SKKU Advanced Institute of Nanotechnology-SAINT, Sungkyunkwan University, Suwon 440-746, Korea.
Protein Sci. 2013 May;22(5):605-13. doi: 10.1002/pro.2244. Epub 2013 Mar 18.
An elastic network model (ENM), usually Cα coarse-grained one, has been widely used to study protein dynamics as an alternative to classical molecular dynamics simulation. This simple approach dramatically saves the computational cost, but sometimes fails to describe a feasible conformational change due to unrealistically excessive spring connections. To overcome this limitation, we propose a mass-weighted chemical elastic network model (MWCENM) in which the total mass of each residue is assumed to be concentrated on the representative alpha carbon atom and various stiffness values are precisely assigned according to the types of chemical interactions. We test MWCENM on several well-known proteins of which both closed and open conformations are available as well as three α-helix rich proteins. Their normal mode analysis reveals that MWCENM not only generates more plausible conformational changes, especially for closed forms of proteins, but also preserves protein secondary structures thus distinguishing MWCENM from traditional ENMs. In addition, MWCENM also reduces computational burden by using a more sparse stiffness matrix.
弹性网络模型（ENM），通常是 Cα 粗粒模型，已被广泛用于研究蛋白质动力学，作为经典分子动力学模拟的替代方法。这种简单的方法大大节省了计算成本，但由于不切实际的过度弹簧连接，有时无法描述可行的构象变化。为了克服这一限制，我们提出了一种质量加权化学弹性网络模型（MWCENM），其中每个残基的总质量被假定集中在代表性的α碳原子上，并且根据化学相互作用的类型精确分配各种刚度值。我们在几个著名的蛋白质上测试了 MWCENM，这些蛋白质既有封闭构象又有开放构象，还有三个富含α-螺旋的蛋白质。它们的正常模式分析表明，MWCENM 不仅产生了更合理的构象变化，特别是对于蛋白质的封闭形式，而且还保留了蛋白质的二级结构，从而将 MWCENM 与传统的 ENM 区分开来。此外，MWCENM 还通过使用更稀疏的刚度矩阵来减少计算负担。
