Ashton L, Blanch E W
Manchester Interdisciplinary Biocentre, Faculty of Life Sciences, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.
Appl Spectrosc. 2008 May;62(5):469-75. doi: 10.1366/000370208784344433.
The study of conformational transitions in polypeptides is not only important for the understanding of folding mechanisms responsible for the self-assembly of proteins but also for the investigation of the misfolding of proteins that can result in diseases including cystic fibrosis, Alzheimer's, and Parkinson's diseases. Our recent studies developing two-dimensional Raman optical activity (ROA) correlation analysis have proven to be successful in the investigation of polypeptide conformational transitions. However, the complexity of the ROA spectra, and the 2D correlation synchronous and asynchronous plots, makes data analysis detailed and complex, requiring great care in interpretation of 2D correlation rules. By utilizing the 2D correlation approaches of autocorrelation and moving windows it has been possible to gain further information from the ROA spectral data sets in a simpler and more consistent way. The most significant spectral intensity changes have been easily identified, facilitating appropriate interpretation of synchronous plots, and transition phases have been identified in the moving window plots, directly relating spectral intensity changes to the perturbation.
多肽构象转变的研究不仅对于理解负责蛋白质自组装的折叠机制很重要,而且对于研究可能导致包括囊性纤维化、阿尔茨海默病和帕金森病在内的疾病的蛋白质错误折叠也很重要。我们最近开展的二维拉曼光学活性(ROA)相关分析研究已被证明在多肽构象转变研究中是成功的。然而,ROA光谱以及二维相关同步和异步图谱的复杂性使得数据分析详细且复杂,在解释二维相关规则时需要格外小心。通过利用自相关和移动窗口的二维相关方法,有可能以更简单和更一致的方式从ROA光谱数据集中获得更多信息。最显著的光谱强度变化已很容易识别,这有助于对同步图谱进行恰当解释,并且在移动窗口图谱中已识别出转变阶段,将光谱强度变化与扰动直接关联起来。