TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires.
TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires.
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DOI：
10.1371/journal.pone.0026301
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发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
Michielin O
中科院分区：
文献类型：
--
作者：
Leimgruber A;Ferber M;Irving M;Hussain-Kahn H;Wieckowski S;Derré L;Rufer N;Zoete V;Michielin O
TCRep 3D是一种基于同源性和从头算建模的自动化系统方法，用于TCR-肽-MHC I类结构预测。从以前的研究中可以看出，它已被相当广泛地推广到适用于大型TCR库。首先，通过针对TCR Vα和Vβ链的数据库的序列比对策略自动识别靶序列的互补决定区的位置。基于结构的比对确保了CDR 3环的自动化鉴定。然后，在基于模拟退火协议的从头算方法中，在复合物的环境中对CDR进行建模。在该步骤期间，应用二面角约束以驱动CDR 1和CDR 2环朝向它们的典型构象，如Al-Lazikani et.我们开发了一种新的自动化算法，该算法确定了额外的约束，以迭代地收敛于TCR构象，从而与pMHC形成频繁的氢键。我们证明了我们的方法在预测相关CDR构象方面优于流行的评分方法（Anolea，Dope和Modeller）。最后，这种建模方法已成功地应用于实验确定的识别NY-ESO-1癌症睾丸抗原的TCR序列。该分析揭示了通过在所有CDR 3 β序列中存在单个保守氨基酸来选择TCR的机制。计算机模拟预测的重要结构修饰和该氨基酸突变后实验结合亲和力的相关急剧损失显示了预测结构与其生物活性之间的良好对应性。据我们所知，这是第一个系统的方法，开发了大型TCR库结构建模。
TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.
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