Tautomer enumeration and stability prediction for virtual screening on large chemical databases

Area of Science:

• Computational chemistry
• Cheminformatics
• Drug discovery

Background:

• Tautomeric rearrangements significantly influence cheminformatics applications reliant on compound structure.
• Accurate representation of tautomeric forms is crucial for database searching, virtual screening, and property prediction.

Purpose of the Study:

• To introduce TauThor, a novel computational tool for enumerating tautomers.
• To predict the stability of tautomers in aqueous environments.
• To assess the impact of tautomerism on chemical libraries.

Main Methods:

• Tautomer enumeration utilizes a recursive process based on the general tautomerization scheme.
• Tautomer stability is assessed using a fragment library with experimental data and a pK(a)-based method employing MoKa predictions.
• Predicted tautomeric ratios were validated against existing literature data.

Main Results:

• The study demonstrates the impact of tautomerism on chemical databases like FDA, NCI, Specs, and Asinex.
• TauThor provides a method for evaluating the relative abundance of different tautomeric forms.
• pK(a) calculations showed good agreement with literature data for eleven benchmark compounds.

Conclusions:

• TauThor offers a valuable approach for handling tautomerism in cheminformatics.
• Accurate tautomer enumeration and stability prediction enhance the reliability of computational chemistry tools.
• Understanding tautomeric diversity is essential for effective drug discovery and chemical library analysis.