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A path based approach to assessing molecular complexity.

John R Proudfoot1

  • 1Boehringer Ingeleim Pharmaceuticals Inc, 900 Ridgebury Road, PO Box 368, Ridgefield, CT 06877, USA.

Bioorganic & Medicinal Chemistry Letters
|March 23, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a novel path-based method for calculating molecular complexity using atom environments. This approach quanties molecular complexity independent of predefined features, enabling subtle structural distinctions.

Keywords:
Approved drugsAtom complexityMolecular complexityShannon entropy

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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.