Evidence map›Paper›PMID 31463793›Full record

ArticleJournal of molecular modeling2019

Discovery of novel natural compound inhibitors targeting estrogen receptor α by an integrated virtual screening strategy.

Enguang Yu, Yueping Xu, Yanbo Shi, Qiuyan Yu, Jie Liu, Lei Xu

Abstract read
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In one paragraph

Article in Journal of molecular modeling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-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

9 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Computer-Aided Ligand Discovery for Estrogen Receptor Alpha.International journal of molecular sciences · 2020
    Review
  9. 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

6 authors at 2 institutions in 1 country.

Enguang YuDepartment of Chinese Surgery, Jiaxing University Affiliated Jiaxing Hospital of Traditional Chinese Medicine, Jiaxing, 314000, Zhejiang, People's Republic of China.
Yueping XuDepartment of Nursing, Jiaxing University Affiliated Jiaxing Hospital of Traditional Chinese Medicine, Jiaxing, 314000, Zhejiang, People's Republic of China.
Yanbo ShiCentral Laboratory of Molecular Medicine Research Center, Jiaxing University Affiliated Jiaxing Hospital of Traditional Chinese Medicine, Jiaxing, 314000, Zhejiang, People's Republic of China.
Qiuyan YuDepartment of Breast Surgery, Jiaxing University Affiliated Jiaxing Hospital of Traditional Chinese Medicine, Jiaxing, 314000, Zhejiang, People's Republic of China.
Jie LiuDepartment of Traditional Chinese Medicine Oncology, Jiaxing University Affiliated Jiaxing Hospital of Traditional Chinese Medicine, Jiaxing, 314000, Zhejiang, People's Republic of China.
Lei XuInstitute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, 213001, Jiangsu, China. leixu@jsut.edu.cn.ORCID http://orcid.org/0000-0002-4095-6539
Jiaxing University · CNJiangsu University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Estrogen receptor (ER) is a nuclear hormone receptor and plays an important role in mediating the cellular effects of estrogen. ER can be classified into two receptors: estrogen receptor alpha (ERα) and beta (ERβ), and the former is expressed in 50~80% of breast tumors and has been extensively investigated in breast cancer for decades. Excessive exposure to estrogen can obviously stimulate the growth of breast cancers primarily mediated by ERα, and thus anti-estrogen therapies by small molecules are of concern to clinicians and pharmaceutical industry in the treatment of ERα-positive breast cancers. Although a series of estrogen receptor modulators have been developed, these drugs can lead to resistance and side effects. Therefore, the development of small molecule inhibitors with high target specificity has been intensified. In this pursuit, an integrated computer-aided virtual screening technique, including molecular docking and pharmacophore model screening, was used to screen traditional Chinese medicine (TCM) databases. The compounds with high docking scores and fit values were subjected to ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction, and ten hits were identified as potential inhibitors targeting ERα. Molecular docking was used to investigate the binding modes between ERα and three most potent hits, and molecular dynamic simulations were chosen to explore the stability of these complexes. The rank of the predicted binding free energies evaluated by MM/GBSA is consistent with the docking score. These novel scaffolds discovered in the present study can be used as critical starting point in the drug discovery process for treating ERα-positive breast cancer. Graphical abstract .

Indexed as

Molecular Docking SimulationMolecular Dynamics SimulationAntineoplastic Agents, HormonalBreast NeoplasmsDrug Evaluation, PreclinicalEstrogen AntagonistsEstrogen Receptor alphaFemaleHumansLigandsMedicine, Chinese TraditionalProtein ConformationTamoxifenAntineoplastic Agents, HormonalEstrogen AntagonistsEstrogen Receptor alphaLigandsTamoxifenEstrogen receptor (ER) αMolecular dockingMolecular dynamics simulationPharmacophore modelTraditional Chinese medicine (TCM)Virtual screening

Identifiers

PMID31463793
OpenAlexW2971236159

What OpenQuestion holds

Textmetadata
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.