Evidence map›Paper›PMID 24035675›Full record

ReviewTrends in pharmacological sciences2013

Computational methods for drug design and discovery: focus on China.

Mingyue Zheng, Xian Liu, Yuan Xu, Honglin Li, Cheng Luo, Hualiang Jiang

Abstract readReview
In one paragraph

Review in Trends in pharmacological sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

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  2. Review
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  19. Article
  20. Computer-Aided Drug Design in Epigenetics.Frontiers in chemistry · 2018
    Review
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

6 authors.

Mingyue ZhengDrug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.
Xian Liu
Yuan Xu
Honglin Li
Cheng Luo
Hualiang Jiang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past decades, China's computational drug design and discovery research has experienced fast development through various novel methodologies. Application of these methods spans a wide range, from drug target identification to hit discovery and lead optimization. In this review, we firstly provide an overview of China's status in this field and briefly analyze the possible reasons for this rapid advancement. The methodology development is then outlined. For each selected method, a short background precedes an assessment of the method with respect to the needs of drug discovery, and, in particular, work from China is highlighted. Furthermore, several successful applications of these methods are illustrated. Finally, we conclude with a discussion of current major challenges and future directions of the field.

Indexed as

Drug DesignChinaComputational BiologyDrug Delivery SystemsDrug DiscoveryHumansModels, MolecularPharmacology

Identifiers

PMID24035675
PMCPMC7126378

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.