Automated network generation and analysis of biochemical reaction pathways using RING

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Abstract

This paper describes how Rule Input Network Generator (RING), a network generation computational tool, can be adopted to generate a variety of complex biochemical reaction networks. The reaction language incorporated in RING allows representation of chemical compounds in biological systems with various structural complexity. Complex molecules such as oligosaccharides in glycosylation pathways can be described using a simplified representation of their monosaccharide building blocks and glycosidic bonds. The automated generation and topological network analysis features in RING also allow for: (1) constructing biochemical reaction networks in a rule-based manner, (2) generating graphical representations of the networks, (3) querying molecules containing a particular structural pattern, (4) finding the shortest synthetic pathways to a user-specified species, and (5) performing enzyme knockout to study their effect on the reaction network. Case studies involving three biochemical reaction systems: (1) Synthesis of 2-ketoglutarate from xylose in bacterial cells, (2) N-glycosylation in mammalian cells, and (3) O-glycosylation in mammalian cells are presented to demonstrate the capabilities of RING for robust and exhaustive network generation and the advantages of its post-processing features.

Original languageEnglish (US)
Pages (from-to)84-93
Number of pages10
JournalMetabolic Engineering
Volume49
DOIs
StatePublished - Sep 2018

Bibliographical note

Funding Information:
We acknowledge the National Science Foundation, Energy for sustainability, CDS&E (Grant no. 1307089 ) for the financial support. We would like to thank Minnesota Supercomputing Institute for permissions to use their facilities and computing resources. We would like to thank Dr. Patrick Hossler for valuable discussion on GlycoVis and glycosylation pathways. We would like to thank Guilherme Costa de Sousa for collecting information on the substrate specificity of glycosylation enzymes. Tung Le was supported in part by the Vietnam Education Foundation (VEF).

Keywords

  • Carbohydrate metabolism
  • Domain specific language interface
  • Glycosylation
  • Network analysis
  • Rule-based network generation

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