Schuyler Adam D, Chirikjian Gregory S
Department of Mechanical Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA.
J Mol Graph Model. 2004 Jan;22(3):183-93. doi: 10.1016/S1093-3263(03)00158-X.
The ability to infer dynamic motions from an equilibrium (static) conformation of a protein can be essential in establishing structure-function relationships. In particular, the low-frequency motions are of functional interest because statistical mechanics predicts these motions will have the largest amplitudes. In this paper, we address the computational cost of normal mode analysis (NMA) applied to a C(alpha)-based elastic network model (C(alpha)-NMA) and present a new coarse-grained rigid-body-based analysis (cluster-NMA). This new method represents a protein as a collection of rigid bodies interconnected with harmonic potentials. This representation produces reduced degree-of-freedom (DOF) equations of motion (EOMs) which, even in the case of large structures (10(3+) residues), enables the computation of normal modes to be done on a desktop PC. We present the complete theory and analysis of cluster-NMA and also include its application to a variety of structures. The results of the new method are compared with C(alpha)-NMA and it is shown that cluster-NMA produces very good approximations to the lowest modes at a fraction of the computational cost.
从蛋白质的平衡（静态）构象推断动态运动的能力对于建立结构 - 功能关系可能至关重要。特别是，低频运动具有功能相关性，因为统计力学预测这些运动将具有最大的振幅。在本文中，我们探讨了应用于基于Cα的弹性网络模型（Cα - NMA）的简正模式分析（NMA）的计算成本，并提出了一种新的基于粗粒度刚体的分析方法（簇 - NMA）。这种新方法将蛋白质表示为通过谐势相互连接的刚体集合。这种表示产生了自由度（DOF）降低的运动方程（EOMs），即使在大型结构（10³ + 个残基）的情况下，也能够在台式计算机上完成简正模式的计算。我们展示了簇 - NMA的完整理论和分析，并将其应用于各种结构。将新方法的结果与Cα - NMA进行了比较，结果表明簇 - NMA以一小部分计算成本对最低模式产生了非常好的近似。
