In silico identification and structural insight of allergens in Pleurotus ostreatus.

Abstract

Background: Computational approaches offer advantages for initial food allergenicity assessment. This study assesses and confirms the allergenicity based on the cross-reactivity of allergen proteins in Pleurotus ostreatus using computational methods.

Results: The possible cross-reactivity between mushroom proteins and already known allergens from an online allergen database was assessed using FASTA alignment on the basis of sequence identity percentage parameter >85%. A total of 182 query proteins were screened as putative allergens, which was further verified by sequence alignment with different allergenic proteins from databases such as Allermatch and AllercatPro. After careful analysis of the alignments, we selected 13 mushroom proteins as putative allergens, which were further analysed for B-cell epitope prediction and epitope conservancy calculation. Six of the putative allergen sequences having epitope conservancy >80% were selected and subjected to physiochemical property-based assessment to analyse allergenicity. Swiss modeller was used to model the 3D structure of allergen proteins, which were further subjected to molecular docking and molecular dynamics simulation using Cluspro web server and Gromacs, respectively. Heat shock protein A0A067NYT5 showing the lowest binding affinity of -1046.8 kcal mol^-1 among other query proteins were selected for molecular simulation for a period of 30 ns.

Conclusion: Computational tools offer preliminary indications of potential allergenicity and cross-reactivity of mushroom proteins, potentially aiding in the assessment of allergen sources for elusive results. © 2025 Society of Chemical Industry.