{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T02:00:05Z","timestamp":1780538405459,"version":"3.54.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T00:00:00Z","timestamp":1768953600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T00:00:00Z","timestamp":1768953600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100007698","name":"University of Florida","doi-asserted-by":"publisher","award":["AI and complex computational research award"],"award-info":[{"award-number":["AI and complex computational research award"]}],"id":[{"id":"10.13039\/100007698","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007698","name":"University of Florida","doi-asserted-by":"publisher","award":["AI and complex computational research award"],"award-info":[{"award-number":["AI and complex computational research award"]}],"id":[{"id":"10.13039\/100007698","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007698","name":"University of Florida","doi-asserted-by":"publisher","award":["AI and complex computational research award"],"award-info":[{"award-number":["AI and complex computational research award"]}],"id":[{"id":"10.13039\/100007698","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OAC-2311632"],"award-info":[{"award-number":["OAC-2311632"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OAC-2311632"],"award-info":[{"award-number":["OAC-2311632"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OAC-2311632"],"award-info":[{"award-number":["OAC-2311632"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OAC-2311632"],"award-info":[{"award-number":["OAC-2311632"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OAC-2311632"],"award-info":[{"award-number":["OAC-2311632"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OAC-2311632"],"award-info":[{"award-number":["OAC-2311632"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OAC-2311632"],"award-info":[{"award-number":["OAC-2311632"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000893","name":"Simons Foundation","doi-asserted-by":"publisher","award":["839534"],"award-info":[{"award-number":["839534"]}],"id":[{"id":"10.13039\/100000893","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Comput Sci"],"DOI":"10.1038\/s43588-025-00946-y","type":"journal-article","created":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T10:02:43Z","timestamp":1768989763000},"page":"233-242","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["PropMolFlow: property-guided molecule generation with geometry-complete flow matching"],"prefix":"10.1038","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1296-913X","authenticated-orcid":false,"given":"Cheng","family":"Zeng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jirui","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2819-5792","authenticated-orcid":false,"given":"Connor","family":"Ambrose","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George","family":"Karypis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Transtrum","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3311-6299","authenticated-orcid":false,"given":"Ellad B.","family":"Tadmor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4933-7686","authenticated-orcid":false,"given":"Richard G.","family":"Hennig","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrian","family":"Roitberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2028-2175","authenticated-orcid":false,"given":"Stefano","family":"Martiniani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5341-4448","authenticated-orcid":false,"given":"Mingjie","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,21]]},"reference":[{"key":"946_CR1","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1126\/science.aat2663","volume":"361","author":"B Sanchez-Lengeling","year":"2018","unstructured":"Sanchez-Lengeling, B. & Aspuru-Guzik, A. Inverse molecular design using machine learning: generative models for matter engineering. Science 361, 360\u2013365 (2018).","journal-title":"Science"},{"key":"946_CR2","unstructured":"Hoogeboom, E., Satorras, V. G., Vignac, C. & Welling, M. Equivariant diffusion for molecule generation in 3D. Proc.Mach. Learn. Res. 162, 8867\u20138887 (2022)."},{"key":"946_CR3","unstructured":"Satorras, V. G., Hoogeboom, E. & Welling, M. E(n) equivariant graph neural networks. Proc. Mach. Learn. Res. 139, 9323\u20139332 (2021)."},{"key":"946_CR4","unstructured":"Xu, M., Powers, A. S., Dror, R. O., Ermon, S. & Leskovec, J. Geometric latent diffusion models for 3D molecule generation. Proc. Mach. Learn. Res. 202, 38592\u201338610 (2023)."},{"key":"946_CR5","doi-asserted-by":"crossref","unstructured":"Liu, X., Gong, C. & Liu, Q. Flow straight and fast: learning to generate and transfer data with rectified flow. In Eleventh International Conference on Learning Representations (ICLR, 2023); https:\/\/openreview.net\/forum?id=XVjTT1nw5z","DOI":"10.1109\/ICVISP64524.2024.10959352"},{"key":"946_CR6","unstructured":"Lipman, Y., Chen, R. T. Q., Ben-Hamu, H., Nickel, M. & Le, M. Flow matching for generative modeling. In Eleventh International Conference on Learning Representations (ICLR, 2023); https:\/\/openreview.net\/forum?id=PqvMRDCJT9t"},{"key":"946_CR7","unstructured":"Albergo, M. S. & Vanden-Eijnden, E. Building normalizing flows with stochastic interpolants. In Eleventh International Conference on Learning Representations (ICLR, 2023); https:\/\/openreview.net\/forum?id=li7qeBbCR1t"},{"key":"946_CR8","unstructured":"H\u00f6llmer, P. et al. Open materials generation with stochastic interpolants. In International Conference on Machine Learning 23417\u201323450 (PMLR, 2025)."},{"key":"946_CR9","unstructured":"Campbell, A., Yim, J., Barzilay, R., Rainforth, T. & Jaakkola, T. Generative flows on discrete state-spaces: enabling multimodal flows with applications to protein co-design. In International Conference on Machine Learning 5453\u20135512 (PMLR, 2024)."},{"key":"946_CR10","unstructured":"Dunn, I. & Koes, D. R. Exploring discrete flow matching for 3D de novo molecule generation. Preprint at https:\/\/arxiv.org\/abs\/2411.16644 (2024)."},{"key":"946_CR11","first-page":"549","volume":"36","author":"Y Song","year":"2023","unstructured":"Song, Y. et al. Equivariant flow matching with hybrid probability transport for 3D molecule generation. Adv. Neural Inf. Process. Syst. 36, 549\u2013568 (2023).","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"946_CR12","unstructured":"Dumitrescu, A. et al. E(3)-equivariant models cannot learn chirality: field-based molecular generation. In Thirteenth International Conference on Learning Representations (ICLR, 2025); https:\/\/openreview.net\/forum?id=mXHTifc1Fn"},{"key":"946_CR13","doi-asserted-by":"crossref","unstructured":"Vignac, C., Osman, N., Toni, L. & Frossard, P. MiDi: mixed graph and 3D denoising diffusion for molecule generation. In Machine Learning and Knowledge Discovery in Databases: Research Track (eds Koutra, D. et al.) 560\u2013576 (Springer, 2023).","DOI":"10.1007\/978-3-031-43415-0_33"},{"key":"946_CR14","doi-asserted-by":"publisher","DOI":"10.1038\/s42004-024-01233-z","volume":"7","author":"A Morehead","year":"2024","unstructured":"Morehead, A. & Cheng, J. Geometry-complete diffusion for 3D molecule generation and optimization. Commun. Chem. 7, 150 (2024).","journal-title":"Commun. Chem."},{"key":"946_CR15","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2014.22","volume":"1","author":"R Ramakrishnan","year":"2014","unstructured":"Ramakrishnan, R., Dral, P. O., Rupp, M. & Von Lilienfeld, O. A. Quantum chemistry structures and properties of 134 kilo molecules. Sci. Data 1, 140022 (2014).","journal-title":"Sci. Data"},{"key":"946_CR16","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1039\/C7SC02664A","volume":"9","author":"Z Wu","year":"2018","unstructured":"Wu, Z. et al. MoleculeNet: a benchmark for molecular machine learning. Chem. Sci. 9, 513\u2013530 (2018).","journal-title":"Chem. Sci."},{"key":"946_CR17","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-28526-y","volume":"13","author":"NWA Gebauer","year":"2022","unstructured":"Gebauer, N. W. A., Gastegger, M., Hessmann, S. S. P., M\u00fcller, K.-R. & Sch\u00fctt, K. T. Inverse design of 3D molecular structures with conditional generative neural networks. Nat. Commun. 13, 973 (2022).","journal-title":"Nat. Commun."},{"key":"946_CR18","unstructured":"Jing, B., Eismann, S., Suriana, P., Townshend, R. J. L. & Dror, R. Learning from protein structure with geometric vector perceptrons. In International Conference on Learning Representations (ICLR, 2021); https:\/\/openreview.net\/forum?id=1YLJDvSx6J4"},{"key":"946_CR19","unstructured":"Bao, F. et al. Equivariant energy-guided SDE for inverse molecular design. In Eleventh International Conference on Learning Representations (ICLR, 2023); https:\/\/openreview.net\/forum?id=r0otLtOwYW"},{"key":"946_CR20","doi-asserted-by":"publisher","first-page":"11857","DOI":"10.1109\/TNNLS.2024.3416328","volume":"35","author":"H Huang","year":"2024","unstructured":"Huang, H., Sun, L., Du, B. & Lv, W. Learning joint 2-D and 3-D graph diffusion models for complete molecule generation. IEEE Trans. Neural Netw. Learn. Syst. 35, 11857\u201311871 (2024).","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"946_CR21","unstructured":"Landrum, G. et al. RDKit: Open-Source Cheminformatics Software (RDKit, 2016)."},{"key":"946_CR22","doi-asserted-by":"publisher","first-page":"3130","DOI":"10.1039\/D3SC04185A","volume":"15","author":"M Buttenschoen","year":"2024","unstructured":"Buttenschoen, M., Morris, G. M. & Deane, C. M. PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences. Chem. Sci. 15, 3130\u20133139 (2024).","journal-title":"Chem. Sci."},{"key":"946_CR23","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1021\/c160017a018","volume":"5","author":"HL Morgan","year":"1965","unstructured":"Morgan, H. L. The generation of a unique machine description for chemical structures\u2014a technique developed at Chemical Abstracts Service. J. Chem. Doc. 5, 107\u2013113 (1965).","journal-title":"J. Chem. Doc."},{"key":"946_CR24","doi-asserted-by":"publisher","first-page":"D1388","DOI":"10.1093\/nar\/gkaa971","volume":"49","author":"S Kim","year":"2021","unstructured":"Kim, S. et al. PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res. 49, D1388\u2013D1395 (2021).","journal-title":"Nucleic Acids Res."},{"key":"946_CR25","unstructured":"Ho, J. & Salimans, T. Classifier-free diffusion guidance. In NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications (2021); https:\/\/openreview.net\/forum?id=qw8AKxfYbI"},{"key":"946_CR26","doi-asserted-by":"crossref","unstructured":"Karras, T. et al. Guiding a diffusion model with a bad version of itself. Adv. Neural Inf. Process. Syst. 37, 52996\u201353021 (2024).","DOI":"10.52202\/079017-1679"},{"key":"946_CR27","unstructured":"Boffi, N. M., Albergo, M. S. & Vanden-Eijnden, E. How to build a consistency model: learning flow maps via self-distillation. In Thirty-ninth Annual Conference on Neural Information Processing Systems (2025); https:\/\/openreview.net\/forum?id=Di5apl8HSH"},{"key":"946_CR28","unstructured":"Liu, G.-H., Choi, J., Chen, Y., Miller, B. K. & Chen, R. T. Q. Adjoint Schr\u00f6dinger bridge sampler. In Thirty-ninth Annual Conference on Neural Information Processing Systems (2025); https:\/\/openreview.net\/forum?id=rMhQBlhh4c"},{"key":"946_CR29","unstructured":"Dunn, I. & Koes, D. R. FlowMol3: flow matching for 3D de novo small-molecule generation. Preprint at https:\/\/arxiv.org\/abs\/2508.12629 (2025)."},{"key":"946_CR30","unstructured":"Dunn, I. & Koes, D. R. Mixed continuous and categorical flow matching for 3D de novo molecule generation. Preprint at https:\/\/arxiv.org\/abs\/2404.19739 (2024)."},{"key":"946_CR31","doi-asserted-by":"crossref","unstructured":"Gat, I. et al. Discrete flow matching. Adv. Neural Inf. Process. Syst. 37, 133345\u2013133385 (2024).","DOI":"10.52202\/079017-4239"},{"key":"946_CR32","unstructured":"Le, T., Cremer, J., Noe, F., Clevert, D.-A. & Sch\u00fctt, K. T. Navigating the design space of equivariant diffusion-based generative models for de novo 3D molecule generation. In Twelfth International Conference on Learning Representations (ICLR, 2024); https:\/\/openreview.net\/forum?id=kzGuiRXZrQ"},{"key":"946_CR33","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-022-01288-4","volume":"9","author":"S Axelrod","year":"2022","unstructured":"Axelrod, S. & G\u00f3mez-Bombarelli, R. GEOM, energy-annotated molecular conformations for property prediction and molecular generation. Sci. Data 9, 185 (2022).","journal-title":"Sci. Data"},{"key":"946_CR34","doi-asserted-by":"publisher","first-page":"5648","DOI":"10.1063\/1.464913","volume":"98","author":"AD Becke","year":"1993","unstructured":"Becke, A. D. Density-functional thermochemistry. III. The role of exact exchange. J. Chem. Phys. 98, 5648\u20135652 (1993).","journal-title":"J. Chem. Phys."},{"key":"946_CR35","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1103\/PhysRevB.37.785","volume":"37","author":"C Lee","year":"1988","unstructured":"Lee, C., Yang, W. & Parr, R. G. Development of the Colle\u2013Salvetti correlation-energy formula into a functional of the electron density. Phys. Rev. B 37, 785\u2013789 (1988).","journal-title":"Phys. Rev. B"},{"key":"946_CR36","doi-asserted-by":"publisher","unstructured":"Zeng, C., Jin, J. & Liu, M. PropMolFlow: property-guided molecule generation with geometry-complete flow matching. Zenodo https:\/\/doi.org\/10.5281\/zenodo.17726328 (2025).","DOI":"10.5281\/zenodo.17726328"},{"key":"946_CR37","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-35692-6","volume":"14","author":"M Moret","year":"2023","unstructured":"Moret, M. et al. Leveraging molecular structure and bioactivity with chemical language models for de novo drug design. Nat. Commun. 14, 114 (2023).","journal-title":"Nat. Commun."},{"key":"946_CR38","doi-asserted-by":"publisher","DOI":"10.1186\/1758-2946-3-33","volume":"3","author":"NM O\u2019Boyle","year":"2011","unstructured":"O\u2019Boyle, N. M. et al. Open Babel: an open chemical toolbox. J. Cheminform. 3, 33 (2011).","journal-title":"J. Cheminform."},{"key":"946_CR39","unstructured":"Frisch, M. J. et al. Gaussian 16 revision C.01 (2016)."},{"key":"946_CR40","doi-asserted-by":"publisher","unstructured":"Zeng, C., Jin, J. & Mingjie, L. PropMolFlow code. Zenodo https:\/\/doi.org\/10.5281\/zenodo.17702415 (2025).","DOI":"10.5281\/zenodo.17702415"}],"container-title":["Nature Computational Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s43588-025-00946-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s43588-025-00946-y","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s43588-025-00946-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T23:02:39Z","timestamp":1774566159000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s43588-025-00946-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,21]]},"references-count":40,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2026,3]]}},"alternative-id":["946"],"URL":"https:\/\/doi.org\/10.1038\/s43588-025-00946-y","relation":{},"ISSN":["2662-8457"],"issn-type":[{"value":"2662-8457","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,21]]},"assertion":[{"value":"19 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}