Yang Jiaan
MicrotechNano, LLC, Indianapolis, Indiana 46234, USA.
Proteins. 2008 May 15;71(3):1497-518. doi: 10.1002/prot.21932.
Understanding and describing three-dimensional (3D) protein structures have dominated biological and biochemistry research for many years. A comprehensive description of protein folding structure is essential for the advancement of protein research. In this study, a novel description method is developed to generate a set of folding patterns with specific shape features, as well as vector characteristics in space. To accomplish the goal, this method embeds features from geometry, morphology and topology together into an algorithmic approach to achieve a full description for proteins. A set of 27 vectors is derived mathematically from an enclosed space, and each vector represents a 3D folding shape of five successive C(alpha) atoms in the protein backbone. The 27 vectors are represented by 27 symbols, which are called as the protein folding shape code (PFSC). The PFSC method offers a digital description of folding shapes along a protein backbone, which facilitates protein structure analysis. The PFSC method provides a tool to study the similarity and dissimilarity for protein or protein conformers. The PFSC results show overall agreement with structural assignments from the protein data bank, as well as results from other methods. All results show that the PFSC method is a reliable tool with explicit meaning for protein folding shape description.
多年来，理解和描述三维（3D）蛋白质结构一直主导着生物学和生物化学研究。全面描述蛋白质折叠结构对于蛋白质研究的进展至关重要。在本研究中，开发了一种新颖的描述方法，以生成一组具有特定形状特征以及空间向量特征的折叠模式。为实现这一目标，该方法将来自几何、形态和拓扑的特征一起嵌入到一种算法方法中，以实现对蛋白质的完整描述。从一个封闭空间中通过数学推导得出一组27个向量，每个向量代表蛋白质主链中五个连续C（α）原子的三维折叠形状。这27个向量由27个符号表示，这些符号被称为蛋白质折叠形状代码（PFSC）。PFSC方法提供了一种沿蛋白质主链对折叠形状的数字描述，这有助于蛋白质结构分析。PFSC方法提供了一个工具来研究蛋白质或蛋白质构象异构体的相似性和差异性。PFSC结果与蛋白质数据库中的结构归属以及其他方法的结果总体一致。所有结果表明，PFSC方法是一种可靠的工具，对于蛋白质折叠形状描述具有明确的意义。
