Evidence map›Paper›PMID 38572755›Full record

ArticleNucleic acids research2024

ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support.

Li Fu, Shaohua Shi, Jiacai Yi, Ningning Wang, Yuanhang He, Zhenxing Wu, Jinfu Peng, Youchao Deng, Wenxuan Wang, Chengkun Wu and 5 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 468 papers.

0numbers the graph read from it
0cells of the map it votes in
468citing papers in PubMed
–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

468 citing papers in PubMed.

  1. Article
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  7. Structure-based discovery of acridone alkaloids as disruptors of the HEG1-KRIT1 protein-protein interaction in cerebral cavernous malformation signaling.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026
    Article
  8. Article
  9. Article
  10. Article
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  13. Target discovery and drug design in the era of artificial intelligence.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026
    Review
  14. Article
  15. Article
  16. Article
  17. Article
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  20. Article

408 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Li FuXiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.ORCID 0009-0002-1800-757X
Shaohua ShiSchool of Chinese Medicine, Hong Kong Baptist University, Kowloon, Hong Kong SAR, 999077, P.R. China.ORCID 0000-0002-0402-9244
Jiacai YiSchool of Computer Science, National University of Defense Technology, Changsha, Hunan 410073, P.R. China.ORCID 0000-0001-6823-1882
Ningning WangXiangya Hospital of Central South University, Changsha, Hunan 410008, P.R. China.
Yuanhang HeXiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.ORCID 0000-0001-7853-7439
Zhenxing WuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China.
Jinfu PengXiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
Youchao DengXiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
Wenxuan WangXiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
Chengkun WuSchool of Computer Science, National University of Defense Technology, Changsha, Hunan 410073, P.R. China.ORCID 0000-0002-9688-5311
Aiping LyuSchool of Chinese Medicine, Hong Kong Baptist University, Kowloon, Hong Kong SAR, 999077, P.R. China.ORCID 0000-0002-2303-0494
Xiangxiang ZengDepartment of Computer Science, Hunan University, Changsha, Hunan 410082, P.R. China.ORCID 0000-0003-1081-7658
Wentao ZhaoSchool of Computer Science, National University of Defense Technology, Changsha, Hunan 410073, P.R. China.
Tingjun HouCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China.ORCID 0000-0001-7227-2580
Dongsheng CaoXiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.ORCID 0000-0003-3604-3785

Funding

2020 Guangdong Provincial Science and Technology Innovation Strategy Special Fund 2020B1212030006HKBU Strategic Development Fund SDF19-0402-P02Hunan Provincial Science Fund for Distinguished Young Scholars 2021JJ10068National Key Research and Development Program of China 2021YFF1201400National Natural Science Foundation of China 22173118Natural Science Foundation of Hunan Province 2022JJ80104Science and Technology Innovation Program of Hunan Province 2021RC4011
6 · The paper itself

Abstract

ADMETlab 3.0 is the second updated version of the web server that provides a comprehensive and efficient platform for evaluating ADMET-related parameters as well as physicochemical properties and medicinal chemistry characteristics involved in the drug discovery process. This new release addresses the limitations of the previous version and offers broader coverage, improved performance, API functionality, and decision support. For supporting data and endpoints, this version includes 119 features, an increase of 31 compared to the previous version. The updated number of entries is 1.5 times larger than the previous version with over 400 000 entries. ADMETlab 3.0 incorporates a multi-task DMPNN architecture coupled with molecular descriptors, a method that not only guaranteed calculation speed for each endpoint simultaneously, but also achieved a superior performance in terms of accuracy and robustness. In addition, an API has been introduced to meet the growing demand for programmatic access to large amounts of data in ADMETlab 3.0. Moreover, this version includes uncertainty estimates in the prediction results, aiding in the confident selection of candidate compounds for further studies and experiments. ADMETlab 3.0 is publicly for access without the need for registration at: https://admetlab3.scbdd.com.

Indexed as

Drug DiscoveryInternetSoftwareHumansPharmaceutical PreparationsPharmaceutical Preparations

Identifiers

PMID38572755
PMCPMC11223840

What OpenQuestion holds

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LicenceCC BY-NC
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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.