School of Computer and Electronics and Information, Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning, China.
College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China.
PLoS Comput Biol. 2021 Feb 2;17(2):e1008676. doi: 10.1371/journal.pcbi.1008676. eCollection 2021 Feb.
Finding non-standard or new metabolic pathways has important applications in metabolic engineering, synthetic biology and the analysis and reconstruction of metabolic networks. Branched metabolic pathways dominate in metabolic networks and depict a more comprehensive picture of metabolism compared to linear pathways. Although progress has been developed to find branched metabolic pathways, few efforts have been made in identifying branched metabolic pathways via atom group tracking. In this paper, we present a pathfinding method called BPFinder for finding branched metabolic pathways by atom group tracking, which aims to guide the synthetic design of metabolic pathways. BPFinder enumerates linear metabolic pathways by tracking the movements of atom groups in metabolic network and merges the linear atom group conserving pathways into branched pathways. Two merging rules based on the structure of conserved atom groups are proposed to accurately merge the branched compounds of linear pathways to identify branched pathways. Furthermore, the integrated information of compound similarity, thermodynamic feasibility and conserved atom groups is also used to rank the pathfinding results for feasible branched pathways. Experimental results show that BPFinder is more capable of recovering known branched metabolic pathways as compared to other existing methods, and is able to return biologically relevant branched pathways and discover alternative branched pathways of biochemical interest. The online server of BPFinder is available at http://114.215.129.245:8080/atomic/. The program, source code and data can be downloaded from https://github.com/hyr0771/BPFinder.
发现非标准或新的代谢途径在代谢工程、合成生物学以及代谢网络的分析和重建中具有重要应用。分支代谢途径在代谢网络中占主导地位，与线性途径相比，能更全面地描绘代谢情况。尽管已经开发出了一些寻找分支代谢途径的方法，但在通过原子团跟踪识别分支代谢途径方面，却鲜有研究。在本文中，我们提出了一种名为 BPFinder 的路径搜索方法，通过原子团跟踪来寻找分支代谢途径，旨在指导代谢途径的合成设计。BPFinder 通过跟踪代谢网络中原子团的运动来枚举线性代谢途径，并将线性原子团守恒途径合并为分支途径。提出了两条基于保守原子团结构的合并规则，以准确地合并线性途径的分支化合物，从而识别分支途径。此外，还综合利用化合物相似性、热力学可行性和保守原子团的信息，对可行的分支途径的路径搜索结果进行排序。实验结果表明，与其他现有方法相比，BPFinder 更能恢复已知的分支代谢途径，并且能够返回具有生物学相关性的分支途径，以及发现具有生物化学意义的替代分支途径。BPFinder 的在线服务器可在 http://114.215.129.245:8080/atomic/ 访问。程序、源代码和数据可从 https://github.com/hyr0771/BPFinder 下载。
