Evidence map›Paper›PMID 29651663›Full record

ArticleJournal of cheminformatics2018

Finding the molecular scaffold of nuclear receptor inhibitors through high-throughput screening based on proteochemometric modelling.

Tianyi Qiu, Dingfeng Wu, Jingxuan Qiu, Zhiwei Cao

Open access · goldAbstract read
In one paragraph

Article in Journal of cheminformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Tianyi QiuSchool of Life Sciences and Technology, Shanghai 10th People's Hospital, Tongji University, No. 1239 SiPing Road, Shanghai, China.ORCID http://orcid.org/0000-0003-2619-0298
Dingfeng WuSchool of Life Sciences and Technology, Shanghai 10th People's Hospital, Tongji University, No. 1239 SiPing Road, Shanghai, China.
Jingxuan QiuSchool of Life Sciences and Technology, Shanghai 10th People's Hospital, Tongji University, No. 1239 SiPing Road, Shanghai, China.
Zhiwei CaoSchool of Life Sciences and Technology, Shanghai 10th People's Hospital, Tongji University, No. 1239 SiPing Road, Shanghai, China. zwcao@tongji.edu.cn.
Tongji University · CN

Funding

China Postdoctoral Science Foundation Funded Project 2017M611451National Postdoctoral Program for Innovative Talents BX201600033
6 · The paper itself

Abstract

Nuclear receptors (NR) are a class of proteins that are responsible for sensing steroid and thyroid hormones and certain other molecules. In that case, NR have the ability to regulate the expression of specific genes and associated with various diseases, which make it essential drug targets. Approaches which can predict the inhibition ability of compounds for different NR target should be particularly helpful for drug development. In this study, proteochemometric modelling was introduced to analysis the bioactivity between chemical compounds and NR targets. Results illustrated the ability of our PCM model for high-throughput NR-inhibitor screening after evaluated on both internal (AUC > 0.870) and external (AUC > 0.746) validation set. Moreover, in-silico predicted bioactive compounds were clustered according to structure similarity and a series of representative molecular scaffolds can be derived for five major NR targets. Through scaffolds analysis, those essential bioactive scaffolds of different NR target can be detected and compared. Generally, the methods and molecular scaffolds proposed in this article can not only help the screening of potential therapeutic NR-inhibitors but also able to guide the future NR-related drug discovery.

Indexed as

CheminformaticsMolecular scaffoldNuclear receptorProteochemometric modelling

Identifiers

PMID29651663
PMCPMC5897275
OpenAlexW2798950799

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.