Evidence map›Paper›PMID 22022246›Full record

ArticlePLoS computational biology2011

Identification of potent EGFR inhibitors from TCM Database@Taiwan.

Shun-Chieh Yang, Su-Sen Chang, Hsin-Yi Chen, Calvin Yu-Chian Chen

RetractedAbstract readRetracted Publication
In one paragraph

Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing 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

54 citing papers in PubMed.

  1. Article
  2. Review
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  6. Identification of NewMolecules (Basel, Switzerland) · 2021
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  15. Discovery of newMolecular diversity · 2015
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Shun-Chieh YangLaboratory of Computational and Systems Biology, School of Chinese Medicine, China Medical University, Taichung, Taiwan. ycc929@MIT.EDU
Su-Sen Chang
Hsin-Yi Chen
Calvin Yu-Chian Chen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Overexpression of epidermal growth factor receptor (EGFR) has been associated with cancer. Targeted inhibition of the EGFR pathway has been shown to limit proliferation of cancerous cells. Hence, we employed Traditional Chinese Medicine Database (TCM Database@Taiwan) (http://tcm.cmu.edu.tw) to identify potential EGFR inhibitor. Multiple Linear Regression (MLR), Support Vector Machine (SVM), Comparative Molecular Field Analysis (CoMFA), and Comparative Molecular Similarities Indices Analysis (CoMSIA) models were generated using a training set of EGFR ligands of known inhibitory activities. The top four TCM candidates based on DockScore were 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid, and all had higher binding affinities than the control Iressa®. The TCM candidates had interactions with Asp855, Lys716, and Lys728, all which are residues of the protein kinase binding site. Validated MLR (r² = 0.7858) and SVM (r² = 0.8754) models predicted good bioactivity for the TCM candidates. In addition, the TCM candidates contoured well to the 3D-Quantitative Structure-Activity Relationship (3D-QSAR) map derived from the CoMFA (q² = 0.721, r² = 0.986) and CoMSIA (q² = 0.662, r² = 0.988) models. The steric field, hydrophobic field, and H-bond of the 3D-QSAR map were well matched by each TCM candidate. Molecular docking indicated that all TCM candidates formed H-bonds within the EGFR protein kinase domain. Based on the different structures, H-bonds were formed at either Asp855 or Lys716/Lys728. The compounds remained stable throughout molecular dynamics (MD) simulation. Based on the results of this study, 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid are suggested to be potential EGFR inhibitors.

Indexed as

Databases, FactualAlgorithmsErbB ReceptorsHydrogen BondingLigandsModels, MolecularMolecular Dynamics SimulationProtein ConformationQuantitative Structure-Activity RelationshipTaiwanErbB ReceptorsLigands

Identifiers

PMID22022246
PMCPMC3192800

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.