Pickaxe

Pickaxe predicts novel metabolic reactions and generates reaction networks by applying enzymatic promiscuity rules to metabolite sets for applications in pathway design, metabolomics annotation, and chemical production.

Key Features:

• Flexible Rule Application: Iterative application of enzymatic promiscuity rules to sets of metabolites, supporting JN1224min rulesets derived from MetaCyc and user-defined custom rules.
• Network Generation and Filtering: Generation of expansive reaction networks with filters for chemical similarity to target molecules, metabolomics data integration, thermodynamic considerations, and reaction feasibility assessments.
• MINE Database integration: Integration with the MINE Database python package to incorporate database-derived metabolites into generated reaction networks.

Scientific Applications:

• Biosynthetic Pathway Design: Expansion of biological databases with novel reactions to support design of biosynthetic pathways.
• Industrial Chemical Production: Generation of candidate reactions and pathways for industrially relevant chemicals from metabolome databases such as yeast.
• Metabolomics Data Annotation: Annotation of untargeted metabolomics peaks, exemplified by application to an E. coli dataset.

Methodology:

Iterative application of enzymatic promiscuity rules (JN1224min or custom) to metabolites to generate novel reactions and reaction networks, with optional filters for chemical similarity, metabolomics data integration, thermodynamic considerations, and reaction feasibility.