{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T15:59:10Z","timestamp":1789401550793,"version":"build-2803163510"},"reference-count":69,"publisher":"National Academy of Sciences","issue":"11","license":[{"start":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T00:00:00Z","timestamp":1773273600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012543","name":"Shanghai Science and Technology Development Foundation","doi-asserted-by":"publisher","award":["24JS2850200 25DX2800400"],"award-info":[{"award-number":["24JS2850200 25DX2800400"]}],"id":[{"id":"10.13039\/100012543","id-type":"DOI","asserted-by":"publisher"}]},{"name":"ShanghaiTech AI4S Initiative","award":["SHTAI4S202404"],"award-info":[{"award-number":["SHTAI4S202404"]}]},{"DOI":"10.13039\/501100012166","name":"MOST | National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFC3400501 2022YFC3400500"],"award-info":[{"award-number":["2022YFC3400501 2022YFC3400500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Program of Shanxi Province","award":["202503021212159"],"award-info":[{"award-number":["202503021212159"]}]}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2026,3,17]]},"abstract":"<jats:p>Targeted protein degradation is a promising strategy for drug discovery, but designing effective PROTACs remains challenging, especially for proteins without well-defined binding sites. Current methods rely on modifying linkers between fixed ligands, which limits the diversity and innovation of the overall molecular architecture of PROTAC. Here, we introduce DeepDegradome, an AI-powered method that automates the structure-aware design of both small-molecule ligands and PROTACs. It employs a large fragment library constructed from public databases and applies an in-house docking method (iFitDock) to obtain initial binding fragments. DeepDegradome builds ligands by assembling these fragments based on the shape and physicochemical features of the target protein pocket. It can further construct PROTACs from these generated ligands, eliminating the dependency on predefined warheads or E3 ligands. Compared to other AI models, DeepDegradome produces more valid, drug-like molecules with higher predicted binding affinity. We demonstrate DeepDegradome\u2019s effectiveness by designing and validating multiple potency inhibitors and PROTACs for two protein targets: WDR5 and CDK9. One synthesized compound showed excellent agreement between predicted and actual binding conformation confirmed by X-ray crystallography. By combining ligand and PROTAC design in one system, DeepDegradome offers a scalable and reliable tool for discovering new drugs against protein targets.<\/jats:p>","DOI":"10.1073\/pnas.2518248123","type":"journal-article","created":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T16:56:41Z","timestamp":1773334601000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":7,"title":["DeepDegradome: A structure-aware deep learning framework for PROTAC and ligand generation against protein targets"],"prefix":"10.1073","volume":"123","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9834-5153","authenticated-orcid":false,"given":"Qiaoyu","family":"Hu","sequence":"first","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Cao","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Life Science and Technology, ShanghaiTech University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"PengXuan","family":"Ren","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Pharmacy, Shanxi Medical University","place":["Taiyuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianglei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fenglei","family":"Li","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Information Science and Technology, ShanghaiTech University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Life Science and Technology, ShanghaiTech University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengyu","family":"Cai","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Information Science and Technology, ShanghaiTech University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ran","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Life Science and Technology, ShanghaiTech University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongqi","family":"Zhou","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Life Science and Technology, ShanghaiTech University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9874-0397","authenticated-orcid":false,"given":"Lianghe","family":"Mei","sequence":"additional","affiliation":[{"name":"Suzhou Institute of Materia Medica, Chinese Academy of Sciences","place":["Suzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1468-5568","authenticated-orcid":false,"given":"Fang","family":"Bai","sequence":"additional","affiliation":[{"name":"Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Life Science and Technology, ShanghaiTech University","place":["Shanghai, China"]},{"name":"School of Information Science and Technology, ShanghaiTech University","place":["Shanghai, China"]},{"name":"Shanghai Clinical Research and Trial Center","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2026,3,12]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41573-021-00371-6"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.chembiol.2021.04.011"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41392-022-00966-4"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.37349\/etat.2020.00018"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1098-1128(199601)16:1<3::AID-MED1>3.0.CO;2-6"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1359-6446(04)03275-1"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.274.5292.1531"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrd2220"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1021\/jm0103920"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature03579"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.3389\/fmolb.2020.00180"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1021\/bi3005126"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1038\/nprot.2013.130"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1021\/jm040031v"},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1080\/17460441.2019.1583643"},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2019.12.006"},{"key":"e_1_3_4_17_2","doi-asserted-by":"publisher","DOI":"10.1038\/nprot.2008.197"},{"key":"e_1_3_4_18_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03819-2"},{"key":"e_1_3_4_19_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07487-w"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1002\/jmr.2471"},{"key":"e_1_3_4_21_2","doi-asserted-by":"publisher","DOI":"10.2174\/157340911795677602"},{"key":"e_1_3_4_22_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrd1549"},{"key":"e_1_3_4_23_2","doi-asserted-by":"publisher","DOI":"10.1021\/acscentsci.7b00572"},{"key":"e_1_3_4_24_2","doi-asserted-by":"crossref","unstructured":"C. Ma X. Zhang \u201cGF-VAE: A flow-based variational autoencoder for molecule generation\u201d in CIKM (2021) pp. 1181\u20131190 10.1145\/3459637.3482260.","DOI":"10.1145\/3459637.3482260"},{"key":"e_1_3_4_25_2","article-title":"All SMILES variational autoencoder","author":"Alperstein Z.","year":"2019","unstructured":"Z. Alperstein, A. Cherkasov, J. T. Rolfe, All SMILES variational autoencoder. NeurIPS (2019).","journal-title":"NeurIPS"},{"key":"e_1_3_4_26_2","doi-asserted-by":"publisher","DOI":"10.1002\/minf.202100102"},{"key":"e_1_3_4_27_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.1c00600"},{"key":"e_1_3_4_28_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-79682-4"},{"key":"e_1_3_4_29_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.9b01120"},{"key":"e_1_3_4_30_2","doi-asserted-by":"publisher","DOI":"10.1039\/D1SC02436A"},{"key":"e_1_3_4_31_2","article-title":"Fragment-based ligand generation guided by geometric deep learning on protein-ligand structure","author":"Powers A. S.","year":"2022","unstructured":"A. S. Powers, H. H. Yu, P. Suriana, R. O. Dror, Fragment-based ligand generation guided by geometric deep learning on protein-ligand structure. bioRxiv (2022), 10.1101\/2022.03.17.484653.","journal-title":"bioRxiv"},{"key":"e_1_3_4_32_2","doi-asserted-by":"publisher","DOI":"10.3390\/biom12060746"},{"key":"e_1_3_4_33_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-39904-5"},{"key":"e_1_3_4_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.chembiol.2023.06.002"},{"key":"e_1_3_4_35_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-34807-3"},{"key":"e_1_3_4_36_2","doi-asserted-by":"publisher","DOI":"10.1002\/cmdc.200800178"},{"key":"e_1_3_4_37_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.5b00559"},{"key":"e_1_3_4_38_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gky1075"},{"key":"e_1_3_4_39_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.accounts.6b00491"},{"key":"e_1_3_4_40_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1359-6446(03)02831-9"},{"key":"e_1_3_4_41_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrd3926-c1"},{"key":"e_1_3_4_42_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1615932113"},{"key":"e_1_3_4_43_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1301814110"},{"key":"e_1_3_4_44_2","unstructured":"M. Ghorbani L. Gendelev P. Beroza M. J. Keiser Autoregressive fragment-based diffusion for pocket-aware ligand design. arXiv [Preprint] (2023) https:\/\/doi.org\/10.48550\/arXiv.2401.05370 (Accessed 15 December 2023)."},{"key":"e_1_3_4_45_2","first-page":"41382","volume-title":"Proc. of the 40th International Conference on Machine Learning","author":"Zhang Z.","year":"2023","unstructured":"Z. Zhang, Q. Liu, \u201cLearning subpocket prototypes for generalizable structure-based drug design\u201d. in Proc. of the 40th International Conference on Machine Learning (PMLR, 2023), pp. 41382\u201341398."},{"key":"e_1_3_4_46_2","first-page":"17644","volume-title":"Proc. of the 39th International Conference on Machine Learning","author":"Peng X.","year":"2022","unstructured":"X. Peng , \u201cPocket2Mol: Efficient molecular sampling based on 3D protein pockets\u201d in Proc. of the 39th International Conference on Machine Learning (PMLR, 2022), pp. 17644\u201317655."},{"key":"e_1_3_4_47_2","volume-title":"International Conference on Learning Representations","author":"Guan J.","year":"2023","unstructured":"J. Guan , \u201c3D equivariant diffusion for target-aware molecule generation and affinity prediction\u201d in International Conference on Learning Representations (ICLR, 2023)."},{"key":"e_1_3_4_48_2","doi-asserted-by":"publisher","DOI":"10.1038\/nsmb0709-678"},{"key":"e_1_3_4_49_2","doi-asserted-by":"publisher","DOI":"10.1093\/emboj\/20.24.7137"},{"key":"e_1_3_4_50_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrd.2017.179"},{"key":"e_1_3_4_51_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2016.05.063"},{"key":"e_1_3_4_52_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0124964"},{"key":"e_1_3_4_53_2","doi-asserted-by":"publisher","DOI":"10.1038\/srep08293"},{"key":"e_1_3_4_54_2","doi-asserted-by":"publisher","DOI":"10.1002\/jcb.26491"},{"key":"e_1_3_4_55_2","doi-asserted-by":"publisher","DOI":"10.1074\/jbc.M806317200"},{"key":"e_1_3_4_56_2","doi-asserted-by":"publisher","DOI":"10.1074\/jbc.M112.364125"},{"key":"e_1_3_4_57_2","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-15-0423"},{"key":"e_1_3_4_58_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1910391116"},{"key":"e_1_3_4_59_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.molcel.2015.02.028"},{"key":"e_1_3_4_60_2","doi-asserted-by":"publisher","DOI":"10.1517\/17460441.2015.1032936"},{"key":"e_1_3_4_61_2","doi-asserted-by":"publisher","DOI":"10.1038\/nchembio.1859"},{"key":"e_1_3_4_62_2","doi-asserted-by":"publisher","DOI":"10.1074\/jbc.M200117200"},{"key":"e_1_3_4_63_2","doi-asserted-by":"publisher","DOI":"10.1074\/jbc.274.49.34527"},{"key":"e_1_3_4_64_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41388-023-02892-3"},{"key":"e_1_3_4_65_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.pharmthera.2017.02.008"},{"key":"e_1_3_4_66_2","doi-asserted-by":"publisher","DOI":"10.1021\/jm030580l"},{"key":"e_1_3_4_67_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkm911"},{"key":"e_1_3_4_68_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.0c00411"},{"key":"e_1_3_4_69_2","unstructured":"Q. Hu . Data from \u201cDeepDegradome: A structure-aware deep learning framework for PROTAC and ligand generation against protein targets.\u201d GitHub. https:\/\/github.com\/QiaoyuHu89\/DeepDegradome. Deposited 1 March 2025."}],"container-title":["Proceedings of the National Academy of Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pnas.org\/doi\/pdf\/10.1073\/pnas.2518248123","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T16:57:17Z","timestamp":1773334637000},"score":1,"resource":{"primary":{"URL":"https:\/\/pnas.org\/doi\/10.1073\/pnas.2518248123"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,12]]},"references-count":69,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2026,3,17]]}},"alternative-id":["10.1073\/pnas.2518248123"],"URL":"https:\/\/doi.org\/10.1073\/pnas.2518248123","relation":{},"ISSN":["0027-8424","1091-6490"],"issn-type":[{"value":"0027-8424","type":"print"},{"value":"1091-6490","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,12]]},"assertion":[{"value":"2025-07-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-11","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-03-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e2518248123"}}