表位
单克隆抗体
计算生物学
抗原
生物
线性表位
互补性(分子生物学)
表位定位
互补决定区
抗体
稳健性(进化)
糖蛋白
对接(动物)
分子生物学
免疫学
遗传学
基因
医学
护理部
作者
Tianyi Qiu,Lu Zhang,Zikun Chen,Yuan Wang,Tiantian Mao,Caicui Wang,Yewei Cun,Genhui Zheng,Dapeng Yan,Mengdi Zhou,Kailin Tang,Zhiwei Cao
摘要
Abstract Identifying the exact epitope positions for a monoclonal antibody (mAb) is of critical importance yet highly challenging to the Ab design of biomedical research. Based on previous versions of SEPPA 3.0, we present SEPPA-mAb for the above purpose with high accuracy and low false positive rate (FPR), suitable for both experimental and modelled structures. In practice, SEPPA-mAb appended a fingerprints-based patch model to SEPPA 3.0, considering the structural and physic-chemical complementarity between a possible epitope patch and the complementarity-determining region of mAb and trained on 860 representative antigen-antibody complexes. On independent testing of 193 antigen-antibody pairs, SEPPA-mAb achieved an accuracy of 0.873 with an FPR of 0.097 in classifying epitope and non-epitope residues under the default threshold, while docking-based methods gave the best AUC of 0.691, and the top epitope prediction tool gave AUC of 0.730 with balanced accuracy of 0.635. A study on 36 independent HIV glycoproteins displayed a high accuracy of 0.918 and a low FPR of 0.058. Further testing illustrated outstanding robustness on new antigens and modelled antibodies. Being the first online tool predicting mAb-specific epitopes, SEPPA-mAb may help to discover new epitopes and design better mAbs for therapeutic and diagnostic purposes. SEPPA-mAb can be accessed at http://www.badd-cao.net/seppa-mab/.
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