Identification and Structural Insights of Allergens in Anacardium occidentale

Abstract

BACKGROUND: Food allergies are allergic reactions that are triggered by food ingredients and affect the immune system, they are most frequently caused by plant-derived foods, especially in adults and children. For tracing the allergens in food there have been developed several methods including both computational and conventional methods, but for preliminary assessment of food allergenicity, the use of computational tools may be more advantageous than using conventional methods. In this study, in silico tools were used to evaluate and validate the allergenic potential of cashew protein. RESULTS: The cross-reactivity of cashew proteins with food allergens was evaluated using the Fast Alignment (FASTA) and Basic Local Alignment Search Tool (BLAST) algorithmbased sequence alignment. Eleven cashew proteins were cross-reactive with known food allergens by consensus approach using both FASTA and BLAST algorithm-based sequence alignment. BLAST data shows the E-value and the percent identity and FASTA alignment demonstrate >50% sequence identity of eleven cashew proteins. AllergenFP, AlgPred, and Allermatch – allergenicity predicted software predicted that eight out of eleven cashew proteins were potential allergens on the basis of their physicochemical properties. According to the sequence alignment using the MUSCLE tool, the cashew protein, and known food allergens were found to have 30.4%-66.8% conservancy. amino acid comparison and secondary structure between cashew protein and known food allergens were predicted and compared using the PHD fold server and PSIPRED. For quality assessment, three-dimensional structure, and superimposition of 8 cashew proteins with food allergens were generated. A protein family analysis was determined using Pfam, conserved domain databases, HMMER, and InterPro databases. Based on the GO accession number, the WEGO tool was used to visualize the gene ontology data. SWISS-MODEL server is used to model the structures of selected cashew proteins. B-cell epitopes for the selected cashew proteins were predicted and their structure modeling for the epitope was conducted by PepFold 3.5 server and subjected to docking in ClusPro 2.0 server. Several docked models were produced through docking; however, the lowest binding energy model was selected for further evaluation. CONCLUSION: Preliminary information on the cross-reactivity and potential allergenicity of cashew proteins is provided by In silico technologies. The prelusive allergenicity of allergen sources can be assessed using this method.