Evidence map›Paper›PMID 39798999›Full record

ArticleBriefings in bioinformatics2024

PbsNRs: predict the potential binders and scaffolds for nuclear receptors.

Genhui Zheng, Dingfeng Wu, Xiuxia Wei, Dongpo Xu, Tiantian Mao, Deyu Yan, Wenhao Han, Xiaoxiao Shang, Zikun Chen, Jingxuan Qiu and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Genhui ZhengInstitute of Clinical Science, Zhongshan Hospital, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Intelligent Medicine Institute, School of Life Sciences, Fudan University, No. 180 Fenglin Road, Shanghai 200032, China.ORCID 0000-0001-5380-2435
Dingfeng WuNational Center, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, No. 3333 Binsheng Road, Hangzhou 310052, China.
Xiuxia WeiSchool of Health Science and Engineering, University of Shanghai for Science and Technology, No. 516 Jungong Road, Yangpu District, Shanghai 200093, China.
Dongpo XuSchool of Health Science and Engineering, University of Shanghai for Science and Technology, No. 516 Jungong Road, Yangpu District, Shanghai 200093, China.
Tiantian MaoSchool of Life Sciences and Technology, Tongji University, No. 1239 Siping Road, Shanghai 200092, China.
Deyu YanSchool of Life Sciences and Technology, Tongji University, No. 1239 Siping Road, Shanghai 200092, China.
Wenhao HanSchool of Life Sciences and Technology, Tongji University, No. 1239 Siping Road, Shanghai 200092, China.
Xiaoxiao ShangInstitute of Clinical Science, Zhongshan Hospital, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Intelligent Medicine Institute, School of Life Sciences, Fudan University, No. 180 Fenglin Road, Shanghai 200032, China.
Zikun ChenSchool of Life Sciences and Technology, Tongji University, No. 1239 Siping Road, Shanghai 200092, China.
Jingxuan QiuSchool of Health Science and Engineering, University of Shanghai for Science and Technology, No. 516 Jungong Road, Yangpu District, Shanghai 200093, China.ORCID 0000-0001-8420-4593
Kailin TangSchool of Life Sciences and Technology, Tongji University, No. 1239 Siping Road, Shanghai 200092, China.
Zhiwei CaoInstitute of Clinical Science, Zhongshan Hospital, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Intelligent Medicine Institute, School of Life Sciences, Fudan University, No. 180 Fenglin Road, Shanghai 200032, China.
Tianyi QiuInstitute of Clinical Science, Zhongshan Hospital, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity, Intelligent Medicine Institute, School of Life Sciences, Fudan University, No. 180 Fenglin Road, Shanghai 200032, China.ORCID 0000-0003-2619-0298

Funding

Fundamental Research Funds for the Central Universities 1350219165National Key R&D Program 2019YFA0905900National Natural Science Foundation of China 32370697
6 · The paper itself

Abstract

Nuclear receptors (NRs) are a class of essential proteins that regulate the expression of specific genes and are associated with multiple diseases. In silico methods for prescreening potential NR binders with predictive binding ability are highly desired for NR-related drug development but are rarely reported. Here, we present the PbsNRs (Predicting binders and scaffolds for Nuclear Receptors), a user-friendly web server designed to predict the potential NR binders and scaffolds through proteochemometric modeling. The utility of PbsNRs was systemically evaluated using both chemical compounds and natural products. Results indicated that PbsNRs achieved a good prediction performance for chemical compounds on internal (ROC-AUC = 0.906, where ROC is Receiver-Operating Characteristic curve and AUC is the Area Under the Curve) and external (ROC-AUC = 0.783) datasets, outperforming both compound-ligand interaction tools and NR-specific predictors. PbsNRs also successfully identified bioactive chemical scaffolds for NRs by screening massive natural products. Moreover, the predicted bioactive and inactive natural products for NR2B1 were experimentally validated using biosensors. PbsNRs not only aids in screening potential therapeutic NR binders but also helps discover the essential molecular scaffold and guide the drug discovery for multiple NR-related diseases. The PbsNRs web server is available at http://pbsnrs.badd-cao.net.

Indexed as

Receptors, Cytoplasmic and NuclearSoftwareBiological ProductsComputational BiologyDrug DiscoveryHumansLigandsProtein BindingBiological ProductsLigandsReceptors, Cytoplasmic and Nuclearbioinformaticscomputer-aided drug designmolecule scaffoldnuclear receptorsPCM model

Identifiers

PMID39798999
PMCPMC11724720

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LicenceCC BY
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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.