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Forward Reaction Prediction as Reverse Verification: A Novel Approach to Retrosynthesis
ChemRxiv Pub Date : 2020-10-27
Ling Wang, Chengyun Zhang, Renren Bai, Jianjun Li, Hongliang Duan

Pupils' intuitive knowledge can lead them to verify multiplication by means of division. Based on this analogy, this study introduces the basic reverse verification concept to verify retrosynthesis through forward reaction. In this work, we present a "combined" model approach for retrosynthetic reaction prediction, where the first model is applied to retrosynthesis, and the second model, which is a "verified" model, is applied to the forward reaction prediction to verify the top-n reactants predicted by the retrosynthetic model. Using a "combined" model borrowed from human language translation, sequence-to-sequence (seq2seq) + transformer models, we improve the top-1 accuracy of retrosynthetic prediction by 4.3% (37.4% vs 41.7%). The application of the similarity + seq2seq models increases the top-1 accuracy by 4.6% (52.9% vs 57.5%). In this way, we can not only improve the accuracy but also automate the evaluation of the synthetic route.

中文翻译:

正向反应预测作为反向验证:一种新型的逆合成方法

学生的直觉知识可以引导他们通过除法验证乘法。在这种类比的基础上,本研究引入了基本的反向验证概念,以通过正向反应验证逆向合成。在这项工作中,我们提出了一种用于逆向合成反应预测的“组合”模型方法,其中将第一个模型应用于逆向合成,将第二个模型(即“已验证”模型)应用于正向反应预测以验证顶部-n反应物由逆合成模型预测。使用从人类语言翻译中借用的“组合”模型,序列到序列(seq2seq)+转换模型,我们将逆合成预测的top-1准确性提高了4.3%(37.4%对41.7%)。相似度+ seq2seq模型的应用使top-1准确性提高了4。6%(52.9%比57.5%)。这样,我们不仅可以提高准确性,而且可以自动评估合成路线。
更新日期:2020-10-28
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