Finding the K best synthesis plans.

Area of Science:

• Computational Chemistry
• Organic Synthesis
• Chemical Engineering

Background:

• Current algorithmic approaches to synthesis planning often rely on selecting a bond set and identifying a single optimal plan.
• This can limit the robustness and flexibility of the synthesis planning process.

Purpose of the Study:

• To reframe synthesis planning as a combinatorial optimization problem on hypergraphs.
• To develop a method for computing multiple optimal synthesis plans for a target molecule.

Main Methods:

• Modeling synthesis plans as directed hyperpaths within a hypergraph of reactions (HoR).
• Utilizing a polynomial time algorithm to find the K shortest hyperpaths.
• Applying the method to the synthesis of Decalin as an illustrative example.

Main Results:

• Demonstrated that synthesis planning can be effectively modeled as a combinatorial optimization problem on hypergraphs.
• Showcased the ability to compute K best synthesis plans for a given target molecule.
• Highlighted the benefits of having multiple plans, including increased robustness and improved cost management.

Conclusions:

• The hypergraph-based approach offers a more robust and flexible framework for chemical synthesis planning.
• The method allows for the integration of diverse cost considerations and handling of imprecise yield data.
• Identified an inconsistency in the classical quality measure of convergency, suggesting its use in synthesis planning may be questionable.