Khan Javed Mohammed, Ranganathan Shoba
Department of Chemistry and Biomolecular Sciences and ARC Center of Excellence in Bioinformatics, Macquarie University, NSW 2109, Australia.
Immunome Res. 2010 Sep 27;6 Suppl 1(Suppl 1):S2. doi: 10.1186/1745-7580-6-S1-S2.
Identification of antigenic peptide epitopes is an essential prerequisite in T cell-based molecular vaccine design. Computational (sequence-based and structure-based) methods are inexpensive and efficient compared to experimental approaches in screening numerous peptides against their cognate MHC alleles. In structure-based protocols, suited to alleles with limited epitope data, the first step is to identify high-binding peptides using docking techniques, which need improvement in speed and efficiency to be useful in large-scale screening studies. We present pDOCK: a new computational technique for rapid and accurate docking of flexible peptides to MHC receptors and primarily apply it on a non-redundant dataset of 186 pMHC (MHC-I and MHC-II) complexes with X-ray crystal structures.
We have compared our docked structures with experimental crystallographic structures for the immunologically relevant nonameric core of the bound peptide for MHC-I and MHC-II complexes. Primary testing for re-docking of peptides into their respective MHC grooves generated 159 out of 186 peptides with Cα RMSD of less than 1.00 Å, with a mean of 0.56 Å. Amongst the 25 peptides used for single and variant template docking, the Cα RMSD values were below 1.00 A for 23 peptides. Compared to our earlier docking methodology, pDOCK shows upto 2.5 fold improvement in the accuracy and is ~60% faster. Results of validation against previously published studies represent a seven-fold increase in pDOCK accuracy.
The limitations of our previous methodology have been addressed in the new docking protocol making it a rapid and accurate method to evaluate pMHC binding. pDOCK is a generic method and although benchmarks against experimental structures, it can be applied to alleles with no structural data using sequence information. Our outcomes establish the efficacy of our procedure to predict highly accurate peptide structures permitting conformational sampling of the peptide in MHC binding groove. Our results also support the applicability of pDOCK for in silico identification of promiscuous peptide epitopes that are relevant to higher proportions of human population with greater propensity to activate T cells making them key targets for the design of vaccines and immunotherapies.
鉴定抗原肽表位是基于T细胞的分子疫苗设计的必要前提。与实验方法相比，计算方法（基于序列和基于结构）在针对其同源MHC等位基因筛选大量肽时成本低廉且效率高。在适用于表位数据有限的等位基因的基于结构的方案中，第一步是使用对接技术鉴定高结合肽，而对接技术在速度和效率方面需要改进才能用于大规模筛选研究。我们提出了pDOCK：一种用于将柔性肽快速准确地对接至MHC受体的新计算技术，并主要将其应用于具有X射线晶体结构的186个pMHC（MHC-I和MHC-II）复合物的非冗余数据集。
我们将对接结构与MHC-I和MHC-II复合物结合肽的免疫相关九聚体核心的实验晶体结构进行了比较。将肽重新对接至其各自MHC凹槽的初步测试在186个肽中产生了159个Cα均方根偏差（RMSD）小于1.00 Å，平均值为0.56 Å。在用于单模板和变体模板对接的25个肽中，23个肽的Cα RMSD值低于1.00 Å。与我们早期的对接方法相比，pDOCK在准确性上提高了2.5倍，速度快了约60%。与先前发表的研究相比，验证结果表明pDOCK的准确性提高了7倍。
新的对接方案解决了我们先前方法的局限性，使其成为评估pMHC结合的快速准确方法。pDOCK是一种通用方法，尽管是根据实验结构进行基准测试，但它可以使用序列信息应用于没有结构数据的等位基因。我们的结果证实了我们的程序预测高度准确的肽结构的有效性，允许在MHC结合凹槽中对肽进行构象采样。我们的结果还支持pDOCK在计算机模拟鉴定混杂肽表位方面的适用性，这些表位与更高比例的人群相关，更倾向于激活T细胞，使其成为疫苗和免疫疗法设计的关键靶点。
