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RPSubAlign: a novel sequence-based molecular representation method for retrosynthesis prediction with improved

Yuting Hu1, Feng Hu1, Hongwen Zhang1

  • 1Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Xuhui District, Shanghai 200237, China.

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|June 8, 2025
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Summary

RPSubAlign enhances retrosynthesis predictions by aligning molecular substructures, improving accuracy and validity for complex molecule synthesis in drug discovery. This novel method offers a more robust approach than traditional techniques.

Keywords:
computer-aided synthesis planningdeep learningmolecular representation

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Area of Science:

  • Organic Chemistry
  • Computational Chemistry
  • Drug Discovery

Background:

  • Retrosynthetic route planning is crucial for synthesizing complex molecules, particularly in drug discovery.
  • Sequence-based models are predominant but limited by molecular representation challenges.
  • Current methods often ignore crucial structural relationships between reactants and products.

Purpose of the Study:

  • Introduce RPSubAlign, a novel molecular sequence representation method for retrosynthesis.
  • Enhance the validity and robustness of sequence-based models in predicting synthetic routes.
  • Improve the accuracy of retrosynthetic predictions by aligning common substructures.

Main Methods:

  • Developed RPSubAlign, a method aligning common substructures between reactants and products.
  • Evaluated RPSubAlign on USPTO-50K and USPTO-MIT datasets.
  • Compared RPSubAlign with conventional random and root-alignment representations.

Main Results:

  • RPSubAlign improved Top-N accuracy by up to 34.8% (with Self-Referencing Embedded Strings).
  • Achieved significantly higher syntactic validity: 86.64% on USPTO-50K and 96.45% on USPTO-MIT (with Simplified Molecular Input Line Entry System).
  • Demonstrated enhanced stability across data augmentation scenarios, outperforming baseline methods.

Conclusions:

  • RPSubAlign is a robust and effective molecular characterization method for retrosynthesis.
  • The substructure alignment approach significantly enhances sequence-based model performance.
  • RPSubAlign offers a promising advancement for computational drug discovery and organic synthesis.