T 细胞受体 (TCR) 识别主要组织相容性复合体 (MHC) 分子呈递的肽是适应性免疫系统中的一个基本过程。在分子水平上理解这种识别过程对于基于 TCR 的疗法和疫苗设计至关重要。TCR 多样性和交叉反应性的广泛性质对传统的结构解析提出了挑战。TCR-pMHC 复合物的计算建模提供了一种有效的替代方法。本研究比较了四种通用对接平台（ClusPro、LightDock、ZDOCK 和 HADDOCK）利用不同级别的结合界面信息进行准确 TCR-pMHC 建模的能力。每个平台都在 44 个 TCR-pMHC 对接案例的扩展基准集上进行了测试。总的来说，HADDOCK 表现最好。提供对接策略指导，获取每个平台的最佳模型，供未来研究使用。本研究中使用的 TCR-pMHC 对接案例可从 https://github.com/innate2adaptive/ExpandedBenchmark 下载。
T cell receptor (TCR) recognition of peptides presented by major histocompatibility complex (MHC) molecules is a fundamental process in the adaptive immune system. An understanding of this recognition process at the molecular level is crucial for TCR based therapeutics and vaccine design. The broad nature of TCR diversity and cross-reactivity presents a challenge for traditional structural resolution. Computational modelling of TCR-pMHC complexes offers an efficient alternative. This study compares the ability of four general-purpose docking platforms (ClusPro, LightDock, ZDOCK and HADDOCK) to make use of varying levels of binding interface information for accurate TCR-pMHC modelling. Each platform was tested on an expanded benchmark set of 44 TCR-pMHC docking cases. In general, HADDOCK is shown to be the best performer. Docking strategy guidance is provided to obtain the best models for each platform for future research. The TCR-pMHC docking cases used in this study can be downloaded from https://github.com/innate2adaptive/ExpandedBenchmark.
