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Cross-React: a new structural bioinformatics method for predicting allergen cross-reactivity

机译:交叉反应:一种新的结构生物信息学方法,用于预测过敏原交叉反应性

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The phenomenon of cross-reactivity between allergenic proteins plays an important role to understand how the immune system recognizes different antigen proteins. Allergen proteins are known to cross-react if their sequence comparison shows a high sequence identity which also implies that the proteins have a similar 3D fold. In such cases, linear sequence alignment methods are frequently used to predict cross-reactivity between allergenic proteins. However, the prediction of cross-reactivity between distantly related allergens continues to be a challenging task. To overcome this problem, we developed a new structure-based computational method, Cross-React, to predict cross-reactivity between allergenic proteins available in the Structural Database of Allergens (SDAP). Our method is based on the hypothesis that we can find surface patches on 3D structures of potential allergens with amino acid compositions similar to an epitope in a known allergen. We applied the Cross-React method to a diverse set of seven allergens, and successfully identified several cross-reactive allergens with high to moderate sequence identity which have also been experimentally shown to cross-react. Based on these findings, we suggest that Cross-React can be used as a predictive tool to assess protein allergenicity and cross-reactivity.
机译:过敏蛋白之间的交叉反应性的现象起着重要作用,以了解免疫系统如何识别出不同的抗原蛋白。已知过敏原蛋白在它们的序列比较显示高序列同一性,这也意味着蛋白质具有相似的3D折叠。在这种情况下,线性序列取向方法经常用于预测过敏蛋白之间的交叉反应性。然而,在远处相关过敏原之间的交叉反应性的预测仍然是一个具有挑战性的任务。为了克服这个问题,我们开发了一种新的基于结构的计算方法,交叉反应,预测过敏蛋白在过敏原(SDAP)结构数据库中可用的过敏蛋白之间的交叉反应性。我们的方法基于假设,我们可以在具有与已知过敏原中的表位类似的氨基酸组合物的潜在过敏原的3D结构上找到表面斑块。我们将交叉反应方法应用于各种七种过敏原,并成功地确定了几种具有高于中等序列同一性的交叉反应性过敏原,该过敏剂也经过实验地显示出交叉反应。基于这些发现,我们建议交叉反应可以用作评估蛋白质过敏性和交叉反应性的预测工具。

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