PREDICTING CONFORMATIONAL SWITCHES IN PROTEINS

我们正在开发一种新的计算技术来预测 蛋白质中的构象转换元件 序列的 ASP（Ambivalent Structure Predictor） 分析二级结构预测算法的结果， 确定构象矛盾区域。 ASP识别 测试蛋白质序列中的矛盾区， 涉及大量的骨架重排。 以前的网站 被描述为构象开关被正确地预测为 结构矛盾区的一部分。 ASP还可以识别 核苷酸之间变构通讯的推定途径， 肌动蛋白结合和肌球蛋白的支点位点。 的设施 计算机图形实验室用于获取序列数据， 二级结构预测 分子图形是不可或缺的 数据分析，因为我们将结构矛盾的预测映射到 蛋白质的三维晶体结构。 进一步发展本港 算法可以提供一个工具，指导实验研究 蛋白质的功能和运动在缺乏详细的 三维结构数据。

We are developing a new computational technique to predict conformationally switching elements in proteins from their amino acid sequences. The method, called ASP (Ambivalent Structure Predictor) analyzes results from a secondary structure prediction algorithm to identify regions of conformational ambivalence. ASP identifies ambivalent regions in test protein sequences for which function involves substantial backbone rearrangements. Sites previously described as conformational switches are correctly predicted to be part of structurally ambivalent regions. ASP can also identify putative pathways of allosteric communication between the nucleotide, actin binding and fulcrum sites of myosin. The facilities at the Computer Graphics Laboratory are used to acquire sequence data and secondary structure predictions. Molecular graphics are integral to data analysis, as we map predictions of structural ambivalence onto the 3D crystal structures of the proteins. Further development of our algorithm may provide a tool for guiding experimental studies on protein function and motion in the absence of detailed three-dimensional structural data.