Evidence map›Paper›PMID 29295563›Full record

ArticleVaccines2017

Structural Analysis and Epitope Prediction of MHC Class-1-Chain Related Protein-A for Cancer Vaccine Development.

Tayo Alex Adekiya, Raphael Taiwo Aruleba, Sbonelo Khanyile, Priscilla Masamba, Babatunji Emmanuel Oyinloye, Abidemi Paul Kappo

Open access · goldAbstract read
In one paragraph

Article in Vaccines, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 34 citations in OpenAlex.

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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

6 authors at 1 institution in 2 countries.

Tayo Alex AdekiyaBiotechnology and Structural Biology (BSB) Group, Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa. adekiyatalex@gmail.com.
Raphael Taiwo ArulebaBiotechnology and Structural Biology (BSB) Group, Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa. arulebataiwo@yahoo.com.
Sbonelo KhanyileBiotechnology and Structural Biology (BSB) Group, Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa. s7khanyile@gmail.com.
Priscilla MasambaBiotechnology and Structural Biology (BSB) Group, Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa. presh4u@rocketmail.com.
Babatunji Emmanuel OyinloyeBiotechnology and Structural Biology (BSB) Group, Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa. tunji4reele@yahoo.com.
Abidemi Paul KappoBiotechnology and Structural Biology (BSB) Group, Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa. KappoA@unizulu.ac.za.
University of Zululand · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Major histocompatibility complex class 1 chain-related gene sequence A is a polymorphic gene found at about 46.6 kb centromeric to HLA-B. It encodes a transmembrane protein, which is a non-classical human leukocyte antigen whose expression is normally induced by stress conditions like cancer and viral infections. The expression of MIC-A leads to the activation of NKG2D receptors of natural killer and T cells, leading to the generation of innate immune response that can easily eliminate/cleanse tumour cells and other cells that express the protein. Several bioinformatics and immunoinformatics tools were used to analyse the sequence and structure of the MIC-A protein. These tools were used in building and evaluating modelled structure of MIC-A, and to predict several antigenic determinant sites on the protein. The MIC-A protein structure generated an average antigenic propensity of 1.0289. Additionally, the hydrophilic regions on the surface of the MIC-A protein where antibodies can be attached were revealed. A total of fourteen antigenic epitopes were predicted, with six found in the transmembrane protein topology, and are predicted to play a role in the development of vaccines that can reactivate the functionalities of the MIC-A protein on the surface of cancer cells in order to elicit a desired immune response.

Indexed as

3-D structureantigenic peptidesbioinformaticscancerepitopesMIC-Avaccine

Identifiers

PMID29295563
PMCPMC5874642
OpenAlexW2776917115

What OpenQuestion holds

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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.