Evidence map›Paper›PMID 38638686›Full record

ArticleFrontiers in molecular biosciences2024

Chemoinformatics and machine learning techniques to identify novel inhibitors of the lemur tyrosine kinase-3 receptor involved in breast cancer.

Faris Alrumaihi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 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, top 94% 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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Faris AlrumaihiDepartment of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia.
Qassim University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is still the largest cause of cancer death in women, and around 70% of primary breast cancer patients are estrogen receptor (ER)-positive, which is the most frequent kind of breast cancer. The lemur tyrosine kinase-3 (LMTK3) receptor has been linked to estrogen responsiveness in breast cancer. However, the function of LMTK3 in reaction to cytotoxic chemotherapy has yet to be studied. Breast cancer therapy research remains tricky due to a paucity of structural investigations on LMTK3. We performed structural investigations on LMTK3 using molecular docking and molecular dynamics (MD) simulations of the LMTK3 receptor in complex with the top three inhibitor molecules along with a control inhibitor. Analysis revealed the top three compounds show the best binding affinities during docking simulations. Interactive analysis of hydrogen bonds inferred hotspot residues Tyr163, Asn138, Asp133, Tyr56, Glu52, Ser132, Asp313, and Asp151. Some other residues in the 5-Å region determined strong alkyl bonds and conventional hydrogen bond linkages. Furthermore, protein dynamics analysis revealed significant modifications among the top complexes and the control system. There was a transition from a loop to a-helix conformation in the protein-top1 complex, and in contrast, in complexes top2 and top3, the formation of a stabilizing sheet in the C chain was observed, which limited significant mobility and increased complex stability. Significant structural alterations were observed in the protein-top complexes, including a shorter helix region and the creation of some loop regions in comparison to the control system. Interestingly, binding free energies, including MMGB/PBSA WaterSwap analysis estimation, reveals that the top1 complex system was more stable than other systems, especially in comparison to the control inhibitor complex system. These results suggest a the plausible mode of action for the novel inhibitors. Therefore, the current investigation contributes to understanding the mechanism of action, serving as a basis for future experimental studies.

Indexed as

binding energiesbreast cancerhydrogen bondingLMTK3WaterSwap analysis

Identifiers

PMID38638686
PMCPMC11025642
OpenAlexW4393931161

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.