Evidence map›Paper›PMID 36825226›Full record

ReviewFrontiers in chemistry2023

Recent updates in click and computational chemistry for drug discovery and development.

Jiang Hong Cai, Xuan Zhe Zhu, Peng Yue Guo, Peter Rose, Xiao Tong Liu, Xia Liu, Yi Zhun Zhu

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

8 citing papers in PubMed, 15 citations in OpenAlex.

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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

7 authors at 4 institutions in 3 countries.

Jiang Hong CaiState Key Laboratory of Quality Research in Chinese Medicine, School of Pharmacy, Macau University of Science and Technology, Taipa, Macau, China.
Xuan Zhe ZhuState Key Laboratory of Quality Research in Chinese Medicine, School of Pharmacy, Macau University of Science and Technology, Taipa, Macau, China.
Peng Yue GuoDepartment of Clinical Pharmacy, School of Pharmacy, Second Military University, Shanghai, China.
Peter RoseSchool of Biosciences, University of Nottingham, Nottingham, United Kingdom.
Xiao Tong LiuState Key Laboratory of Quality Research in Chinese Medicine, School of Pharmacy, Macau University of Science and Technology, Taipa, Macau, China.
Xia LiuDepartment of Clinical Pharmacy, School of Pharmacy, Second Military University, Shanghai, China.
Yi Zhun ZhuState Key Laboratory of Quality Research in Chinese Medicine, School of Pharmacy, Macau University of Science and Technology, Taipa, Macau, China.
Macau University of Science and Technology · MOSecond Military Medical University · CNFudan University · CNUniversity of Nottingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug discovery is a costly and time-consuming process with a very high failure rate. Recently, click chemistry and computer-aided drug design (CADD) represent popular areas for new drug development. Herein, we summarized the recent updates in click and computational chemistry for drug discovery and development including clicking to effectively synthesize druggable candidates, synthesis and modification of natural products, targeted delivery systems, and computer-aided drug discovery for target identification, seeking out and optimizing lead compounds, ADMET prediction as well as compounds synthesis, hopefully, inspires new ideas for novel drug development in the future.

Indexed as

CADDclick chemistrycomputational chemistrydrug developmentdruggable candidates

Identifiers

PMID36825226
PMCPMC9941707
OpenAlexW4319439065

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.