Evidence map›Paper›PMID 41550147›Full record

ReviewPharmaceutical science advances2024

Natural product databases for drug discovery: Features and applications.

Tao Zeng, Jiahao Li, Ruibo Wu

Erratum issuedAbstract readReview
In one paragraph

Review in Pharmaceutical science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Special Issue "Antiviral Drugs Discovery".International journal of molecular sciences · 2026
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  5. Article
  6. Review
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  15. Special Issue "Natural Products as Multitarget Agents in Human Diseases".International journal of molecular sciences · 2026
    Article
  16. Review
  17. Article
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  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Tao ZengSchool of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, PR China.
Jiahao LiSchool of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, PR China.
Ruibo WuSchool of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

CheminformaticsComputer-aided drug designDatabaseDrug discoveryNatural products

Identifiers

PMID41550147
PMCPMC12709921

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.