AI and mechanistic modeling for characterizing biosynthetic pathways of natural products

  • Byung Tae Lee
  • , Byeongsub Lee
  • , Joon Young Kwon
  • , Tilmann Weber
  • , Hyun Uk Kim

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Covering: 2020 to 2025Natural products are a major source of bioactive compounds, yet elucidating their biosynthetic pathways remains a major challenge due to complex genotype-phenotype relationships. Recent advances in computational approaches, particularly artificial intelligence (AI) and mechanistic modeling, are transforming this field. This highlight examines key databases that underpin computational studies, AI-driven methods for predicting biosynthetic pathways and enzyme-substrate interactions, and mechanistic simulations that provide energetic and structural insights. We also discuss current challenges and future opportunities for integrating these strategies to accelerate discovery, engineering, and application of natural products in drug discovery, biotechnology, and synthetic biology.
Original languageEnglish
JournalNatural Product Reports
ISSN0265-0568
DOIs
Publication statusAccepted/In press - 2026

Fingerprint

Dive into the research topics of 'AI and mechanistic modeling for characterizing biosynthetic pathways of natural products'. Together they form a unique fingerprint.

Cite this