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A new ensemble coevolution system for detecting HIV-1 protein coevolution

机译:用于检测HIV-1蛋白质协同进化的新型整体协同进化系统

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摘要

BackgroundA key challenge in the field of HIV-1 protein evolution is the identification of coevolving amino acids at the molecular level. In the past decades, many sequence-based methods have been designed to detect position-specific coevolution within and between different proteins. However, an ensemble coevolution system that integrates different methods to improve the detection of HIV-1 protein coevolution has not been developed.ResultsWe integrated 27 sequence-based prediction methods published between 2004 and 2013 into an ensemble coevolution system. This system allowed combinations of different sequence-based methods for coevolution predictions. Using HIV-1 protein structures and experimental data, we evaluated the performance of individual and combined sequence-based methods in the prediction of HIV-1 intra- and inter-protein coevolution. We showed that sequence-based methods clustered according to their methodology, and a combination of four methods outperformed any of the 27 individual methods. This four-method combination estimated that HIV-1 intra-protein coevolving positions were mainly located in functional domains and physically contacted with each other in the protein tertiary structures. In the analysis of HIV-1 inter-protein coevolving positions between Gag and protease, protease drug resistance positions near the active site mostly coevolved with Gag cleavage positions (V128, S373-T375, A431, F448-P453) and Gag C-terminal positions (S489-Q500) under selective pressure of protease inhibitors.ConclusionsThis study presents a new ensemble coevolution system which detects position-specific coevolution using combinations of 27 different sequence-based methods. Our findings highlight key coevolving residues within HIV-1 structural proteins and between Gag and protease, shedding light on HIV-1 intra- and inter-protein coevolution.ReviewersThis article was reviewed by Dr. Zoltán Gáspári.
机译:背景技术HIV-1蛋白进化领域的一个关键挑战是在分子水平上鉴定共同进化的氨基酸。在过去的几十年中,已经设计了许多基于序列的方法来检测不同蛋白质内部和之间的位置特异性协同进化。然而,尚未开发出集成了多种方法以改善HIV-1蛋白协同进化检测的整体协同进化系统。结果我们将2004年至2013年间发布的27种基于序列的预测方法整合到了整体协同进化系统中。该系统允许组合使用不同的基于序列的方法进行协同进化预测。使用HIV-1蛋白质结构和实验数据,我们评估了单独和组合基于序列的方法在预测HIV-1蛋白质内和蛋白质间协同进化中的性能。我们显示了基于序列的方法根据其方法进行聚类,并且四种方法的组合优于27种单独方法中的任何一种。这种四法相结合的方法估计,HIV-1蛋白质内协同进化的位置主要位于功能域,并在蛋白质三级结构中彼此物理接触。在分析Gag和蛋白酶之间的HIV-1蛋白间共同进化位置时,活性位点附近的蛋白酶抗药性位置大多与Gag裂解位置(V128,S373-T375,A431,F448-P453)和Gag C端位置共同进化(S489-Q500)在蛋白酶抑制剂的选择性压力下。结论本研究提出了一种新的整体协同进化系统,该系统可使用27种不同的基于序列的方法的组合检测位置特异性协同进化。我们的发现突出了HIV-1结构蛋白内部以及Gag与蛋白酶之间的关键协同进化残基,为HIV-1蛋白内部和蛋白间协同进化提供了亮点。评论者本文由ZoltánGáspári博士进行了评论。

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