M-path

M-path constructs synthetic metabolic pathways by navigating comprehensive chemical and enzymatic databases to identify potential routes from initial compounds to target products for sustainable chemical production and pathway design.

Key Features:

• Iterative random algorithm: Employs an iterative random algorithm to navigate chemical and enzymatic databases and identify candidate synthetic metabolic routes.
• Search space management: Manages and controls the search space to limit combinatorial explosion during pathway discovery.
• Efficiency versus exhaustive enumeration: Outperforms traditional exhaustive enumeration methods in pathway discovery by reducing computational complexity.
• Evaluation scoring: Assesses candidate pathways using evaluation scores based on chemical similarities.
• Database integration: Leverages comprehensive chemical and enzymatic databases for pathway identification.
• Scalability: Scales to calculate potential metabolic pathways for arbitrary sets of chemicals, demonstrated on alpha amino acids.

Scientific Applications:

• Sustainable chemical production: Discovery of synthetic metabolic routes aimed at producing chemicals via engineered metabolism.
• Pathway design and optimization: Design and optimization of high-value synthetic metabolic pathways.
• Amino acid pathway generation: Generation of synthetic metabolic pathways for alpha amino acids.
• Bioinformatics and synthetic biology research: Exploration of diverse chemical and enzymatic data to support research in bioinformatics and synthetic biology.

Methodology:

Uses an iterative random algorithm to navigate comprehensive chemical and enzymatic databases while controlling the search space and scoring candidate pathways with evaluation metrics based on chemical similarities.