Berjanskii Mark V, Wishart David S
Department of Computing Science, University of Alberta, Edmonton, AB, Canada T6G 2E8.
Nucleic Acids Res. 2007 Jul;35(Web Server issue):W531-7. doi: 10.1093/nar/gkm328. Epub 2007 May 7.
Protein motions play important roles in numerous biological processes such as enzyme catalysis, muscle contractions, antigen-antibody interactions, gene regulation and virus assembly. Knowledge of protein flexibility is also important in rational drug design, protein docking and protein engineering. However, the experimental measurement of protein motions is often difficult, requiring sophisticated experiments, complex data analysis and detailed information about the protein's tertiary structure. As a result, there is a considerable interest in developing simpler, more effective ways of quantifying protein flexibility. Recently, we described a method, called the random coil index (RCI), which is able to quantitatively estimate backbone root mean square fluctuations (RMSFs) of structural ensembles and order parameters using only chemical shifts. The RCI method is very fast (<5 s) and exceedingly robust. It also offers an excellent alternative to traditional methods of measuring protein flexibility. We have recently extended the RCI concept and implemented it as a web server. This server allows facile, accurate and fully automated predictions of MD RMSF values, NMR RMSF values and model-free order parameters (S2) directly from chemical shift assignments. It also performs automatic chemical shift re-referencing to ensure consistency and reproducibility. On average, the correlation between RCI predictions and experimentally obtained motional amplitudes is within the range from 0.77 to 0.82. The server is available at http://wishart.biology.ualberta.ca/rci.
蛋白质运动在众多生物过程中发挥着重要作用,如酶催化、肌肉收缩、抗原 - 抗体相互作用、基因调控和病毒组装。了解蛋白质的柔韧性在合理药物设计、蛋白质对接和蛋白质工程中也很重要。然而,蛋白质运动的实验测量往往很困难,需要复杂的实验、复杂的数据分析以及有关蛋白质三级结构的详细信息。因此,人们对开发更简单、更有效的量化蛋白质柔韧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,该方法仅使用化学位移就能定量估计结构集合的主链均方根波动(RMSF)和序参数。RCI方法非常快速(<5秒)且极其稳健。它也为测量蛋白质柔韧性的传统方法提供了一种出色的替代方案。我们最近扩展了RCI概念并将其实现为一个网络服务器。该服务器允许直接从化学位移分配轻松、准确且全自动地预测分子动力学(MD)RMSF值、核磁共振(NMR)RMSF值和无模型序参数(S2)。它还会自动进行化学位移重新参照,以确保一致性和可重复性。平均而言,RCI预测与实验获得的运动幅度之间的相关性在0.77至0.82范围内。该服务器可在http://wishart.biology.ualberta.ca/rci获取。