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结构与动力学的相互作用:来自 HIV-1 逆转录酶晶体结构研究的见解。

The interplay of structure and dynamics: insights from a survey of HIV-1 reverse transcriptase crystal structures.

机构信息

Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York.

出版信息

Proteins. 2013 Oct;81(10):1792-801. doi: 10.1002/prot.24325. Epub 2013 Aug 16.

Abstract

HIV-1 reverse transcriptase (RT) is a critical drug target for HIV treatment, and understanding the exact mechanisms of its function and inhibition would significantly accelerate the development of new anti-HIV drugs. It is well known that structure plays a critical role in protein function, but for RT, structural information has proven to be insufficient-despite enormous effort-to explain the mechanism of inhibition and drug resistance of non-nucleoside RT inhibitors. We hypothesize that the missing link is dynamics, information about the motions of the system. However, many of the techniques that give the best information about dynamics, such as solution nuclear magnetic resonance and molecular dynamics simulations, cannot be easily applied to a protein as large as RT. As an alternative, we combine elastic network modeling with simultaneous hierarchical clustering of structural and dynamic data. We present an extensive survey of the dynamics of RT bound to a variety of ligands and with a number of mutations, revealing a novel mechanism for drug resistance to non-nucleoside RT inhibitors. Hydrophobic core mutations restore active-state motion to multiple functionally significant regions of HIV-1 RT. This model arises out of a combination of structural and dynamic information, rather than exclusively from one or the other.

摘要

HIV-1 逆转录酶(RT)是治疗 HIV 的关键药物靶点,深入了解其功能和抑制的确切机制将极大地促进新型抗 HIV 药物的研发。众所周知,结构在蛋白质功能中起着至关重要的作用,但对于 RT,尽管付出了巨大的努力,结构信息仍不足以解释非核苷类 RT 抑制剂的抑制和耐药机制。我们假设缺失的环节是动态信息,即系统运动的信息。然而,许多能够提供关于动力学的最佳信息的技术,如溶液核磁共振和分子动力学模拟,都不能轻易地应用于像 RT 这样大的蛋白质。作为替代方法,我们将弹性网络建模与结构和动态数据的分层聚类相结合。我们对与多种配体和多种突变结合的 RT 的动力学进行了广泛的研究,揭示了一种针对非核苷类 RT 抑制剂的耐药性的新机制。疏水核心突变使 HIV-1 RT 的多个功能重要区域恢复到活跃状态的运动。该模型是结构和动态信息相结合的结果,而不仅仅是来自于其中之一。

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本文引用的文献

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