In-silico 3D molecular editing through physics-informed and preference-aligned generative foundation models
Abstract Generating molecular structures towards desired properties is a critical task in computer-aided drug and material design. As special 3D entities, molecules inherit non-trivial physical complexity, and many intrinsic properties may not be learnable through pure data-driven approaches, hinder...
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| Auteurs principaux: | , , , , , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Nature Portfolio
2025-07-01
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| Collection: | Nature Communications |
| Accès en ligne: | https://doi.org/10.1038/s41467-025-61323-x |
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