Doytchinova Irini, Atanasova Mariyana, Sotirov Stanislav, Dimitrov Ivan
Drug Design and Bioinformatics Lab, Faculty of Pharmacy, Medical University of Sofia, 1000 Sofia, Bulgaria.
Pharmaceuticals (Basel). 2024 Aug 21;17(8):1097. doi: 10.3390/ph17081097.
Peanut allergy, a prevalent and potentially severe condition affecting millions worldwide, has been linked to specific human leukocyte antigens (HLAs), suggesting increased susceptibility. Employing an immunoinformatic strategy, we developed a "logo model" based on amino acid frequencies in the peptide binding core and used it to predict peptides originating from 28 known peanut allergens binding to HLA-DRB103:01, one of the susceptibility alleles. These peptides hold promise for immunotherapy in HLA-DRB103:01 carriers, offering reduced allergenicity compared to whole proteins. By targeting essential epitopes, immunotherapy can modulate immune responses with minimal risk of severe reactions. This precise approach could induce immune tolerance with fewer adverse effects, presenting a safer and more effective treatment for peanut allergy and other allergic conditions.
花生过敏是一种在全球影响数百万人的普遍且可能严重的病症,它与特定的人类白细胞抗原(HLA)相关联,表明易感性增加。我们采用免疫信息学策略,基于肽结合核心中的氨基酸频率开发了一种“标志模型”,并用它来预测源自28种已知花生过敏原的肽与易感性等位基因之一的HLA - DRB103:01结合。这些肽有望用于HLA - DRB103:01携带者的免疫治疗,与全蛋白相比,其致敏性降低。通过靶向关键表位,免疫治疗可以调节免疫反应,同时严重反应的风险最小。这种精确的方法可以以较少的不良反应诱导免疫耐受,为花生过敏和其他过敏性疾病提供更安全、更有效的治疗方法。