Structural prediction of peptides binding to MHC class I molecules
Structural prediction of peptides binding to MHC class I molecules
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DOI：
10.1002/prot.20870
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发表时间：
2006-04-01
影响因子：
2.9
通讯作者：
Haworth, IS
中科院分区：
文献类型：
--
作者：
Bui, HH;Schiewe, AJ;Haworth, IS
肽与一类主要组织相容性复合体（MHCI）分子的结合是免疫反应的关键步骤，这种相互作用的结构细节在肽疫苗的设计中具有重要意义。基于一级序列的算法已经成功地预测了MHCI的潜在抗原肽，但这种算法的准确性有限，并且没有提供结构信息。在这里，我们提出了一种算法PePSSI（通过溶剂化界面预测肽- mhc结构），用于预测肽与MHCI分子HLA-A2结合时的结构。该算法结合了肽主结构的采样和MHC侧链的灵活运动，在其他预测算法中，它在肽-MHC界面上结合了明确的水分子，是独一无二的。在算法的初始测试中，使用PePSSI来预测与HILA-A2结合的8个肽的构象，其中x射线数据可用。这些肽的预测构象和x射线构象的比较得出RMSD值在1.301和2.475埃之间。然后使用PePSSI预测了266个已知与hla - a2结合亲和力的肽的结合构象。对这些肽- hla - a2构象的结构分析表明，肽的结合亲和力与肽- mhc接触数呈正相关，与界面水分子数负相关。这些结果与HLA-A2肽结合界面的相对疏水结合性质一致。总之，PePSSI能够快速准确地预测肽- mhc结合构象，从而可以估计mhci -肽的结合亲和力。
Peptide binding to class I major histocompatibility complex (MHCI) molecules is a key step in the immune response and the structural details of this interaction are of importance in the design of peptide vaccines. Algorithms based on primary sequence have had success in predicting potential antigenic peptides for MHCI, but such algorithms have limited accuracy and provide no structural information. Here, we present an algorithm, PePSSI (peptide-MHC prediction of structure through solvated interfaces), for the prediction of peptide structure when bound to the MHCI molecule, HLA-A2. The algorithm combines sampling of peptide backbone conformations and flexible movement of MHC side chains and is unique among other prediction algorithms in its incorporation of explicit water molecules at the peptide-MHC interface. In an initial test of the algorithm, PePSSI was used to predict the conformation of eight peptides bound to HILA-A2, for which X-ray data are available. Comparison of the predicted and X-ray conformations of these peptides gave RMSD values between 1.301 and 2.475 angstrom. Binding conformations of 266 peptides with known binding affinities for HILA-A2 were then predicted using PePSSI. Structural analyses of these peptide-HLA-A2 conformations showed that peptide binding affinity is positively correlated with the number of peptide-MHC contacts and negatively correlated with the number of interfacial water molecules. These results are consistent with the relatively hydrophobic binding nature of the HLA-A2 peptide binding interface. In summary, PePSSI is capable of rapid and accurate prediction of peptide-MHC binding conformations, which may in turn allow estimation of MHCI-peptide binding affinity.