Natural product databases for drug discovery: Features and applications

Abstract

Natural products (NPs) exhibit diverse chemical structures and biological activities that make them valuable sources for drug discovery. With advancements in computational technology, computation-enabled natural drug discovery is gaining increasing significance, with NP databases playing a pivotal role. In light of this, we first summarize the key features of NP databases, including structural data, property annotations, biological sources, biosynthetic pathways, and web interfaces. Subsequently, the wide applications of these databases in drug discovery, such as virtual screening, knowledge graph construction, and molecular generation, are reviewed. We further discuss the puzzle of database development, focusing on data quality and updating. Finally, we emphasize the pivotal role of team collaboration and toolkit innovation in harnessing the immense potential of NP-related databases to accelerate bioactivity mining, structure modification, and manufacturing. This review aims to elucidate the key features and applications of NP databases, with the goal of aiding researchers in developing and maintaining high-quality NP databases for drug discovery.

Keywords

Natural products / Database / Drug discovery / Cheminformatics / Computer-aided drug design

Data availability

Not applicable.

Ethics approval

Not applicable.

Funding information

This work was supported by the National Key Research and Development Program of China (2023YFC3404900) and the Key Area Research and Development Program of Guangdong Province, China (2022B1111080005). We also thank the Top-Notch Young Talents Program of China for its support.

CRediT authorship contribution statement

Tao Zeng: Writing - original draft, Resources, Methodology. Jiahao Li: Resources. Ruibo Wu: Writing - review & editing, Supervision, Project administration, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

Not applicable.

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