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Transition modes in Ising networks: an approximate theory for macromolecular recognition.

机译:Ising网络中的跃迁模式:大分子识别的近似理论。

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摘要

For a statistical lattice, or Ising network, composed of N identical units existing in two possible states, 0 and 1, and interacting according to a given geometry, a set of values can be found for the mean free energy of the 0-->1 transition of a single unit. Each value defines a transition mode in an ensemble of nu N = 3N - 2N possible values and reflects the role played by intermediate states in shaping the energetics of the system as a whole. The distribution of transition modes has a number of intriguing properties. Some of them apply quite generally to any Ising network, regardless of its dimension, while others are specific for each interaction geometry and dimensional embedding and bear on fundamental aspects of analytical number theory. The landscape of transition modes encapsulates all of the important thermodynamic properties of the network. The free energy terms defining the partition function of the system can be derived from the modes by simple transformations. Classical mean-field expressions can be obtained from consideration of the properties of transition modes in a rather straightforward way. The results obtained in the analysis of the transition mode distributions have been used to develop an approximate treatment of the problem of macromolecular recognition. This phenomenon is modeled as a cooperative process that involves a number of recognition subsites across an interface generated by the binding of two macromolecular components. The distribution of allowed binding free energies for the system is shown to be a superposition of Gaussian terms with mean and variance determined a priori by the theory. Application to the analysis of the biologically interaction of thrombin with hirudin has provided some useful information on basic aspects of the interaction, such as the number of recognition subsites involved and the energy balance for binding and cooperative coupling among them. Our results agree quite well with information derived independently from analysis of the crystal structure of the thrombin-hirudin complex.
机译:对于一个统计晶格或Ising网络,它由N个相同的单元组成,它们存在于两个可能的状态0和1中,并且根据给定的几何形状相互作用,可以找到一组值的平均值为0->单个单元的1个转换。每个值在nu N = 3N-2N个可能值的集合中定义了一个过渡模式,并反映了中间状态在塑造系统整体能量方面所扮演的角色。过渡模式的分布具有许多吸引人的属性。它们中的一些相当普遍地适用于任何Ising网络,而不论其尺寸如何,而另一些则特定于每种相互作用的几何形状和尺寸嵌入,并涉及解析数论的基本方面。过渡模式的范围封装了网络的所有重要热力学性质。可以通过简单的转换从模式中得出定义系统分配函数的自由能项。可以通过相当简单的方式考虑过渡模式的属性来获得经典的平均场表达式。在过渡模式分布的分析中获得的结果已用于开发大分子识别问题的近似处理。将此现象建模为一个协作过程,该过程涉及通过两个大分子成分的结合生成的跨界面的多个识别子位点。系统的允许结合自由能的分布显示为高斯项的叠加,均值和方差由理论先验确定。在凝血酶与水hi素的生物相互作用分析中的应用为相互作用的基本方面提供了一些有用的信息,例如涉及的识别亚位点的数量以及它们之间结合和协同偶联的能量平衡。我们的结果与从凝血酶-水ud素复合物的晶体结构分析中独立得出的信息非常吻合。

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