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Updated: Jan 12, 2026

Mass Spectrometry-Guided Genome Mining as a Tool to Uncover Novel Natural Products
Published on: March 12, 2020
AI and mechanistic modeling for characterizing biosynthetic pathways of natural products
Byung Tae Lee1, Byeongsub Lee2, Joon Young Kwon1
1Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea. ehukim@kaist.ac.kr.
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.
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