Evidence map›Paper›PMID 34631360›Full record

ArticleIn silico pharmacology2021

Multifaceted targeting strategies in cancer against the human notch 3 protein: a computational study.

S Saranyadevi

Open access · bronzeAbstract read
In one paragraph

Article in In silico pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 46% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Green Synthesis of Novel Silver Nanoparticles UsingInternational journal of molecular sciences · 2024
    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

1 author at 1 institution in 1 country.

S SaranyadeviDepartment of Nanotechnology, Nanodot Research Private Limited, Nagercoil, Kanyakumari, 629001 India.ORCID 0000-0001-6938-5066
Kanyakumari Government Medical College · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Notch receptors play a significant role in the development and the regulation of cell-fate in several multicellular organisms. For normal differentiation, genomes are essential as their regular roles and play a role in cancer is dysregulated. Notch 3 has been shown to play a major role in lung cancer function and therefore, inhibition of notch 3 protein activation represents a clear plan for cancer treatment. This study accomplished a combined structure- and ligand-based pharmacophore hypothesis to explore novel notch 3 inhibitors. The analysis identified common lead molecule ZINC000013449462 that showed better XP GScore and binding energy score than the reference inhibitor DAPT. The identified lead compound that passed all the druggable characteristics exhibited stable binding. Furthermore, the lead molecule can also form hydrogen and salt bridge interactions with binding site residues Asp1621 and Arg1465 residues, respectively of the active pockets of notch 3 protein. In essence, the inhibitory activity of the hit was validated across 109 NSCLC cell lines by employing a deep neural network algorithm. Our study proposes that ZINC000013449462 would be a possible prototype molecule towards the notch 3 target and further examined by clinical studies to combat NSCLC.

Indexed as

ADMETDeep learning modelDrug repurposingLung cancerNotch 3Virtual screening

Identifiers

PMID34631360
PMCPMC8481405
OpenAlexW3203655318

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.