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张量弹性网络模型在蛋白质动力学中的应用:各向异性网络模型与键弯曲和扭转弹性的结合。

Tensorial elastic network model for protein dynamics: integration of the anisotropic network model with bond-bending and twist elasticities.

机构信息

The Stella and Avram Goren-Goldstein Department of Biotechnology Engineering, Ben-Gurion University of The Negev, Beer Sheva 84105, Israel.

出版信息

Proteins. 2012 Dec;80(12):2692-700. doi: 10.1002/prot.24153. Epub 2012 Aug 21.

Abstract

We present a tensorial elastic network model (TNM) to describe the equilibrium fluctuations of proteins near their native fold structure. The model combines the anisotropic network model (ANM), bond bending elasticity, and backbone twist elasticity, and can predict both the isotropic fluctuations, similar to the Gaussian network model (GNM), and anisotropic fluctuations, similar to the ANM. TNM performs equally well for B-factor predictions as GNM and predicts the anisotropy of B-factors better than ANM. The model also outperforms the ANM in its predictability of the complete anisotropic displacement parameters.

摘要

我们提出了一种张量弹性网络模型(TNM)来描述蛋白质在天然折叠结构附近的平衡波动。该模型结合了各向异性网络模型(ANM)、键弯曲弹性和骨架扭转弹性,既能预测各向同性波动(类似于高斯网络模型(GNM)),也能预测各向异性波动(类似于 ANM)。TNM 在 B 因子预测方面的表现与 GNM 相当,并且比 ANM 更好地预测了 B 因子的各向异性。该模型在预测完整各向异性位移参数方面也优于 ANM。

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