A path based approach to assessing molecular complexity

Area of Science:

• Computational chemistry
• Cheminformatics
• Drug discovery

Background:

• Traditional molecular complexity measures often rely on predefined structural features.
• A need exists for methods that capture intrinsic molecular complexity without feature predefinition.

Purpose of the Study:

• To develop and present a novel atom environment, path-based approach for calculating molecular complexity.
• To derive molecular complexity measures from atom-centric path diversity.
• To demonstrate the method's independence from explicit structural features like rings or chirality.

Main Methods:

• The method utilizes Shannon's equation to quantify complexity based on path number and diversity from each atom.
• Atom complexity values are aggregated to derive various molecular complexity measures.
• The approach is applied to visualize the complexity landscape of marketed drugs and biologics.

Main Results:

• The path-based method successfully quantifies molecular complexity.
• The approach is independent of predefined features such as ring membership, bond types, chirality, or symmetry.
• Subtle differences in molecular structure are distinguishable using these complexity measures.
• The method was applied to visualize complexity in marketed drugs and biologics.

Conclusions:

• The described atom environment, path-based approach offers a robust method for calculating molecular complexity.
• This method provides a valuable tool for analyzing and visualizing molecular structures, particularly in drug discovery and development.
• The independence from predefined features enhances its applicability across diverse chemical spaces.