Meads D, Hansen M D, Pang A
Computer Science Department, University of California, Santa Cruz 95064, USA. doanna,mhansen,
Pac Symp Biocomput. 1999:354-67. doi: 10.1142/9789814447300_0035.
Protein fold recognition (sometimes called threading) is the prediction of a protein's 3-dimensional shape based on its similarity to a protein of known structure. Fold predictions are low resolution; that is, no effort is made to rotate the protein's component amino acid side chains into their correct spatial orientations. The goal is simply to recognize the protein family member that most closely resembles the target sequence of unknown structure and to create a sensible alignment of the target to the known structure (i.e., a structure-sequence alignment). To facilitate this type of structure prediction, we have designed a low resolution molecular graphics tool. ProtAlign introduces the ability to interact with and edit alignments directly in the 3-dimensional structure as well as in the usual 2-dimensional layout. It also contains several functions and features to help the user assess areas within the alignment. ProtAlign implements an open pipe architecture to allow other programs to access its molecular graphics capabilities. In addition, it is capable of "driving" other programs. Because amino acid side chain orientation is not relevant in fold recognition, we represent amino acid residues as abstract shapes or glyphs much like Lego (tm) blocks and we borrow techniques from comparative flow visualization using streamlines to provide clean depictions of the entire protein model. By creating a low resolution representation of protein structure, we are able to at least double the amount of information on the screen. At the same time, we create a view that is not as busy as the corresponding representations using traditional high resolution visualization methods which show detailed atomic structure. This eliminates distracting and possibly misleading visual clutter resulting from the mapping of protein alignment information onto a high resolution display of the known structure. This molecular graphics program is implemented in Open GL to facilitate porting to other platforms.
蛋白质折叠识别（有时称为穿线法）是基于与已知结构蛋白质的相似性来预测蛋白质的三维形状。折叠预测的分辨率较低；也就是说，不会努力将蛋白质的组成氨基酸侧链旋转到其正确的空间取向。目标仅仅是识别与未知结构的目标序列最相似的蛋白质家族成员，并创建目标与已知结构的合理比对（即结构-序列比对）。为了便于进行这种类型的结构预测，我们设计了一种低分辨率分子图形工具。ProtAlign引入了在三维结构以及通常的二维布局中直接与比对进行交互和编辑的能力。它还包含几个功能和特性，以帮助用户评估比对中的区域。ProtAlign实现了一种开放管道架构，允许其他程序访问其分子图形功能。此外，它能够“驱动”其他程序。由于氨基酸侧链取向在折叠识别中无关紧要，我们将氨基酸残基表示为抽象形状或符号，很像乐高积木，并且我们借鉴了使用流线的比较流可视化技术，以提供整个蛋白质模型的清晰描绘。通过创建蛋白质结构的低分辨率表示，我们能够至少将屏幕上的信息量增加一倍。同时，我们创建的视图不像使用显示详细原子结构的传统高分辨率可视化方法的相应表示那样繁杂。这消除了将蛋白质比对信息映射到已知结构的高分辨率显示上所产生的分散注意力且可能产生误导的视觉混乱。这个分子图形程序是用OpenGL实现的，以便于移植到其他平台。
