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Retro-BLEU: Quantifying Chemical Plausibility of Retrosynthesis Routes through Reaction Template Sequence Analysis

8 Nov 2023arXiv:2311.06304archive 2025-07-28

Junren Li, Lei Fang, Jian-Guang Lou

Computer-assisted methods have emerged as valuable tools for retrosynthesis analysis. However, quantifying the plausibility of generated retrosynthesis routes remains a challenging task. We introduce Retro-BLEU, a statistical metric adapted from the well-established BLEU score in machine translation, to evaluate the plausibility of retrosynthesis routes based on reaction template sequences analysis. We demonstrate the effectiveness of Retro-BLEU by applying it to a diverse set of retrosynthesis routes generated by state-of-the-art algorithms and compare the performance with other evaluation metrics. The results show that Retro-BLEU is capable of differentiating between plausible and implausible routes. Furthermore, we provide insights into the strengths and weaknesses of Retro-BLEU, paving the way for future developments and improvements in this field.

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extract_mol_set catalystforyou/retro-bleu/preprocess/single_step.py official repository ran no licence file found · pointer only · 10689258f4befa51 · report
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extract_rxns catalystforyou/retro-bleu/BLEU_utils.py official repository ran no licence file found · pointer only · fb643f2990ee8e06 · report
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Machine TranslationRetrosynthesis

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