Department of Statistics, University of Oxford, Oxford OX1 3LB, UK.
Data and Computational Sciences, GlaxoSmithKline Research and Development, Stevenage SG1 2NY, UK.
Bioinformatics. 2020 Jun 1;36(11):3580-3581. doi: 10.1093/bioinformatics/btaa194.
T-cell receptors (TCRs) are immune proteins that primarily target peptide antigens presented by the major histocompatibility complex. They tend to have lower specificity and affinity than their antibody counterparts, and their binding sites have been shown to adopt multiple conformations, which is potentially an important factor for their polyspecificity. None of the current TCR-modelling tools predict this variability which limits our ability to accurately predict TCR binding.
We present TCRBuilder, a multi-state TCR structure prediction tool. Given a paired αβTCR sequence, TCRBuilder returns a model or an ensemble of models covering the potential conformations of the binding site. This enables the analysis of structurally driven polyspecificity in TCRs, which is not possible with existing tools.
http://opig.stats.ox.ac.uk/resources.
Supplementary data are available at Bioinformatics online.
T 细胞受体 (TCRs) 是主要针对主要组织相容性复合体呈递的肽抗原的免疫蛋白。它们的特异性和亲和力通常低于抗体对应物，并且已经表明它们的结合位点可以采用多种构象，这可能是其多特异性的一个重要因素。目前没有任何 TCR 建模工具可以预测这种可变性，这限制了我们准确预测 TCR 结合的能力。
我们提出了 TCRBuilder，这是一种多态 TCR 结构预测工具。给定一对 αβTCR 序列，TCRBuilder 返回一个或一组模型，涵盖结合位点的潜在构象。这使得能够分析 TCR 中的结构驱动的多特异性，这是现有工具所不可能的。
http://opig.stats.ox.ac.uk/resources。
补充数据可在“Bioinformatics”在线获取。
