SynthFormer: Equivariant pharmacophore-based generation of synthesizable molecules for ligand-based drug design

Drug discovery is a complex, resource-intensive process requiring significant time and cost to bring new medicines to patients. Many generative models aim to accelerate drug discovery, but few produce synthetically accessible molecules. Conversely, synthesis-focused models do not leverage the 3D inf...

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書誌詳細

主要な著者:	Zygimantas Jocys, Zhanxing Zhu, Henriette M.G. Willems, Katayoun Farrahi
フォーマット:	Artigo
言語:	Inglês
出版事項:	Elsevier 2026-06-01
シリーズ:	Artificial Intelligence in the Life Sciences
主題:	Drug discovery Generative models Synthesizable molecules Pharmacophore modeling Equivariant neural networks Transformer models
オンライン･アクセス:	http://www.sciencedirect.com/science/article/pii/S2667318525000248
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