Retro-BLEU: quantifying chemical plausibility of retrosynthesis routes through reaction template sequence analysis

• Published in: Digital discovery 2024-03, Vol.3 (3), p.482-49
• Main Authors: Li, Junren, Fang, Lei, Lou, Jian-Guang
• Format: Article
• Language: English
• ISSN: 2635-098X; 2635-098X
• DOI: 10.1039/d3dd00219e

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. Retro-BLEU is a statistical metric to evaluate the plausibility of model-generated retrosynthesis routes based on reaction template sequences analysis.