A transformer-based model to predict peptide-HLA class I binding and optimize mutated peptides for vaccine design
A transformer-based model to predict peptide-HLA class I binding and optimize mutated peptides for vaccine design
复制标题
DOI：
10.1038/s42256-022-00459-7
复制
发表时间：
2022-03-01
影响因子：
23.8
通讯作者：
Wei, Dong-Qing
中科院分区：
文献类型：
--
作者：
Chu, Yanyi;Zhang, Yan;Wei, Dong-Qing
人类白细胞抗原（human leukocyte antigen，HLA）能识别并结合外源肽段，将其呈递给特异性免疫细胞，从而启动免疫应答。肽和HLA（pHLA）结合的计算预测可以加速免疫原性肽的筛选并促进疫苗设计。然而，缺乏自动程序来优化与目标HLA等位基因具有更高亲和力的突变肽。在这里，为了填补这一空白，我们开发的transMut框架组成的transPHLA的pHLA结合预测和自动优化的突变肽（AOMP）程序，它可以推广到任何生物分子的结合和突变任务。首先，通过构建基于转化子的模型来预测pHLA结合，开发了TransPHLA，其在pHLA结合预测和新抗原和人乳头瘤病毒疫苗鉴定方面上级先前的14种方法。对于疫苗设计，然后通过利用由TransPHLA生成的注意力分数来开发AOMP程序，以自动优化对靶HLA等位基因具有更高亲和力并且与源肽具有高同源性的突变肽。人类白细胞抗原（HLA）复合物在构建免疫应答中起着重要作用，但很难预测哪些肽将与之结合。Chu等人提出了一种基于transformer的方法来鉴定哪些肽与HLA具有高结合亲和力，这一任务也可以转化为其他结合问题。
Human leukocyte antigen (HLA) can recognize and bind foreign peptides to present them to specialized immune cells, then initiate an immune response. Computational prediction of the peptide and HLA (pHLA) binding can speed up immunogenic peptide screening and facilitate vaccine design. However, there is a lack of an automatic program to optimize mutated peptides with higher affinity to the target HLA allele. Here, to fill this gap, we develop the TransMut framework-composed of TransPHLA for pHLA binding prediction and an automatically optimized mutated peptides (AOMP) program-which can be generalized to any binding and mutation task of biomolecules. First, TransPHLA is developed by constructing a transformer-based model to predict pHLA binding, which is superior to 14 previous methods on pHLA binding prediction and neoantigen and human papilloma virus vaccine identification. For vaccine design, the AOMP program is then developed by exploiting the attention scores generated by TransPHLA to automatically optimize mutated peptides with higher affinity to the target HLA allele and with high homology to the source peptide. The proposed framework may automatically generate potential peptide vaccines for experimentalists.The human leukocyte antigen (HLA) complex plays an important role in building an immune response, but it is hard to predict which peptides will bind to it. Chu et al. present a transformer-based approach to identify which peptides have a high binding affinity to HLA, a task that can also be translated to other binding problems.
预测针对化脓性链球菌设计疫苗的混杂T细胞表位。
影响因子：
3
作者：
Ebrahimi S;Mohabatkar H;Behbahani M
通讯作者：
Behbahani M