Evidence map›Paper›PMID 26862373›Full record

ArticleComputational and structural biotechnology journal2016

Prediction of anticancer peptides against MCF-7 breast cancer cells from the peptidomes of Achatina fulica mucus fractions.

Teerasak E-Kobon, Pennapa Thongararm, Sittiruk Roytrakul, Ladda Meesuk, Pramote Chumnanpuen

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Biological Properties of the Mucus and Eggs ofInternational journal of molecular sciences · 2024
    Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. PeerJ · 2024
    Article
  17. Short Fragmented Peptides fromCurrent drug discovery technologies · 2024
    Article
  18. Article
  19. Article
  20. Proteome of monocled cobra (Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2023
    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

5 authors.

Teerasak E-KobonDepartment of Genetics, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.
Pennapa ThongararmDepartment of Zoology, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.
Sittiruk RoytrakulNational Center for Genetic Engineering and Biotechnology, Thailand Science Park, Pathum Thani 12120, Thailand.
Ladda MeesukFaculty of Dentistry, Thammasat University, Pathum Thani 12120, Thailand.
Pramote ChumnanpuenDepartment of Zoology, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several reports have shown antimicrobial and anticancer activities of mucous glycoproteins extracted from the giant African snail Achatina fulica. Anticancer properties of the snail mucous peptides remain incompletely revealed. The aim of this study was to predict anticancer peptides from A. fulica mucus. Two of HPLC-separated mucous fractions (F2 and F5) showed in vitro cytotoxicity against the breast cancer cell line (MCF-7) and normal epithelium cell line (Vero). According to the mass spectrometric analysis, 404 and 424 peptides from the F2 and F5 fractions were identified. Our comprehensive bioinformatics workflow predicted 16 putative cationic and amphipathic anticancer peptides with diverse structures from these two peptidome data. These peptides would be promising molecules for new anti-breast cancer drug development.

Indexed as

Achatina fulicaBioinformatics predictionBreast cancerCytotoxic peptidesPeptidomicsSnail mucus

Identifiers

PMID26862373
PMCPMC4706611

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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.