General Prediction of Peptide-MHC Binding Modes Using Incremental Docking: A Proof of Concept.
General Prediction of Peptide-MHC Binding Modes Using Incremental Docking: A Proof of Concept.
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DOI：
10.1038/s41598-018-22173-4
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发表时间：
2018-03-12
影响因子：
4.6
通讯作者：
Kavraki LE
中科院分区：
文献类型：
--
作者：
Antunes DA;Devaurs D;Moll M;Lizée G;Kavraki LE
I类主要组织相容性复合体（MHC）能够结合源自细胞内蛋白质的肽段，并将它们展示在细胞表面。T细胞对这些肽 - MHC（pMHC）复合物的识别是细胞免疫的基石，能够清除受感染的细胞或肿瘤细胞。基于T细胞的癌症免疫疗法利用了这一机制，可极大地受益于pMHC复合物的结构分析。已经进行了若干尝试利用分子对接进行此类分析，但即使是最先进的对接工具，pMHC结构仍然极具挑战性。为了克服这些限制，我们描述了一种增量元对接方法用于pMHC复合物的结构预测。在此背景下应用的先前方法使用特定的约束条件来降低这一预测问题的复杂性，但牺牲了通用性。我们的策略不做任何假设，并且有可能用于预测任何pMHC复合物的结合模式。我们的方法已经在重新对接实验中进行了测试，重现了25种具有晶体结构的pMHC复合物的结合模式。这项研究是一个概念验证，即增量对接策略能够实现pMHC复合物的通用几何结构预测，在针对癌症或传染病的免疫疗法中具有潜在应用。
The class I major histocompatibility complex (MHC) is capable of binding peptides derived from intracellular proteins and displaying them at the cell surface. The recognition of these peptide-MHC (pMHC) complexes by T-cells is the cornerstone of cellular immunity, enabling the elimination of infected or tumoral cells. T-cell-based immunotherapies against cancer, which leverage this mechanism, can greatly benefit from structural analyses of pMHC complexes. Several attempts have been made to use molecular docking for such analyses, but pMHC structure remains too challenging for even state-of-the-art docking tools. To overcome these limitations, we describe the use of an incremental meta-docking approach for structural prediction of pMHC complexes. Previous methods applied in this context used specific constraints to reduce the complexity of this prediction problem, at the expense of generality. Our strategy makes no assumption and can potentially be used to predict binding modes for any pMHC complex. Our method has been tested in a re-docking experiment, reproducing the binding modes of 25 pMHC complexes whose crystal structures are available. This study is a proof of concept that incremental docking strategies can lead to general geometry prediction of pMHC complexes, with potential applications for immunotherapy against cancer or infectious diseases.
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影响因子：
3.7
作者：
Chang MW;Ayeni C;Breuer S;Torbett BE
通讯作者：
Torbett BE
影响因子：
64.5
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Birnbaum ME;Mendoza JL;Sethi DK;Dong S;Glanville J;Dobbins J;Ozkan E;Davis MM;Wucherpfennig KW;Garcia KC
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Gfellert, David
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