建模II类MHC等位基因和预测肽结合的自动化方法

Martin T. Swain, A. J. Brooks, G. Kemp
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引用次数: 11

摘要

提出了一种利用约束逻辑编程选择侧链构象的自动构建II类MHC结构三维模型的方法。由此产生的模型被“肽线”程序所使用,该程序试图从一个蛋白质序列中预测肽,该蛋白质序列将与特定的MHC等位基因紧密结合。该方法采用比较建模方法,基于实验确定的mhc肽结构的模型结构。然而,限制条件被用来缓解打开肽结合槽,使模拟的MHC结构不太适合开始结构中的共结晶肽。初步结果表明,以这种方式构建的MHC模型使肽线程序能够做出与使用实验确定的MHC结构时获得的结果相当的结合预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An automated approach to modelling class II MHC alleles and predicting peptide binding
We present an automated method for constructing 3D models of class II MHC structures that uses constraint logic programming to select side-chain conformations. The resulting models are used by a "peptide threading" program that attempts to predict peptides from a protein sequence that will bind strongly to particular MHC alleles. This method follows a comparative modelling approach in basing the model structures on experimentally determined MHC-peptide structures. However, constraints are used to ease open the peptide binding groove so that the modelled MHC structure is a less specific fit for the co-crystallised peptide in the starting structure. Preliminary results indicate that MHC models that have been constructed in this way enable the peptide threading program to make binding predictions that are comparable with those obtained when using experimentally determined MHC structures.
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