Understanding topological symmetry: a heuristic approach to its determination

Area of Science:

• Computational chemistry
• Cheminformatics
• Molecular modeling

Background:

• Topological symmetry is crucial for understanding molecular properties and reactions.
• Existing methods for symmetry perception can be computationally intensive, especially for complex organic structures.

Purpose of the Study:

• To present a novel algorithm for topological symmetry perception in organic molecules.
• To identify symmetry planes and equivalent atoms (symmetry atom groups - SAGs) efficiently.
• To provide a computationally effective approach for chemical structure analysis.

Main Methods:

• Development of a heuristic-rule-based algorithm for topological symmetry perception.
• Identification of symmetry planes and symmetry atom groups (SAGs).
• Avoidance of exhaustive graph automorphism group exploration and complex cycle determination.

Main Results:

• The algorithm successfully identifies topological symmetry planes and SAGs in diverse organic structures.
• It demonstrates high effectiveness in computer processing, even for complex molecules like dendrimers.
• The method avoids computationally expensive steps like full graph automorphism and cycle determination.

Conclusions:

• The presented algorithm offers an efficient and effective method for topological symmetry perception in organic chemistry.
• This approach simplifies the analysis of molecular symmetry, aiding in computational chemistry and drug discovery.
• The heuristic-rule-based strategy provides a practical solution for handling complex chemical structures.