Symmetry calculation for molecules and transition states

Area of Science:

• Computational Chemistry
• Chemical Informatics
• Molecular Modeling

Background:

• Molecular symmetry is crucial in computational chemistry, impacting reaction mechanisms and properties.
• Existing automated symmetry identification methods often require 3D atomic coordinates, limiting their applicability when coordinates are unavailable.
• Accurate symmetry determination is vital for various chemical applications, including drug discovery.

Purpose of the Study:

• To develop a novel algorithm for automated symmetry identification of molecules and transition states.
• To overcome the limitations of coordinate-dependent symmetry detection methods.
• To provide a generic and broadly applicable tool for determining molecular symmetry numbers.

Main Methods:

• An augmented graph representation incorporating molecular topology and stereocenters was employed.
• The algorithm utilizes the automorphism group order of the graph as a foundational element.
• A new concept of 'label-stereoisomers' was introduced to refine symmetry number calculation.

Main Results:

• The algorithm successfully identified symmetry for a wide range of molecular structures, from asymmetric to highly symmetric.
• Calculated symmetry numbers align with expected values across diverse chemical entities.
• The method demonstrated robustness and accuracy without relying on heuristic rules.

Conclusions:

• The developed algorithm offers a reliable, coordinate-independent approach to determining molecular symmetry.
• This advancement facilitates the fast screening of symmetry in large molecular datasets.
• The new method enhances computational chemistry tools, particularly for applications where 3D structures are not readily available.