Institute of Bioinformatics and Structural Biology, National Tsing-Hua University, Hsinchu, Taiwan.
Biophys J. 2011 Apr 6;100(7):1784-93. doi: 10.1016/j.bpj.2011.02.033.
In this study, I present a new elastic network model, to our knowledge, that addresses insufficiencies of two conventional models-the Gaussian network model (GNM) and the anisotropic network model (ANM). It has been shown previously that the GNM is not rotation-invariant due to its energy, which penalizes rigid-body rotation (external rotation). As a result, GNM models are found contaminated with rigid-body rotation, especially in the most collective ones. A new model (EPIRM) is proposed to remove such external component in modes. The extracted internal motions result from a potential that penalizes interresidue stretching and rotation in a protein. The new model is shown to pertinently describe crystallographic temperature factors (B-factors) and protein open↔closed transitions. Also, the capability of separating internal and external motions in GNM slow modes permits reexamining important mechanochemical properties in enzyme active sites. The results suggest that catalytic residues stay closer to rigid-body rotation axes than their immediate backbone neighbors. I show that the cumulative density of states for EPIRM and ANM follow different power laws as functions of low-mode frequencies. When using a cutoff distance of 7.5 Å, The cumulative density of states of EPIRM scales faster than that of all-atom normal mode analysis and slower than that of simple lattices.
在这项研究中,我提出了一个新的弹性网络模型,据我们所知,该模型解决了两个传统模型——高斯网络模型(GNM)和各向异性网络模型(ANM)的不足。以前已经表明,由于其能量,GNM 不是旋转不变的,因为它惩罚刚体旋转(外部旋转)。因此,发现 GNM 模型受到刚体旋转的污染,尤其是在最集体的模型中。提出了一种新模型(EPIRM)来去除模式中的这种外部成分。从惩罚蛋白质中残基伸展和旋转的势中提取出内部运动。结果表明,新模型可以很好地描述晶体学温度因子(B 因子)和蛋白质开/关转变。此外,在 GNM 慢模式中分离内部和外部运动的能力允许重新检查酶活性位点中的重要机械化学性质。结果表明,催化残基比其直接的骨架邻居更接近刚体旋转轴。我表明,EPIRM 和 ANM 的态密度累积随低模式频率的函数遵循不同的幂律。当使用 7.5 Å 的截止距离时,EPIRM 的态密度累积比全原子模态分析快,比简单晶格慢。