Population of the HLA ligand database
Population of the HLA ligand database
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DOI：
10.1034/j.1399-0039.2003.610102.x
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发表时间：
2003-01-01
期刊：
影响因子：
--
通讯作者：
Hildebrand, WH
中科院分区：
文献类型：
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作者：
Sathiamurthy, M;Hickman, HD;Hildebrand, WH
我们已经建立了一个HLA配体数据库，为科学家和临床医生提供主要组织相容性复合物（MHC）I类和II类基序和配体数据。HLA配体数据库可在万维网http://hlaligand.ouhsc.edu上获得，并且包含已在同行评审期刊上发表的配体。HLA肽数据集在几个领域证明是有用的：配体是重要的各种免疫反应的目标，而建立在配体数据集上的算法允许识别新的肽，而无需耗时的实验程序。对数据库中的HLA I类配体的回顾确定了数据库中的优势和不足，因此确定了数据集用于识别新肽的实用性。例如，存在212种HLA-A表型，其中23种具有确定的基序，43种具有表征的肽。在配体数量方面，HLA-A*0201具有258个特征化配体，A*1101具有25个肽，而其余三分之二的HLA-A表型具有少于10个相关肽序列。配体和基序的表征在HLA-B基因座处保持大致相同，而HLA-C基因座的肽倾向于较少表征。这些数据表明，74%的HLA I类分子没有在数据库中表示的配体，因此基于数据集的算法无法预测大多数美国人口的配体。基于该数据集和HLA等位基因频率的知识，有可能计划HLA I类配体数据库的系统扩展，以更好地鉴定在整个人群中有用的配体。
We have established an HLA ligand database to provide scientists and clinicians with access to Major Histocompatibility Complex (MHC) class I and II motif and ligand data. The HLA Ligand Database is available on the world wide web at http://hlaligand.ouhsc.edu and contains ligands that have been published in peer-reviewed journals. HLA peptide datasets prove useful in several areas: ligands are important as targets for various immune responses while algorithms built upon ligand datasets allow identification of new peptides without time-consuming experimental procedures. A review of the HLA class I ligands in the database identifies strengths and deficiencies in the database and, therefore, the utility of the dataset for identifying new peptides. For instance, 212 HLA-A phenotypes exist of which 23 have a motif determined and 43 have peptides characterized. In terms of number of ligands, HLA-A*0201 has 258 characterized ligands, A*1101 has 25 peptides, while the remaining two-thirds of the HLA-A phenotypes have less than 10 associated peptide sequences. Characterization of ligands and motifs remains roughly the same at the HLA-B locus while the peptides of the HLA-C locus tend to be less characterized. These data show that 74% of HLA class I molecules do not have ligands represented in the database and thus algorithms based on the dataset could not predict ligands for a majority of the US population. Building upon this dataset and knowledge of HLA allelic frequencies, it is possible to plan a systematic expansion of the HLA class I ligand database to better identify ligands useful throughout the population.