Evidence map›Paper›PMID 38509156›Full record

ArticleScientific reports2024

In silico approaches for the identification of potential allergens among hypothetical proteins from Alternaria alternata and its functional annotation.

Rajamanikandan Sundararaj, Amala Mathimaran, Dhamodharan Prabhu, Balajee Ramachandran, Jeyakanthan Jeyaraman, Saravanan Muthupandian, Tsehaye Asmelash

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. AirborneJournal of fungi (Basel, Switzerland) · 2024
    Article
4 · The record

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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

7 authors.

Rajamanikandan SundararajDepartment of Biochemistry, Centre for Drug Discovery, Karpagam Academy of Higher Education, Coimbatore, 641021, India.
Amala MathimaranStructural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630 004, India.
Dhamodharan PrabhuDepartment of Biotechnology, Centre for Drug Discovery, Karpagam Academy of Higher Education, Coimbatore, 641021, India.
Balajee RamachandranDepartment of Pharmacology, Physiology & Biophysics, Chobanian & Avedisian School of Medicine, Boston University, 700 Albany Street, Boston, MA, 02118, USA.
Jeyakanthan JeyaramanStructural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630 004, India.
Saravanan MuthupandianDepartment of Pharmacology, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, 600077, India.
Tsehaye AsmelashDepartment of Medical Microbiology and Immunology, College of Health Sciences, Mekelle University, Mekelle, Tigray, Ethiopia. tsehaye.asmelash@mu.edu.et.ORCID 0000-0002-6182-6223

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Direct exposure to the fungal species Alternaria alternata is a major risk factor for the development of asthma, allergic rhinitis, and inflammation. As of November 23rd 2020, the NCBI protein database showed 11,227 proteins from A. alternata genome as hypothetical proteins (HPs). Allergens are the main causative of several life-threatening diseases, especially in fungal infections. Therefore, the main aim of the study is to identify the potentially allergenic inducible proteins from the HPs in A. alternata and their associated functional assignment for the complete understanding of the complex biological systems at the molecular level. AlgPred and Structural Database of Allergenic Proteins (SDAP) were used for the prediction of potential allergens from the HPs of A. alternata. While analyzing the proteome data, 29 potential allergens were predicted by AlgPred and further screening in SDAP confirmed the allergic response of 10 proteins. Extensive bioinformatics tools including protein family classification, sequence-function relationship, protein motif discovery, pathway interactions, and intrinsic features from the amino acid sequence were used to successfully predict the probable functions of the 10 HPs. The functions of the HPs are characterized as chitin-binding, ribosomal protein P1, thaumatin, glycosyl hydrolase, and NOB1 proteins. The subcellular localization and signal peptide prediction of these 10 proteins has further provided additional information on localization and function. The allergens prediction and functional annotation of the 10 proteins may facilitate a better understanding of the allergenic mechanism of A. alternata in asthma and other diseases. The functional domain level insights and predicted structural features of the allergenic proteins help to understand the pathogenesis and host immune tolerance. The outcomes of the study would aid in the development of specific drugs to combat A. alternata infections.

Indexed as

AsthmaHypersensitivityAllergensAlternariaAllergensAlgPredAlternaria alternataSDAPStructure–function relationship and drug discovery

Identifiers

PMID38509156
PMCPMC10954717

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