Molecular insights fast-tracked: AI in biosynthetic pathway research.

IF 10.2 1区化学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Natural Product Reports Pub Date : 2025-03-25 DOI:10.1039/d4np00003j

Lijuan Liao, Mengjun Xie, Xiaoshan Zheng, Zhao Zhou, Zixin Deng, Jiangtao Gao

{"title":"Molecular insights fast-tracked: AI in biosynthetic pathway research.","authors":"Lijuan Liao, Mengjun Xie, Xiaoshan Zheng, Zhao Zhou, Zixin Deng, Jiangtao Gao","doi":"10.1039/d4np00003j","DOIUrl":null,"url":null,"abstract":"<p><p>Covering: 2000 to 2025This review explores the potential of artificial intelligence (AI) in addressing challenges and accelerating molecular insights in biosynthetic pathway research, which is crucial for developing bioactive natural products with applications in pharmacology, agriculture, and biotechnology. It provides an overview of various AI techniques relevant to this research field, including machine learning (ML), deep learning (DL), natural language processing, network analysis, and data mining. AI-powered applications across three main areas, namely, pathway discovery and mining, pathway design, and pathway optimization, are discussed, and the benefits and challenges of integrating omics data and AI for enhanced pathway research are also elucidated. This review also addresses the current limitations, future directions, and the importance of synergy between AI and experimental approaches in unlocking rapid advancements in biosynthetic pathway research. The review concludes with an evaluation of AI's current capabilities and future outlook, emphasizing the transformative impact of AI on biosynthetic pathway research and the potential for new opportunities in the discovery and optimization of bioactive natural products.</p>","PeriodicalId":94,"journal":{"name":"Natural Product Reports","volume":" ","pages":""},"PeriodicalIF":10.2000,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Natural Product Reports","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1039/d4np00003j","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Covering: 2000 to 2025This review explores the potential of artificial intelligence (AI) in addressing challenges and accelerating molecular insights in biosynthetic pathway research, which is crucial for developing bioactive natural products with applications in pharmacology, agriculture, and biotechnology. It provides an overview of various AI techniques relevant to this research field, including machine learning (ML), deep learning (DL), natural language processing, network analysis, and data mining. AI-powered applications across three main areas, namely, pathway discovery and mining, pathway design, and pathway optimization, are discussed, and the benefits and challenges of integrating omics data and AI for enhanced pathway research are also elucidated. This review also addresses the current limitations, future directions, and the importance of synergy between AI and experimental approaches in unlocking rapid advancements in biosynthetic pathway research. The review concludes with an evaluation of AI's current capabilities and future outlook, emphasizing the transformative impact of AI on biosynthetic pathway research and the potential for new opportunities in the discovery and optimization of bioactive natural products.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Natural Product Reports 化学-生化与分子生物学

CiteScore

21.20

自引率

3.40%

发文量

127

审稿时长

1.7 months

期刊介绍： Natural Product Reports (NPR) serves as a pivotal critical review journal propelling advancements in all facets of natural products research, encompassing isolation, structural and stereochemical determination, biosynthesis, biological activity, and synthesis. With a broad scope, NPR extends its influence into the wider bioinorganic, bioorganic, and chemical biology communities. Covering areas such as enzymology, nucleic acids, genetics, chemical ecology, carbohydrates, primary and secondary metabolism, and analytical techniques, the journal provides insightful articles focusing on key developments shaping the field, rather than offering exhaustive overviews of all results. NPR encourages authors to infuse their perspectives on developments, trends, and future directions, fostering a dynamic exchange of ideas within the natural products research community.