AI RESEARCH
Computational framework for multistep metabolic pathway design
arXiv CS.LG
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ArXi:2604.13471v1 Announce Type: new In silico tools are important for generating novel hypotheses and exploring alternatives in de novo metabolic pathway design. However, while many computational frameworks have been proposed for retrobiosynthesis, few successful examples of algorithm-guided xenobiotic biochemical retrosynthesis have been reported in the literature. Deep learning has improved the quality of synthesis and retrosynthesis in organic chemistry applications.