Department of Bioinformatics and Life Science, Soongsil University, Seoul 156-743, Korea.
Proteins. 2010 Dec;78(16):3428-36. doi: 10.1002/prot.22849. Epub 2010 Sep 24.
Protein loops are often involved in important biological functions such as molecular recognition, signal transduction, or enzymatic action. The three dimensional structures of loops can provide essential information for understanding molecular mechanisms behind protein functions. In this article, we develop a novel method for protein loop modeling, where the loop conformations are generated by fragment assembly and analytical loop closure. The fragment assembly method reduces the conformational space drastically, and the analytical loop closure method finds the geometrically consistent loop conformations efficiently. We also derive an analytic formula for the gradient of any analytical function of dihedral angles in the space of closed loops. The gradient can be used to optimize various restraints derived from experiments or databases, for example restraints for preferential interactions between specific residues or for preferred backbone angles. We demonstrate that the current loop modeling method outperforms previous methods that employ residue-based torsion angle maps or different loop closure strategies when tested on two sets of loop targets of lengths ranging from 4 to 12.
蛋白质环通常参与重要的生物学功能,如分子识别、信号转导或酶促反应。环的三维结构可以为理解蛋白质功能背后的分子机制提供重要信息。在本文中,我们开发了一种新的蛋白质环建模方法,其中环构象通过片段组装和分析环闭合生成。片段组装方法大大减小了构象空间,而分析环闭合方法有效地找到几何一致的环构象。我们还推导出了一个用于在闭环空间中任何二面角分析函数的梯度的解析公式。梯度可用于优化来自实验或数据库的各种约束,例如特定残基之间的优先相互作用或优选骨架角度的约束。当在两组长度从 4 到 12 的环目标上进行测试时,我们证明当前的环建模方法优于使用基于残基的扭转角图或不同环闭合策略的先前方法。