Inferring meaningful pathways in weighted metabolic networks
Inferring meaningful pathways in weighted metabolic networks
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DOI：
10.1016/j.jmb.2005.09.079
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发表时间：
2006-02-10
影响因子：
5.6
通讯作者：
van Helden, J
中科院分区：
文献类型：
--
作者：
Croes, D;Couche, F;van Helden, J
提出了一种计算小分子代谢网络中有意义的途径的方法，该网络包括所有生物体中具有特征的化学反应。代谢网络被描述为一个加权图，其中包括所有化合物，但每个化合物的权重等于它参与的反应的数量。在这个图中，通过搜索一个或多个权重最低的路径来执行寻路。通过计算标注代谢途径中第一反应和最后反应之间的路径，并将计算途径中的中间反应与标注途径中的中间反应进行比较，系统地评估了性能。为了便于比较，还分别在未加权的原始（所有化合物和反应）和过滤（除去高度连接的池代谢物）代谢图中计算路径。在原始图中，计算路径和注释路径之间的对应关系非常差（< 30%）；在过滤后的图中增加到接近65%；在加权图中接近85%。考虑五个最轻路径中最匹配的路径，对应度平均增加到92%。然后我们发现，在加权图中，代谢物对之间的平均距离明显大于未经过滤的原始图，这表明先前报道的代谢网络的小世界特性可能是由于通过池代谢物的无关捷径造成的。此外，我们提供的证据表明，加权图中最短路径的长度代表了酶之间“代谢距离”的有效度量。我们认为，我们的简单方法的成功植根于代谢途径中反应的高度特异性，可能反映了这些途径中运行的热力学约束。我们希望我们的方法在推断新测序的基因组的代谢途径中找到有用的应用。(c) 2005年Elsevier Ltd出版
An approach is presented for computing meaningful pathways in the network of small molecule metabolism comprising the chemical reactions characterized in all organisms. The metabolic network is described as a weighted graph in which all the compounds are included, but each compound is assigned a weight equal to the number of reactions in which it participates. Path finding is performed in this graph by searching for one or more paths with lowest weight. Performance is evaluated systematically by computing paths between the first and last reactions in annotated metabolic pathways, and comparing the intermediate reactions in the computed pathways to those in the annotated ones. For the sake of comparison, paths are computed also in the un-weighted raw (all compounds and reactions) and filtered (highly connected pool metabolites removed) metabolic graphs, respectively. The correspondence between the computed and annotated pathways is very poor (< 30%) in the raw graph; increasing to similar to 65% in the filtered graph; reaching similar to 85% in the weighted graph. Considering the best-matching path among the five lightest paths increases the correspondence to 92%, on average. We then show that the average distance between pairs of metabolites is significantly larger in the weighted graph than in the raw unfiltered graph, suggesting that the small-world properties previously reported for metabolic networks probably result from irrelevant shortcuts through pool metabolites. In addition, we provide evidence that the length of the shortest path in the weighted graph represents a valid measure of the "metabolic distance" between enzymes.We suggest that the success of our simplistic approach is rooted in the high degree of specificity of the reactions in metabolic pathways, presumably reflecting thermodynamic constraints operating in these pathways. We expect our approach to find useful applications in inferring metabolic pathways in newly sequenced genomes. (c) 2005 Published by Elsevier Ltd.