BACKGROUND The rapid growth of available knowledge on metabolic processes across thousands of species continues to expand the possibilities of producing chemicals by combining pathways found in different species. Several computational search algorithms have been developed for automating the identification of possible heterologous pathways; however, these searches may return thousands of pathway results. Although the large number of results are in part due to the large number of possible compounds and reactions, a subset of core reaction modules is repeatedly observed in pathway results across multiple searches, suggesting that some subpaths between common compounds were more consistently explored than others.To reduce the resources spent on searching the same metabolic space, a new meta-algorithm for metabolic pathfinding, Hub Pathway search with Atom Tracking (HPAT), was developed to take advantage of a precomputed network of subpath modules. To investigate the efficacy of this method, we created a table describing a network of common hub metabolites and how they are biochemically connected and only offloaded searches to and from this hub network onto an interactive webserver capable of visualizing the resulting pathways. RESULTS A test set of nineteen known pathways taken from literature and metabolic databases were used to evaluate if HPAT was capable of identifying known pathways. HPAT found the exact pathway for eleven of the nineteen test cases using a diverse set of precomputed subpaths, whereas a comparable pathfinding search algorithm that does not use precomputed subpaths found only seven of the nineteen test cases. The capability of HPAT to find novel pathways was demonstrated by its ability to identify novel 3-hydroxypropanoate (3-HP) synthesis pathways. As for pathway visualization, the new interactive pathway filters enable a reduction of the number of displayed pathways from hundreds down to less than ten pathways in several test cases, illustrating their utility in reducing the amount of presented information while retaining pathways of interest. CONCLUSIONS This work presents the first step in incorporating a precomputed subpath network into metabolic pathfinding and demonstrates how this leads to a concise, interactive visualization of pathway results. The modular nature of metabolic pathways is exploited to facilitate efficient discovery of alternate pathways.

中文翻译：

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通过预先计算的途径改善代谢寻路的组织和交互性。

背景技术关于跨越数千种物种的代谢过程的可用知识的迅速增长，通过结合在不同物种中发现的途径，继续扩大了生产化学物质的可能性。已经开发了几种计算搜索算法来自动识别可能的异源途径。但是，这些搜索可能会返回数千条路径结果。尽管大量结果部分归因于大量可能的化合物和反应，但在多次搜索的途径结果中反复观察到核心反应模块的子集，这表明常见化合物之间的某些子途径比其他途径更为一致。为了减少用于搜索相同代谢空间的资源，一种新的元算法用于代谢寻路，开发了带有原子跟踪（HPAT）的集线器路径搜索，以利用子路径模块的预先计算的网络。为了研究该方法的有效性，我们创建了一张表格，该表格描述了常见的枢纽代谢物网络以及它们如何进行生化连接，并且仅将搜索往返于该枢纽网络的搜索卸载到了能够可视化最终途径的交互式Web服务器上。结果使用从文献和代谢数据库中提取的19条已知途径的测试集来评估HPAT是否能够识别已知途径。HPAT使用各种预先计算的子路径为19个测试案例中的11个找到了确切的路径，而不使用预先计算的子路径的可比较寻路搜索算法仅发现19个测试案例中的7个。HPAT发现新途径的能力通过其鉴定新的3-羟基丙酸酯（3-HP）合成途径的能力得到证明。至于路径可视化，新的交互式路径过滤器可以在几个测试案例中将显示路径的数量从数百个减少到少于十个，从而说明了它们在减少显示信息量的同时保留感兴趣路径的效用。结论这项工作代表了将预先计算的子路径网络整合到代谢寻路中的第一步，并演示了这如何导致途径结果的简洁，交互式可视化。利用代谢途径的模块性质来促进有效发现替代途径。