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Towards 3D Modeling of Interacting TM Helix Pairs Based on Classification of Helix Pair Sequence

机译:基于螺旋对对序列分类的基于螺旋螺旋对的三维建模

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Spatial structures of transmembrane proteins are difficult to obtain either experimentally or by computational methods. Recognition of helix-helix contacts conformations, which provide structural skeleton of many transmembrane proteins, is essential in the modeling. Majority of helix-helix interactions in transmembrane proteins can be accurately clustered into a few classes on the basis of their 3D shape. We propose a Stochastic Context Free Grammars framework, combined with evolutionary algorithm, to represent sequence level features of these classes. The descriptors were tested using independent test sets and typically achieved the areas under ROC curves 0.60-0.70; some reached 0.77.
机译:跨膜蛋白的空间结构难以实验或通过计算方法获得。识别螺旋螺旋触点的构象,其提供许多跨膜蛋白的结构骨架,这在建模中是必不可少的。跨膜蛋白的大部分螺旋螺旋相互作用可以基于其3D形状准确地聚集成一些课程。我们提出了一种随机上下文免费语法框架,结合进化算法,表示这些类的序列级别特征。使用独立的测试组测试描述符,通常达到ROC曲线下的区域0.60-0.70;有些人达到0.77。

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