Introduction: Fungi are common aeroallergens responsible for at least 3% - 10% of allergic diseases worldwide, with the proportion hugely variable in different populations. Treatment is complicated by viable nature and disease causing ability of the allergen and is often only palliative. Thus, this study aimed to serve as a pilot investigation to design novel anti-allergy therapeutics to cure allergy at the molecular level. It investigates the effect of wild type fungal peptides and corresponding variant peptides on allergy associated immunological responses - cellular and cytokine based - to use such variant peptides to cause the delicate shift from an allergic to a normal immune response. Further, the study explores the role of bioinformatics in investigating allergy and designing novel therapeutics. Methods: This study used ProPred, a bioinformatics software, to predict wild type peptides from selected allergens of Aspergillus fumigatus and Alternata alternaria for a target population. These were then modified to generate single amino acid variants. Both these peptide sets were tested to compare the cellular and cytokine patterns they generated in sensitised (n = 3) and healthy volunteers (n = 3) to check for anti-allergy responses that may be exerted by certain variants. The recruited population was also subjected to skin prick testing (SPT, n = 46) to check for co-sensitisations patterns and HLA typing (n = 40) to evaluate ProPred accuracy for peptide prediction. This study also attempted an in silico search for unknown Penicillium chrysogenum allergens by comparing known Penicillium and A. fumigatus allergens to identify probable agents of co-sensitization. Results: Of the wild type and variant peptides tested in this study, one variant peptide - peptide 1.1v from Asp f 2 - was successfully identified to change the cellular and cytokine profile to promote an anti-allergic response when compared to its corresponding wild type form (1.1o). This candidate is a good target for further investigation for use in peptide immunotherapy. Further, 8 shared allergens between A. fumigatus and P. chrysogenum were identified that may possibly be agents of co-sensitization between these species. SPT results indicated maximum subject co-sensitization between A. fumigatus and Candida albicans and P. chrysogenum. HLA typing results demonstrated the efficiency of ProPred to be 96.29%, thus implying that bioinformatics can effectively be used to study allergy in this novel manner. Conclusion: This study has demonstrated that variant peptides with a single amino acid change can cause the delicate shift from an allergic to a healthy immune response in sensitised subjects. This approach - in combination with other allergy associated factors such as epitope specificity for HLA types and inherent co-sensitization patterns in a population - can effectively be used to design peptide candidates for immunotherapy to target allergy at the molecular level. With promising results obtained in this pilot study, this approach guarantees further investigation in immunotherapy. This study has also demonstrated that bioinformatics can be effectively used to design and execute allergy studies in a targeted and inexpensive manner.