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Comparing Molecular Patterns Using the Example of SMARTS: Theory and Algorithms.

Robert Schmidt1, Emanuel S R Ehmki1, Farina Ohm1

  • 1ZBH - Center for Bioinformatics , Bundesstraße 43 , 20146 Hamburg , Germany.

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|May 24, 2019
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Summary
This summary is machine-generated.

A new method uses chemical fingerprints to compare molecular patterns, enabling automated hierarchy derivation and searching within large pattern collections. This tool, SMARTScompare, aids in analyzing structural filters for drug design.

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Area of Science:

  • Computational chemistry
  • Cheminformatics

Background:

  • Molecular patterns are crucial for filtering compounds in drug design, identifying structural properties linked to undesirable traits like toxicity.
  • Existing methods struggle to analytically compare large sets of complex structural filters.

Purpose of the Study:

  • To develop a novel, generic approach for comparing molecular patterns and analyzing structural filter collections.
  • To introduce a tool for automated pattern hierarchy derivation and similarity searching.

Main Methods:

  • Chemically inspired fingerprints were developed for pattern nodes and edges to create a comparable pattern representation.
  • A maximum common subgraph algorithm was applied to annotated pattern graphs to calculate pattern inclusion and similarity.
  • The approach was implemented in a tool called SMARTScompare for the SMARTS language.

Main Results:

  • The developed algorithm enables the calculation of pattern inclusion and similarity.
  • SMARTScompare can automatically derive pattern hierarchies and search large pattern collections for related patterns.
  • The tool's capabilities were demonstrated on a substantial dataset of real-world SMARTS patterns.

Conclusions:

  • This work presents the first algorithm capable of chemical pattern analytics for deriving hierarchies and performing similarity searches.
  • SMARTScompare offers a powerful new capability for analyzing and managing collections of structural filters in molecular design.
  • The approach facilitates more efficient and systematic compound filtering and molecular design processes.