Normal-modes-based prediction of protein conformational changes guided by distance constraints.
Normal-modes-based prediction of protein conformational changes guided by distance constraints.
复制标题
DOI：
10.1529/biophysj.104.058453
复制
发表时间：
2005-05
影响因子：
3.4
通讯作者：
Wenjun Zheng;B. Brooks
中科院分区：
文献类型：
--
作者：
Wenjun Zheng;B. Brooks
基于弹性网络模型，我们开发了一种新的方法，预测蛋白质复合物的构象变化给定其初始状态的晶体结构连同一个小的成对的距离约束的最终状态。预测的构象变化，这是从弹性网络模型求解的多个低频正常模式的线性组合，被计算为由对系统哈密顿量的扰动引起的响应位移，该系统哈密顿量包含给定的距离约束。对于一系列测试用例，我们发现当仅使用少数成对约束时（</=10），计算的响应位移与测量的构象变化显著重叠。该方法的性能也被证明是强大的对成对距离约束和错误的值的不同选择。这种方法，如果提供实验推导的距离约束（例如，从NMR或其他光谱测量），可以应用于分析蛋白质构象变化的瞬态。
Based on the elastic network model, we develop a novel method that predicts the conformational change of a protein complex given its initial-state crystal structure together with a small set of pairwise distance constraints for the end state. The predicted conformational change, which is a linear combination of multiple low-frequency normal modes that are solved from the elastic network model, is computed as a response displacement induced by a perturbation to the system Hamiltonian that incorporates the given distance constraints. For a list of test cases, we find that the computed response displacement overlaps significantly with the measured conformational changes, when only a handful of pairwise constraints are used (</=10). The performance of this method is also shown to be robust against different choices of pairwise distance constraints and errors in their values. This method, if supplied with the experimentally derived distance constraints (for example, from NMR or other spectroscopic measurements), can be applied to the analysis of protein conformational changes toward transient states.