Using NMR-derived restraints in combination with molecular dynamics simulations to derive thermodynamic parameters for biomolecular interactions.

使用 NMR 衍生的约束与分子动力学模拟相结合，得出生物分子相互作用的热力学参数。

• 批准号: BB/E014844/1
• 负责人: Steve Homans
• 金额: $ 22.75万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FE014844%2F1
• 关键词: Using; NMR; derived; restraints; combination

Complex biological processes involve the binding of one molecule by another. The binding process can be thought of as a 'shape' problem, whereby the strength of binding depends critically on shape complementarity between the ligand and the binding pocket on the protein. However, the binding process is more complicated than this, since it is also determined by the extent of dynamics ('floppiness') of the interacting partners. A valuable technique to measure the contribution of protein dynamics to binding concerns high-resolution nuclear magnetic resonance (NMR) relaxation-time measurements. However, the intepretation of such measurements requires some knowledge of the nature of the molecular motions, and in the past it has been common practice to assume a simplified model for these motions. Here, we propose to make use of theoretical molecular dynamics simulations which are restrained by the experimental NMR data. Such simulations will offer a much more realistic picture of the motional processes that take place in the protein before and after ligand binding, and will permit a more accurate quantitation of the dynamic factors that influence the binding process. Such information is of significant importance in the context of structure-based discovery of lead compounds for novel drugs.

复杂的生物过程包括一个分子与另一个分子的结合。结合过程可以被认为是一个“形状”问题，因此结合的强度主要取决于配体和蛋白质结合袋之间的形状互补性。然而，结合过程比这更复杂，因为它也是由相互作用伙伴的动态程度（“软性”）决定的。高分辨率核磁共振弛豫时间测量是测量蛋白质动力学对结合的贡献的一种有价值的技术。然而，这种测量的解释需要对分子运动的本质有一定的了解，在过去，通常的做法是假设这些运动的简化模型。在此，我们建议利用受实验核磁共振数据限制的理论分子动力学模拟。这样的模拟将为配体结合前后蛋白质中发生的运动过程提供更真实的画面，并将允许对影响结合过程的动态因素进行更准确的定量。这些信息在基于结构的新药先导化合物发现的背景下具有重要意义。