Zhang Guang Lan, Khan Asif M, Srinivasan Kellathur N, August J Thomas, Brusic Vladimir
Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.
Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W172-9. doi: 10.1093/nar/gki452.
MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules (proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability (area under the receiver operating characteristic curve A(ROC) > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets--termed T-cell epitope hotspots. MULTIPRED is available at http://antigen.i2r.a-star.edu.sg/multipred/.
MULTIPRED是一个基于网络的计算系统,用于预测肽与属于人类白细胞抗原(HLA)I类A2、A3以及II类DR超型的多种分子(蛋白质)的结合。它使用隐马尔可夫模型和人工神经网络方法作为预测引擎。一种新颖的数据表示方法使MULTIPRED能够预测在一个HLA超型内可与多个HLA等位基因混杂结合的肽。为验证预测模型进行了广泛测试。测试结果表明,MULTIPRED既灵敏又特异,具有良好的预测能力(受试者操作特征曲线下面积A(ROC) > 0.80)。MULTIPRED可用于混杂性T细胞表位的定位以及这些靶标的高浓度区域——即所谓的T细胞表位热点。可通过http://antigen.i2r.a-star.edu.sg/multipred/访问MULTIPRED。