Generic strategies for chemical space exploration

Area of Science:

• Computational Chemistry
• Graph Theory
• Systems Biology

Background:

• Chemical synthesis explores vast molecular universes, posing combinatorial challenges.
• Analyzing biochemical reaction networks is crucial for understanding chemical and biological systems.
• Graphs and graph rewriting offer natural models for molecules and reactions.

Purpose of the Study:

• To develop a framework for specifying exploration strategies in graph-rewriting systems.
• To address the combinatorial complexity of exploring large chemical spaces.
• To enable efficient analysis of complex reaction networks.

Main Methods:

• Introducing partial applications of rewrite rules, inspired by functional programming's partial evaluation.
• Utilizing graph-rewriting systems to model molecules and chemical reactions.
• Applying the framework to complex reaction networks in carbohydrate chemistry.

Main Results:

• Demonstrated the feasibility of a high-level strategy framework for chemical exploration.
• Successfully applied the framework to complex carbohydrate chemistry reaction networks.
• Showcased the framework's versatility beyond chemistry, including puzzle game emulation.

Conclusions:

• The proposed framework provides a powerful tool for navigating and analyzing complex chemical spaces.
• Partial application of rewrite rules offers an efficient strategy for exploring vast molecular universes.
• The framework's adaptability extends its utility to diverse computational modeling tasks.