Evidence map›Paper›PMID 36873279›Full record

ArticleResearch in pharmaceutical sciences2023

Identifying potential ligand molecules EGFR mediated TNBC targeting the kinase domain-identification of customized drugs through

Hima Vyshnavi, Krishnan Namboori

Abstract read
In one paragraph

Article in Research in pharmaceutical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

2 authors.

Hima VyshnaviComputational Chemistry Group (CCG), Amrita Molecular Modeling and Synthesis Research Lab, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India.
Krishnan NambooriComputational Chemistry Group (CCG), Amrita Molecular Modeling and Synthesis Research Lab, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Purpose: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer in which three hormone receptors are negative. This work aimed at identifying customized potential molecules inhibiting epidermal growth factor receptor (EGFR) by exploring variants using the pharmacogenomics approaches. Experimental approach: The pharmacogenomics approach has been followed to identify the genetic variants across the 1000 genomes continental population. Model proteins for the populations have been designed by including genetic variants in the reported positions. The 3D structures of the mutated proteins have been generated through homology modeling. The kinase domain present in the parent and the model protein molecules has been investigated. The docking study has been performed with the protein molecules against the kinase inhibitors evaluated by the molecular dynamic simulation studies. Molecular evolution has been performed to generate the potential derivatives of these kinase inhibitors suitable for the conserved region of the kinase domain. This study considered variants within the kinase domain as the sensitive region and remaining residues as the conserved region. Findings/Results: The results reveal that few kinase inhibitors interact with the sensitive region. Among the derivatives of these kinase inhibitors molecules, the potential kinase inhibitor that interacts with the different population models has been identified. Conclusions and implications: This study encompasses the importance of genetic variants in drug action as well as in the design of customized drugs. This research gives way to designing customized potential molecules inhibiting EGFR by exploring variants using the pharmacogenomics approaches.

Indexed as

Conserved regionEGFRKinase domainSensitive regionTNBC

Identifiers

PMID36873279
PMCPMC9976054

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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.