View in EDS

FLOWR: flow matching for structure-aware de novo, interaction- and fragment-based ligand generation.

Saved in:
Bibliographic Details
Title: FLOWR: flow matching for structure-aware de novo, interaction- and fragment-based ligand generation.
Authors: Cremer J; Machine Learning and Computational Sciences, Pfizer Worldwide R&D, Berlin, Germany. julian.cremer@pfizer.com., Irwin R; Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden. rossir@chalmers.se.; Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden. rossir@chalmers.se., Tibo A; Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden., Janet JP; Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden., Olsson S; Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden., Clevert DA; Machine Learning and Computational Sciences, Pfizer Worldwide R&D, Berlin, Germany.
Source: Nature computational science [Nat Comput Sci] 2026 Jun; Vol. 6 (6), pp. 565-574. Date of Electronic Publication: 2026 May 28.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: United States NLM ID: 101775476 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2662-8457 (Electronic) Linking ISSN: 26628457 NLM ISO Abbreviation: Nat Comput Sci Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2662-8457
DOI:10.1038/s43588-026-00998-8