Evidence map›Paper›PMID 24980533›Full record

ArticleDrug discovery today. Technologies2006

New technologies in computer-aided drug design: Toward target identification and new chemical entity discovery.

Yun Tang, Weiliang Zhu, Kaixian Chen, Hualiang Jiang

Abstract read
In one paragraph

Article in Drug discovery today. Technologies, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. In silico Methods for Identification of Potential Therapeutic Targets.Interdisciplinary sciences, computational life sciences · 2022
    Review
  15. Article
  16. Discovery of potent and noncovalent KRASFrontiers in pharmacology · 2022
    Article
  17. Article
  18. Drug Discovery forInternational journal of molecular sciences · 2021
    Review
  19. Article
  20. Article
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

4 authors.

Yun TangSchool of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.
Weiliang ZhuDrug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.
Kaixian ChenDrug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.
Hualiang JiangDrug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China. Electronic address:hljiang@mail.shcnc.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the postgenomic era, computer-aided drug design (CADD) has considerably extended its range of applications, spanning almost all stages in the drug discovery pipeline, from target identification to lead discovery, from lead optimization to preclinical or clinical trials. Two new technologies of CADD associated with target identification and new chemical entity discovery will be the focus of this review.:

Identifiers

PMID24980533
PMCPMC7185835

What OpenQuestion holds

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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.