DISSIM: a program for the analysis of chemical diversity

Area of Science:

• Computational chemistry
• Cheminformatics
• Drug discovery

Background:

• Growing interest in database searching and compound selection necessitates robust methods for quantifying chemical similarity.
• Existing methods may not adequately address the selection of diverse chemical subsets from large compound collections.

Purpose of the Study:

• To introduce DISSIM, a computer program designed for selecting diverse subsets from large chemical compound collections.
• To present a pragmatic solution combining a maximum dissimilarity search algorithm with a multidimensional measure of chemical similarity.

Main Methods:

• Development of the DISSIM program incorporating a maximum dissimilarity search algorithm.
• Utilizing a general multidimensional measure of chemical similarity based on combined molecular descriptors.
• Addressing descriptor correlation through appropriate weighting and normalization schemes.

Main Results:

• DISSIM provides a practical approach to selecting diverse chemical compounds.
• The program effectively combines multiple molecular descriptors for a comprehensive similarity assessment.
• Demonstrated application in comparative analysis of topological indices for chemical diversity.

Conclusions:

• DISSIM offers an effective computational tool for chemical diversity analysis and compound selection.
• The methods employed by DISSIM are valuable for managing and analyzing large chemical databases.
• This approach enhances the efficiency of selecting diverse compound libraries for various applications.