Ivanciuc Ovidiu, Schein Catherine H, Braun Werner
Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch, Galveston, TX 77555-1157, USA.
Bioinformatics. 2002 Oct;18(10):1358-64. doi: 10.1093/bioinformatics/18.10.1358.
Many sequences, and in some cases structures, of proteins that induce an allergic response in atopic individuals have been determined in recent years. This data indicates that allergens, regardless of source, fall into discreet protein families. Similarities in the sequence may explain clinically observed cross-reactivities between different biological triggers. However, previously available allergy databases group allergens according to their biological sources, or observed clinical cross-reactivities, without providing data about the proteins. A computer-aided data mining system is needed to compare the sequential and structural details of known allergens. This information will aid in predicting allergenic cross-responses and eventually in determining possible common characteristics of IgE recognition.
The new web-based Structural Database of Allergenic Proteins (SDAP) permits the user to quickly compare the sequence and structure of allergenic proteins. Data from literature sources and previously existing lists of allergens are combined in a MySQL interactive database with a wide selection of bioinformatics applications. SDAP can be used to rapidly determine the relationship between allergens and to screen novel proteins for the presence of IgE or T-cell epitopes they may share with known allergens. Further, our novel similarity search method, based on five dimensional descriptors of amino acid properties, can be used to scan the SDAP entries with a peptide sequence. For example, when a known IgE binding epitope from shrimp tropomyosin was used as a query, the method rapidly identified a similar sequence in known shellfish and insect allergens. This prediction of cross-reactivity between allergens is consistent with clinical observations.
SDAP is available on the web at http://fermi.utmb.edu/SDAP/index.html
近年来，已确定了许多能在特应性个体中引发过敏反应的蛋白质序列，在某些情况下还包括其结构。这些数据表明，过敏原无论来源如何，都属于不同的蛋白质家族。序列上的相似性或许可以解释临床上观察到的不同生物触发因素之间的交叉反应性。然而，以前可用的过敏数据库是根据过敏原的生物来源或观察到的临床交叉反应性对其进行分类的，并未提供有关蛋白质的数据。因此需要一个计算机辅助数据挖掘系统来比较已知过敏原的序列和结构细节。这些信息将有助于预测过敏交叉反应，并最终确定IgE识别的可能共同特征。
新的基于网络的变应原蛋白结构数据库（SDAP）允许用户快速比较变应原蛋白的序列和结构。来自文献来源的数据和先前存在的过敏原列表被整合到一个MySQL交互式数据库中，并配有广泛的生物信息学应用程序。SDAP可用于快速确定过敏原之间的关系，并筛选新蛋白质中是否存在它们可能与已知过敏原共有的IgE或T细胞表位。此外，我们基于氨基酸性质的五维描述符的新型相似性搜索方法，可用于用肽序列扫描SDAP条目。例如，当使用来自虾原肌球蛋白的已知IgE结合表位作为查询时，该方法能在已知的贝类和昆虫过敏原中快速识别出相似序列。这种对过敏原之间交叉反应性的预测与临床观察结果一致。
SDAP可通过网络访问，网址为http://fermi.utmb.edu/SDAP/index.html
