M-path: a compass for navigating potential metabolic pathways.

Area of Science:

• Metabolic Engineering
• Computational Biology
• Synthetic Biology

Background:

• Synthetic metabolic pathway construction offers sustainable chemical and material production.
• Computational methods are crucial for designing high-value pathways by mining chemical and enzymatic databases.
• Existing methods face limitations in computational complexity, restricting the diversity of data used.

Purpose of the Study:

• To introduce a novel computational platform, M-path, for exploring synthetic metabolic pathways.
• To overcome the computational complexity limitations of previous pathway design methods.
• To facilitate the discovery of diverse and valuable synthetic metabolic pathways.

Main Methods:

• M-path utilizes an iterative random algorithm for efficient database exploration.
• The platform allows control over the search space, outperforming exhaustive enumeration.
• A web-based pathway viewer with chemical similarity scoring is integrated.

Main Results:

• M-path successfully explores synthetic metabolic pathways, including novel enzymatic reactions and compounds.
• The platform demonstrates efficient use of chemical and enzymatic databases.
• Extensive synthetic pathways for alpha-amino acids were generated, showcasing scalability for any chemical.

Conclusions:

• M-path provides a scalable and efficient computational solution for synthetic metabolic pathway design.
• The platform enhances the exploration of diverse chemical and enzymatic data.
• M-path facilitates the discovery of sustainable production routes for various chemicals.