Barcelona Supercomputing Center (BSC), Barcelona, Spain.
Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
Methods Mol Biol. 2023;2673:211-226. doi: 10.1007/978-1-0716-3239-0_15.
T cell epitopes presented on the surface of mammalian cells are subjected to a complex network of antigen processing and presentation. Among them, C-terminal antigen processing constitutes one of the main bottlenecks for the generation of epitopes, as it defines the C-terminal end of the final epitope and delimits the peptidome that will be presented downstream. Previously (Amengual-Rigo and Guallar, Sci Rep 111(11):1-8, 2021), we demonstrated that NetCleave stands out as one of the best algorithms for the prediction of C-terminal processing, which in its turn can be crucial to design peptide-based vaccination strategies. In this chapter, we provide a pipeline to exploit the full capabilities of NetCleave, an open-source and retrainable algorithm for predicting the C-terminal antigen processing for the MHC-I and MHC-II pathways.
哺乳动物细胞表面呈现的 T 细胞表位受到复杂的抗原加工和呈递网络的影响。其中，C 末端抗原加工是产生表位的主要瓶颈之一，因为它定义了最终表位的 C 末端，并限制了下游呈现的肽组。此前（Amengual-Rigo 和 Guallar，Sci Rep 111(11):1-8, 2021），我们证明 NetCleave 是预测 C 末端加工的最佳算法之一，这对于设计基于肽的疫苗策略至关重要。在本章中，我们提供了一个利用 NetCleave 全部功能的流程，NetCleave 是一种用于预测 MHC-I 和 MHC-II 途径的 C 末端抗原加工的开源和可重新训练算法。
