Pathway design using de novo steps through uncharted biochemical spaces

Area of Science:

• Biotechnology
• Computational Biology
• Synthetic Biology

Background:

• Current retrosynthesis tools often address key design criteria like cost and feasibility post-hoc.
• Integrating known and putative enzymatic steps in pathway design presents a significant challenge.

Purpose of the Study:

• To develop a computational procedure for designing bioconversion routes that simultaneously considers multiple complex criteria.
• To enable the integration of known and putative enzymatic transformations within a single pathway design framework.

Main Methods:

• Utilized a prime factorization-based encoding technique (rePrime) to codify reaction centers as rules.
• Employed the novoStoic algorithm to trace metabolites and molecular moieties through balanced bioconversion strategies.
• Simultaneously considered known biotransformations and newly generated reaction rules.

Main Results:

• Demonstrated the ability to bypass steps in existing pathways using putative transformations.
• Successfully assembled complex pathways blending known and putative steps for pharmaceutical production.
• Postulated novel pathways for the biodegradation of xenobiotics.

Conclusions:

• The novoStoic approach offers a unified framework for designing bioconversion pathways with enhanced efficiency and flexibility.
• This method facilitates the development of novel biocatalysts and metabolic engineering strategies.
• The tool supports diverse applications, including drug development and environmental remediation.