(169cv) Expanding Chemical Synthesis Planning to Explore Chemo-Enzymatic Pathways Using Minimal Transitions

Chemo-enzymatic pathway design merges complimentary enzymatic and chemical reactions strengths to expand the biomolecular design space. While chemical reactions struggle with regioselectivity and stereoselectivity, biological processes encounter limitations such as product toxicity and enzyme scarcity. Optimally integrating both approaches provides an opportunity to identify efficient pathways beyond the capabilities of either approach. Recently, numerous studies have shown the advantages of leveraging enzymatic steps into industrial-scale chemical processes such as for the blood sugar regulator Sitagliptin (Merck) and for the treatment of AIDS, a protease inhibitor Darunavir (Prozomix). Designing optimal chemo-enzymatic pathways is a complex task and requires navigating a high-dimensional search space of potential reactions that combines individual chemical and biochemical steps. Unlike retrosynthesis which recursively traces back from a given target molecule to the starting precursor one step at a time, we solve a mixed-integer linear programming algorithm (MILP) to discover entire pathways by traversing reaction rules of known chemical and enzymatic connections extracted from USPTO and MetaNetX databases respectively. The algorithm minimizes the number of transitions between chemical and biological reactions, hence cutting down on multiple stages of separation and purification required for each switch between enzymatic and chemical reaction environments. Our approach has been validated through case studies on four molecules: 2-5-Furandicarboxylic acid, Terephthalate, 3-Hydroxybutyrate, and α-Pinene, which demonstrates our capability to identify previously reported total synthesis pathways while also exploring alternative routes with different chemical reaction conditions and outcomes such as temperature and yield respectively. This effort contributes to search for total synthesis pathways leveraging known reactions and streamlines the planning of chemical synthesis potentially leading to the development of more effective synthesis strategies, accessible through open-source code for users. (https://github.com/maranasgroup/chemo-enz).