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

机译:基于螺旋对序列分类的交互 r nTM螺旋对的3D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很难通过实验或计算方法获得。螺旋-螺旋接触构象的识别在建模中至关重要,螺旋构象提供了许多跨膜蛋白的结构骨架。跨膜蛋白中的大多数螺旋-螺旋相互作用可以根据其3D形状准确地分为几类。我们提出了一种随机上下文无关文法框架,结合了进化算法,以表示这些类的序列级特征。使用独立的测试集对描述符进行测试,并且通常可实现ROC曲线下的面积0.60-0.70;一些达到0.77。

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