These are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information. For more information, please see our FAQs.
Forward Reaction Prediction as Reverse Verification A Novel Approach to Retrosynthesis.pdf (732.07 kB)

Forward Reaction Prediction as Reverse Verification: A Novel Approach to Retrosynthesis

submitted on 24.10.2020, 02:53 and posted on 27.10.2020, 10:00 by 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.


National Natural Science Foundation of China No.81903438


Email Address of Submitting Author


Zhejiang University of Technology



ORCID For Submitting Author


Declaration of Conflict of Interest

The authors declare no competing financial interest.