The significance of metabolic pathway prediction is to envision the viable unknown transformations that can occur provided the appropriate enzymes are present. It can facilitate the prediction of the consequences of host-pathogen interactions. In this article, we have proposed a new algorithm ASAPP (Architectural Similarity-based Automated Pathway Prediction) to predict metabolic pathways based on the structural similarity among the metabolites. ASAPP takes two dimensional structure and molecular weight of metabolites as input, and generates a list of probable transformations without the knowledge of any externally established reactions, with an accuracy of 85.09%. ASAPP has also been applied to predict the outcome of pathogen liberated toxins on the carbohydrate and lipid pathways of the hosts. We have analyzed the disruption of host pathways in the presence of toxins, and have found that some metabolites in Glycolysis and the TCA cycle have a high chance of being the breakpoints in the pathway. The tool is available at http://asapp.droppages.com/.

中文翻译：

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ASAPP：基于架构相似性的自动路径预测系统及其在宿主与病原体相互作用中的应用。

代谢途径预测的意义在于，设想存在适当的酶时可能发生的可行的未知转化。它可以促进对宿主-病原体相互作用后果的预测。在本文中，我们提出了一种新的算法ASAPP（基于建筑相似性的自动途径预测），以基于代谢物之间的结构相似性来预测代谢途径。ASAPP将代谢物的二维结构和分子量作为输入，并在不知道任何外部确定的反应的情况下生成可能的转化列表，准确度为85.09％。ASAPP也已用于预测宿主的碳水化合物和脂质途径上的病原体释放毒素的结果。我们分析了毒素存在下宿主途径的破坏，并发现糖酵解和TCA循环中的某些代谢物极有可能成为该途径的断点。该工具可从http://asapp.droppages.com/获得。