Prediction of antibody structural epitopes via random peptide library screening and next generation sequencing.
Prediction of antibody structural epitopes via random peptide library screening and next generation sequencing.
复制标题
DOI：
10.1016/j.jim.2017.08.004
复制
发表时间：
2017-12
影响因子：
2.2
通讯作者：
Daugherty PS
中科院分区：
文献类型：
--
作者：
Ibsen KN;Daugherty PS
新一代测序技术在免疫学研究中得到了广泛的应用，但在抗体表位定位中尚未普及。一种利用细菌中表达的12聚随机肽文库，结合磁性细胞分选和NGS的方法，正确地鉴定了两种单克隆抗体（曲妥珠单抗和贝伐单抗）抗原上75%以上的表位残基。PepSurf是一种设计用于结构表位定位的基于网络的计算方法，用于比较单克隆抗体（mAb）结合物库中与抗原表面（HER2和VEGF-A）丰富的肽段。与从相同分选方案的Sanger测序中获得的半模位相比，来自NGS数据集的基序提高了表位预测的灵敏度和精度，曲妥珠单抗从18%提高到82%，从0.27提高到0.51，贝伐单抗从47%提高到76%，从0.19提高到0.27。Sanger和NGS的特异性相似，曲妥珠单抗的特异性为99%和97%，贝伐单抗的特异性为66%和67%。这些结果表明，将肽库筛选与NGS相结合产生的表位基序可以提高结构表位的预测。
Next generation sequencing (NGS) is widely applied in immunological research, but has yet to become common in antibody epitope mapping. A method utilizing a 12-mer random peptide library expressed in bacteria coupled with magnetic-based cell sorting and NGS correctly identified more than 75% of epitope residues on the antigens of two monoclonal antibodies (trastuzumab and bevacizumab). PepSurf, a web-based computational method designed for structural epitope mapping was utilized to compare peptides in libraries enriched for monoclonal antibody (mAb) binders to antigen surfaces (HER2 and VEGF-A). Compared to mimotopes recovered from Sanger sequencing of plated colonies from the same sorting protocol, motifs derived from sets of the NGS data improved epitope prediction as defined by sensitivity and precision, from 18% to 82% and 0.27 to 0.51 for trastuzumab and 47% to 76% and 0.19 to 0.27 for bevacizumab. Specificity was similar for Sanger and NGS, 99% and 97% for trastuzumab and 66% and 67% for bevacizumab. These results indicate that combining peptide library screening with NGS yields epitope motifs that can improve prediction of structural epitopes.
登录
查看更多内容
影响因子：
3.5
作者：
Li W;Ran Y;Li M;Zhang K;Qin X;Xue X;Zhang C;Hao Q;Zhang W;Zhang Y
通讯作者：
Zhang Y
影响因子：
64.8
作者：
Cho, HS;Mason, K;Leahy, DJ
通讯作者：
Leahy, DJ
DOI：
10.1093/protein/gzs024
发表时间：
2012-10
期刊：
Protein engineering, design & selection : PEDS
影响因子：
--
作者：
Kuroda D;Shirai H;Jacobson MP;Nakamura H
通讯作者：
Nakamura H
DOI：
10.2165/00063030-200721030-00002
发表时间：
2007
期刊：
BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy
影响因子：
--
作者：
Gershoni JM;Roitburd-Berman A;Siman-Tov DD;Tarnovitski Freund N;Weiss Y
通讯作者：
Weiss Y
影响因子：
2.7
作者：
Rapberger, Ronald;Lukas, Arno;Mayer, Bernd
通讯作者：
Mayer, Bernd