Protein structure prediction via combinatorial assembly of sub-structural units
Protein structure prediction via combinatorial assembly of sub-structural units
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DOI：
10.1093/bioinformatics/btg1020
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发表时间：
2003-07-01
期刊：
影响因子：
5.8
通讯作者：
Wolfson, Haim J.
中科院分区：
文献类型：
--
作者：
Inbar, Yuval;Benyamini, Hadar;Wolfson, Haim J.
根据蛋白质折叠的层次性质，我们提出了一个三阶段的方案来预测蛋白质结构的序列。首先，序列被切割成片段，每个片段被分配一个结构。其次，将指定的结构组合起来，形成整体的三维组织。三是完成和完善高级别预测安排。这项工作的重点是该方案的第二阶段：组合组装。提出了一种组合对接算法CombDock。CombDock获得一组有序的蛋白质亚结构，并预测定义其整体组织的相互联系。我们将组合装配简化为一个图论问题，并给出了这个计算困难问题的一个启发式多项式解。我们将CombDock应用于两种类型的结构单元的各种示例：蛋白质结构域和构建块，它们是结构域的相对稳定的子结构。此外，我们使用越来越扭曲的输入来测试CombDock，其中天然结构单元被从同源蛋白质中提取的类似折叠单元所取代，在更困难的情况下，从全局不相关的蛋白质中提取。该算法具有鲁棒性，对输入失真的敏感性较低。这表明CombDock是一种有用的蛋白质结构预测工具，可以应用于大型靶蛋白。
Following the hierarchical nature of protein folding, we propose a three-stage scheme for the prediction of a protein structure from its sequence. First, the sequence is cut to fragments that are each assigned a structure. Second, the assigned structures are combinatorially assembled to form the overall 3D organization. Third, highly ranked predicted arrangements are completed and refined. This work focuses on the second stage of this scheme: the combinatorial assembly. We present CombDock, a combinatorial docking algorithm. CombDock gets an ordered set of protein sub-structures and predicts the inter-contacts that define their overall organization. We reduce the combinatorial assembly to a graph-theory problem, and give a heuristic polynomial solution to this computationally hard problem. We applied CombDock to various examples of structural units of two types: protein domains and building blocks, which are relatively stable sub-structures of domains. Moreover, we tested CombDock using increasingly distorted input, where the native structural units were replaced by similarly folded units extracted from homologous proteins and, in the more difficult cases, from globally unrelated proteins. The algorithm is robust, showing low sensitivity to input distortion. This suggests that CombDock is a useful tool in protein structure prediction that may be applied to large target proteins.