Department of Biotechnology, Faculty of Applied Sciences, UCSI University, Kuala Lumpur, Malaysia.
Methods Mol Biol. 2020;2131:213-228. doi: 10.1007/978-1-0716-0389-5_10.
Discovery of tumor antigenic epitopes is important for cancer vaccine development. Such epitopes can be designed and modified to become more antigenic and immunogenic in order to overcome immunosuppression towards the native tumor antigen. In silico-guided modification of epitope sequences allows predictive discrimination of those that may be potentially immunogenic. Therefore, only candidates predicted with high antigenicity will be selected, constructed, and tested in the lab. Here, we described the employment of in silico tools using a multiparametric approach to assess both potential T-cell epitopes (MHC class I/II binding) and B-cell epitopes (hydrophilicity, surface accessibility, antigenicity, and linear epitope). A scoring and ranking system based on these parameters was developed to shortlist potential mimotope candidates for further development as peptide cancer vaccines.
发现肿瘤抗原表位对于癌症疫苗的开发非常重要。这些表位可以被设计和修饰,以提高其抗原性和免疫原性,从而克服对天然肿瘤抗原的免疫抑制。基于计算机的表位序列修饰允许预测性地鉴别那些可能具有免疫原性的表位。因此,只有那些具有高抗原性的候选者才会被选择出来,在实验室中构建和测试。在这里,我们描述了使用多参数方法结合计算机工具来评估潜在的 T 细胞表位(MHC Ⅰ/Ⅱ类结合)和 B 细胞表位(亲水性、表面可及性、抗原性和线性表位)。我们开发了一个基于这些参数的评分和排名系统,以筛选潜在的模拟表位候选物,进一步开发为肽类癌症疫苗。