Mass spectral database-based methodologies for the annotation and discovery of natural products.
10.1016/S1875-5364(25)60852-1
- Author:
Fengyao YANG
1
;
Zeyuan LIANG
1
;
Haoran ZHAO
1
;
Jiayi ZHENG
1
;
Lifang LIU
1
;
Huipeng SONG
2
,
3
;
Guizhong XIN
4
Author Information
1. State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
2. College of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian 116600, China. Electronic address: songhuipeng15@
3. com.
4. State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China. Electronic address: xingz@cpu.edu.cn.
- Publication Type:Review
- Keywords:
Annotation;
Databases;
Mass spectrometry;
Natural products
- MeSH:
Biological Products/chemistry*;
Mass Spectrometry/methods*;
Databases, Factual;
Drug Discovery/methods*;
Humans
- From:
Chinese Journal of Natural Medicines (English Ed.)
2025;23(4):410-420
- CountryChina
- Language:English
-
Abstract:
Natural products (NPs) have long held a significant position in various fields such as medicine, food, agriculture, and materials. The chemical space covered by NPs is extensive but often underexplored. Therefore, high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems. Mass spectrometry (MS) has emerged as a powerful platform for the annotation and discovery of NPs. MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information. Additionally, the released annotation methodologies, based on a variety of informatics tools, continuously improve the ability to annotate the structure and properties of compounds. This review examines the current mainstream databases and annotation methodologies, focusing on their advantages and limitations. Prospects for future technological advancements are then discussed in terms of novel applications and research objectives. Through a systematic overview, this review aims to provide valuable insights and a reference for MS-based NPs annotation, thereby promoting the discovery of novel natural entities.
