Sankar Kannan, Liu Jie, Wang Yuan, Jernigan Robert L
Bioinformatics and Computational Biology Program, Iowa State University, Ames, Iowa 50011, USA.
J Chem Phys. 2015 Dec 28;143(24):243153. doi: 10.1063/1.4937940.
Predicting conformational changes of proteins is needed in order to fully comprehend functional mechanisms. With the large number of available structures in sets of related proteins, it is now possible to directly visualize the clusters of conformations and their conformational transitions through the use of principal component analysis. The most striking observation about the distributions of the structures along the principal components is their highly non-uniform distributions. In this work, we use principal component analysis of experimental structures of 50 diverse proteins to extract the most important directions of their motions, sample structures along these directions, and estimate their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca(2+) adenosine triphosphatase (SERCA), as examples, we show that such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, we also show that Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes.
为了全面理解蛋白质的功能机制，需要预测蛋白质的构象变化。鉴于相关蛋白质组中存在大量可用结构，现在可以通过主成分分析直接可视化构象簇及其构象转变。关于结构沿主成分的分布，最显著的观察结果是它们的分布极不均匀。在这项工作中，我们对50种不同蛋白质的实验结构进行主成分分析，以提取其运动的最重要方向，沿这些方向对结构进行采样，并通过结合基于知识的势和从弹性网络模型计算出的熵来估计其自由能景观。当这些产生的运动在其粗粒度自由能景观上可视化时，构象途径的基础就变得显而易见了。以三种经过充分研究的蛋白质——T4溶菌酶、血清白蛋白和肌质网Ca(2+)三磷酸腺苷酶（SERCA）为例，我们表明这种构象变化的自由能景观为功能动力学提供了有意义的见解，并暗示了不同构象状态之间的转变途径。作为另一个例子，我们还表明，在HIV-1蛋白酶的粗粒度景观上进行的蒙特卡罗模拟可以直接产生力驱动构象变化的途径。
