensor_by_batch","repo":"luost26/3d-generative-sbdd","repo_kind":"official","path":"models/sample.py","file_url":"https://github.com/luost26/3d-generative-sbdd/blob/HEAD/models/sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c8e6ed243dd0c66b"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}