RetSynth

RetSynth identifies optimal and sub-optimal synthetic metabolic pathways, including hybrid biological/non-biological routes, for producing target compounds in microbial chassis by enumerating fully independent pathways within metabolic networks.

Key Features:

• Optimal Pathway Identification: A novel algorithm enumerates all optimal pathways for target chemicals by focusing on fully independent pathways rather than the entire metabolic network.
• Dynamic constraint selection and scalability: The algorithm dynamically selects constraints to reduce computational complexity and enable scalable pathway enumeration.
• Sub-optimal and Hybrid Solutions: Identifies sub-optimal pathways and incorporates non-biological chemical reactions to generate hybrid biological/non-biological routes.
• Data Integration and Flux Balance Analysis: Integrates data from metabolic repositories and performs flux balance analysis to evaluate pathway feasibility.
• Ranking Criteria: Provides quantitative ranking metrics such as target yield for comparing and prioritizing synthetic routes.

Scientific Applications:

• Metabolic engineering: Supports engineering of microbial organisms for biological production of industrially and economically important compounds by streamlining pathway selection.
• Hybrid pathway design: Enables design of synthesis routes that combine biological reactions with non-biological chemical steps for compounds not accessible solely via metabolism.

Methodology:

A novel algorithm scales enumeration by focusing on fully independent pathways and dynamically selecting constraints; the approach incorporates non-biological chemical reactions, integrates data from metabolic repositories, and applies flux balance analysis to evaluate and rank pathways.