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.

计算机辅助方法在反合成分析中作为有价值的工具出现。我们介绍了Retro-BLEU，这是一个从机器翻译中建立的BLEU分数中改编而来的统计指标，用于评估基于反应模板序列分析的反合成路径的可信度。我们通过将Retro-BLEU应用于由最先进的算法生成的不同种类的反合成路径，并与其他评估指标进行比较来证明Retro-BLEU的有效性。结果表明Retro-BLEU能够区分可信的和不可信的路径。此外，我们对Retro-BLEU的优点和缺点提供了见解，为该领域的未来发展和改进铺平了道路。

Retro-BLEU: 通过反应模板序列分析量化合成途径的化学合理性