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Ranking Beta Sheet Topologies of Proteins

机译:排名蛋白质的β胸拓

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One of the challenges of protein structure prediction is to identify long-range interactions between amino acids. To reliably predict such interactions, we enumerate, score and rank all β-topologies (partitions of β-strands into sheets, orderings of strands within sheets and orientations of paired strands) of a given protein. We show that the β-topology corresponding to the native structure is, with high probability, among the top-ranked. Since full enumeration is very time-consuming, we also suggest a method to deal with proteins with many β-strands. The results reported in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. The top-ranked β-topologies can be used to find initial conformations from which conformational searches can be started. They can also be used to filter decoys by removing those with poorly assembled β-sheets, and finally they can be relevant in contact prediction methods.
机译:蛋白质结构预测的挑战之一是鉴定氨基酸之间的远程相互作用。为了可靠地预测这种相互作用,我们枚举,得分和将所有β-拓扑(β-股的分区排序成片材,在给定蛋白的片材和配对链中的片材中的股线的排列)。我们表明,对应于天然结构的β-拓扑是具有很高的概率的β-拓扑。由于完全枚举非常耗时,我们还建议一种处理具有许多β股的蛋白质的方法。本文报道的结果对基于诱饵发电的AB初始蛋白质结构预测方法非常相关。排名排名级β-拓扑可以用于找到可以启动构象搜索的初始构象。它们还可用于通过去除具有较差的β-薄片的那些来过滤诱饵,最后它们可以以接触预测方法相关。

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