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Algorithm for the Pruning of Synthesis Graphs.

Gergely Zahoránszky-Kőhalmi1, Nikita Lysov1, Ilia Vorontcov1

  • 1National Center for Advancing Translational Sciences, Rockville, Maryland 20850, United States.

Journal of Chemical Information and Modeling
|April 19, 2022
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Summary
This summary is machine-generated.

A new algorithm, Synthesis Graph Pruning (SGP), efficiently removes undesirable substances from chemical synthesis graphs. This enhances computer-aided synthesis planning for autonomous chemistry platforms.

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Area of Science:

  • Computational Chemistry
  • Chemical Synthesis
  • Artificial Intelligence in Chemistry

Background:

  • Synthesis route planning is crucial for autonomous chemistry.
  • Current methods struggle to modify synthesis graphs based on constraints like undesirable substances.
  • Pruning synthesis graphs with specific constraints remains an open challenge.

Purpose of the Study:

  • To introduce a novel algorithm for pruning synthesis graphs.
  • To address the challenge of eliminating undesirable substances from synthesis pathways.

Main Methods:

  • Developed the Synthesis Graph Pruning (SGP) algorithm.
  • Input: synthesis graph and a set of undesirable substances with inventory metadata.
  • Algorithm utilizes a simple, local rule set for node and edge elimination.

Main Results:

  • The SGP algorithm effectively prunes synthesis graphs.
  • Demonstrated algorithm operation through several case studies.
  • Successfully removes specified undesirable substances from theoretical synthesis pathways.

Conclusions:

  • The SGP algorithm provides a robust solution for synthesis graph modification.
  • This algorithm is expected to be a key component in computer-aided synthesis planning.
  • Facilitates the development of more refined and constraint-aware autonomous chemistry platforms.