T细胞表位的鉴定对于深入了解传染病、自身免疫和癌症免疫识别机制非常关键。同时，T细胞表位还为个人疫苗和T细胞治疗提供了目标，包括在癌症免疫治疗等多方面具有很多治疗应用。T细胞表位由显示在主要组织相容性复合物（MHC）分子上的短肽组成。基于质谱（MS）的技术用于分析MHC分子上所显示的肽集合，即所谓的免疫肽组-对于我们理解抗原呈递和MHC配体具有重大影响。一方面，这些技术使研究人员可以直接鉴定出MHC分子上呈递的成千上万个肽段，包括一些引起T细胞识别的肽段。另一方面，这些实验收集到的数据揭示了抗原呈递途径的基本特性，并显著提高了我们预测自然呈递的MHC配体和跨越人类和其他生物中广泛谱的MHC等位基因的T细胞表位的能力。本文回顾了最近计算机领域的发展，在分析实验所确定的免疫肽组的基础上，利用这些数据来改善我们理解抗原呈递和MHC结合特异性以及预测MHC配位体的能力。我们还进一步讨论了最新方法的优点和局限性，以超越抗原呈递的预测，并解决预测T细胞受体识别和免疫原性的挑战。 © 2023作者版权所有。 由Elsevier Ltd.出版。保留所有权利。

The identification of T-cell epitopes is key for a complete molecular understanding of immune recognition mechanisms in infectious diseases, autoimmunity and cancer. T-cell epitopes further provide targets for personalized vaccines and T-cell therapy, with several therapeutic applications in cancer immunotherapy and elsewhere. T-cell epitopes consist of short peptides displayed on Major Histocompatibility Complex (MHC) molecules. The recent advances in mass spectrometry (MS) based technologies to profile the ensemble of peptides displayed on MHC molecules - the so-called immunopeptidome - had a major impact on our understanding of antigen presentation and MHC ligands. On the one hand, these techniques enabled researchers to directly identify hundreds of thousands of peptides presented on MHC molecules, including some that elicited T-cell recognition. On the other hand, the data collected in these experiments revealed fundamental properties of antigen presentation pathways and significantly improved our ability to predict naturally presented MHC ligands and T-cell epitopes across the wide spectrum of MHC alleles found in human and other organisms. Here we review recent computational developments to analyze experimentally determined immunopeptidomes and harness these data to improve our understanding of antigen presentation and MHC binding specificities, as well as our ability to predict MHC ligands. We further discuss the strengths and limitations of the latest approaches to move beyond predictions of antigen presentation and tackle the challenges of predicting TCR recognition and immunogenicity.Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.