Berjanskii Mark V, Wishart David S
Department of Computing Science, University of Alberta, Edmonton, AB, Canada.
J Biomol NMR. 2008 Jan;40(1):31-48. doi: 10.1007/s10858-007-9208-0. Epub 2007 Nov 6.
Protein flexibility lies at the heart of many protein-ligand binding events and enzymatic activities. However, the experimental measurement of protein motions is often difficult, tedious and error-prone. As a result, there is a considerable interest in developing simpler and faster ways of quantifying protein flexibility. Recently, we described a method, called Random Coil Index (RCI), which appears to be able to quantitatively estimate model-free order parameters and flexibility in protein structural ensembles using only backbone chemical shifts. Because of its potential utility, we have undertaken a more detailed investigation of the RCI method in an attempt to ascertain its underlying principles, its general utility, its sensitivity to chemical shift errors, its sensitivity to data completeness, its applicability to other proteins, and its general strengths and weaknesses. Overall, we find that the RCI method is very robust and that it represents a useful addition to traditional methods of studying protein flexibility. We have implemented many of the findings and refinements reported here into a web server that allows facile, automated predictions of model-free order parameters, MD RMSF and NMR RMSD values directly from backbone 1H, 13C and 15N chemical shift assignments. The server is available at http://wishart.biology.ualberta.ca/rci.
蛋白质柔性是许多蛋白质 - 配体结合事件和酶活性的核心。然而，蛋白质运动的实验测量往往困难、繁琐且容易出错。因此，人们对开发更简单、更快的量化蛋白质柔性的方法有着浓厚的兴趣。最近，我们描述了一种称为随机卷曲指数（RCI）的方法，该方法似乎能够仅使用主链化学位移来定量估计蛋白质结构集合中无模型的序参数和柔性。由于其潜在的实用性，我们对RCI方法进行了更详细的研究，试图确定其基本原理、一般用途、对化学位移误差的敏感性、对数据完整性的敏感性、对其他蛋白质的适用性以及其总体优缺点。总体而言，我们发现RCI方法非常稳健，并且它是研究蛋白质柔性的传统方法的有益补充。我们已将此处报告的许多发现和改进措施应用到一个网络服务器中，该服务器允许直接根据主链1H、13C和15N化学位移分配轻松、自动地预测无模型序参数、MD RMSF和NMR RMSD值。该服务器可在http://wishart.biology.ualberta.ca/rci上获取。
