Discovery of Hybrid Chemical Synthesis Pathways with DORAnet

  • Quan Zhang
  • , William Sprague
  • , Shivani Kozarekar
  • , Stefan Pate
  • , Taylor Uekert
  • , Linda Broadbelt

Research output: Contribution to journalArticlepeer-review

1 Scopus Citations

Abstract

Developing efficient tools for discovering novel synthesis pathways is essential to advance chemical production methods that maximize the use of resources and energy. We introduce DORAnet (Designing Optimal Reaction Avenues Network Enumeration Tool), an open-source computational framework that addresses key limitations in current computer-aided synthesis planning (CASP) tools. DORAnet integrates both chemical/chemocatalytic (i.e., non-enzymatic) and enzymatic transformations, enabling the discovery of hybrid synthesis pathways. With 390 expert-curated chemical/chemocatalytic reaction rules and 3606 enzymatic rules derived from MetaCyc, it provides extensive flexibility for synthetic chemists and biotechnologists. The framework features customizable network expansion strategies, advanced filtering, and pathway search, ranking, and visualization tools. Validated against known reaction data, DORAnet successfully identified both established and novel synthesis routes for key industrial chemicals. In a case study involving 51 high-volume targets, DORAnet frequently ranked known commercial pathways among the top three results, demonstrating its practical relevance and ranking accuracy, while also uncovering numerous alternative (hybrid) synthesis pathways that were highly ranked.
Original languageAmerican English
Pages (from-to)3109-3125
Number of pages17
JournalDigital Discovery
Volume4
Issue number11
DOIs
StatePublished - 2025

NLR Publication Number

  • NLR/JA-6A20-95088

Keywords

  • chemical discovery
  • computational chemistry

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