Tautomerism in computer-aided drug design

Area of Science:

• Computational chemistry
• Medicinal chemistry
• Drug discovery

Background:

• Tautomers are frequently overlooked in computational molecular modeling.
• Limited data exists on molecular tautomeric states, and they are seldom recorded in chemical databases.
• Tautomeric forms exhibit variations in shape, functional groups, surface properties, and hydrogen-bonding patterns.

Purpose of the Study:

• To highlight the underaddressed issue of tautomerism in computer-aided drug design.
• To demonstrate the impact of tautomeric states on molecular properties and ligand-protein interactions.

Main Methods:

• The study discusses the differences in physical-chemical properties and molecular descriptors across various tautomeric states.
• Illustrative examples include log P calculations, similarity index, and protein complementarity patterns.
• The impact on ligand-protein interactions and docking predictions is examined.

Main Results:

• Different tautomeric states yield distinct physical-chemical properties and molecular descriptors.
• Tautomerism significantly influences the prediction of ligand binding affinity and complementarity to protein targets.
• Ignoring tautomers can lead to inaccurate assessments in drug design.

Conclusions:

• Tautomerism is a critical factor in computer-aided drug design that requires careful consideration.
• Incorporating tautomeric forms into molecular modeling enhances the accuracy of predicting ligand-protein interactions.
• Addressing tautomerism can improve the success rate of drug discovery efforts.