Scholarlink

Purpose <p>The ingestion of food triggering an allergic reaction that affects the immune system is called food allergy. Various methods, including computational and conventional approaches, have been developed to identify the allergenic components in food. Computational tools are preferred for the preliminary assessment of food allergenicity due to their cost-effectiveness and speed compared to conventional methods. This research aimed to employ in silico methods to identify, evaluate, and validate the allergenic potential of cashew proteins.</p> Method <p>The study assessed the cross-reactivity of cashew proteins with known food allergens using Fast Alignment (FASTA) and the Basic Local Alignment Search Tool (BLAST) for sequence alignment. Allergenicity was further evaluated using <i>AllergenFP</i>, <i>AlgPred</i>, and <i>Allermatch</i> based on the physicochemical properties of the proteins. Conservation analysis was conducted between cashew proteins and known allergens. B-cell epitopes were predicted, and 3D structure modelling was carried out using the I-TASSER server. The modelled structures were docked against the IgE Fab region (PDB ID: 8VK2) using the Cluspro 2.0 server. The model with the lowest binding energy among the docked complexes was selected for further analysis.</p> Result <p>FASTA and BLAST results revealed that eleven cashew proteins showed cross-reactivity with known food allergens. Of these, eight proteins were predicted as potential allergens by multiple prediction tools. Sequence alignment indicated a 66–68% Conservation between the cashew proteins and known allergens. Predicted B-cell epitopes and structural models provided further evidence supporting their allergenic potential. The docking studies identified the most stable IgE-protein complex based on binding energy, highlighting potential IgE interaction sites.</p> Conclusion <p>In silico analysis offers a rapid and informative approach to evaluate the cross-reactivity and potential allergenicity of cashew proteins. The results emphasize the presence of conserved allergenic features within various protein families. This computational approach can serve as a valuable tool for the early assessment of food allergenicity in novel or underexplored food sources.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Exploring the potential cross-reactivity of allergenic proteins from Anacardium occidentale using in-silico approaches

  • 期刊论文

  • 发表日期：

    2026年2月6日

查看全文
  • Rashi Chugh,
  • Yadvi Sandhir,
  • Ranjit Singh Gujjar,
  • Vikas Handa,
  • Atul Kumar Upadhyay

摘要

Purpose

The ingestion of food triggering an allergic reaction that affects the immune system is called food allergy. Various methods, including computational and conventional approaches, have been developed to identify the allergenic components in food. Computational tools are preferred for the preliminary assessment of food allergenicity due to their cost-effectiveness and speed compared to conventional methods. This research aimed to employ in silico methods to identify, evaluate, and validate the allergenic potential of cashew proteins.

Method

The study assessed the cross-reactivity of cashew proteins with known food allergens using Fast Alignment (FASTA) and the Basic Local Alignment Search Tool (BLAST) for sequence alignment. Allergenicity was further evaluated using AllergenFP, AlgPred, and Allermatch based on the physicochemical properties of the proteins. Conservation analysis was conducted between cashew proteins and known allergens. B-cell epitopes were predicted, and 3D structure modelling was carried out using the I-TASSER server. The modelled structures were docked against the IgE Fab region (PDB ID: 8VK2) using the Cluspro 2.0 server. The model with the lowest binding energy among the docked complexes was selected for further analysis.

Result

FASTA and BLAST results revealed that eleven cashew proteins showed cross-reactivity with known food allergens. Of these, eight proteins were predicted as potential allergens by multiple prediction tools. Sequence alignment indicated a 66–68% Conservation between the cashew proteins and known allergens. Predicted B-cell epitopes and structural models provided further evidence supporting their allergenic potential. The docking studies identified the most stable IgE-protein complex based on binding energy, highlighting potential IgE interaction sites.

Conclusion

In silico analysis offers a rapid and informative approach to evaluate the cross-reactivity and potential allergenicity of cashew proteins. The results emphasize the presence of conserved allergenic features within various protein families. This computational approach can serve as a valuable tool for the early assessment of food allergenicity in novel or underexplored food sources.