Rahman Syed Asad, Schomburg Dietmar
Cologne University Bioinformatics Center, CUBIC, Zülpicher Strasse 47, 50674 Koeln, Germany.
Bioinformatics. 2006 Jul 15;22(14):1767-74. doi: 10.1093/bioinformatics/btl181. Epub 2006 May 8.
The local and global aspects of metabolic network analyses allow us to identify enzymes or reactions that are crucial for the survival of the organism(s), therefore directing us towards the discovery of potential drug targets.
We demonstrate a new method ('load points') to rank the enzymes/metabolites in the metabolic network and propose a model to determine and rank the biochemical lethality in metabolic networks (enzymes/metabolites) through 'choke points'. Based on an extended form of the graph theory model of metabolic networks, metabolite structural information was used to calculate the k-shortest paths between metabolites (the presence of more than one competing path between substrate and product). On the basis of these paths and connectivity information, load points were calculated and used to empirically rank the importance of metabolites/enzymes in the metabolic network. The load point analysis emphasizes the role that the biochemical structure of a metabolite, rather than its connectivity (hubs), plays in the conversion pathway. In order to identify potential drug targets (based on the biochemical lethality of metabolic networks), the concept of choke points and load points was used to find enzymes (edges) which uniquely consume or produce a particular metabolite (nodes). A non-pathogenic bacterial strain Bacillus subtilis 168 (lactic acid producing bacteria) and a related pathogenic bacterial strain Bacillus anthracis Sterne (avirulent but toxigenic strain, producing the toxin Anthrax) were selected as model organisms. The choke point strategy was implemented on the pathogen bacterial network of B.anthracis Sterne. Potential drug targets are proposed based on the analysis of the top 10 choke points in the bacterial network. A comparative study between the reported top 10 bacterial choke points and the human metabolic network was performed. Further biological inferences were made on results obtained by performing a homology search against the human genome.
The load and choke point modules are introduced in the Pathway Hunter Tool (PHT), the basic version of which is available on http://www.pht.uni-koeln.de.
代谢网络分析的局部和全局方面使我们能够识别对生物体生存至关重要的酶或反应,从而引导我们发现潜在的药物靶点。
我们展示了一种新方法(“负载点”)来对代谢网络中的酶/代谢物进行排名,并提出了一个模型,通过“阻塞点”来确定和排名代谢网络(酶/代谢物)中的生化致死性。基于代谢网络的图论模型的扩展形式,利用代谢物结构信息计算代谢物之间的k条最短路径(底物和产物之间存在多条竞争路径)。基于这些路径和连通性信息,计算负载点并用于凭经验对代谢网络中代谢物/酶的重要性进行排名。负载点分析强调了代谢物的生化结构而非其连通性(枢纽)在转化途径中所起的作用。为了识别潜在的药物靶点(基于代谢网络的生化致死性),使用阻塞点和负载点的概念来找到唯一消耗或产生特定代谢物(节点)的酶(边)。选择非致病性细菌菌株枯草芽孢杆菌168(产乳酸细菌)和相关的致病性细菌菌株炭疽芽孢杆菌斯特恩(无毒但产毒菌株,产生炭疽毒素)作为模型生物。在炭疽芽孢杆菌斯特恩的病原菌网络上实施阻塞点策略。基于对细菌网络中前10个阻塞点的分析提出潜在的药物靶点。对报道的前10个细菌阻塞点与人类代谢网络进行了比较研究。通过对人类基因组进行同源性搜索获得的结果进行了进一步的生物学推断。
负载和阻塞点模块已引入途径猎手工具(PHT),其基本版本可在http://www.pht.uni-koeln.de上获取。