Structure-interaction relationships between the bile acid GCA and pharmaceuticals using multivariate data analysis...

Area of Science:

• Analytical Chemistry
• Computational Chemistry
• Pharmacology

Background:

• Capillary electrophoresis (CE) is a powerful separation technique applicable to drug-bile acid interaction studies.
• Understanding drug-bile acid interactions is crucial for pharmaceutical development and predicting drug behavior in vivo.
• Glycocholate (GCA) is a primary bile acid involved in drug absorption and disposition.

Purpose of the Study:

• To develop and validate a CE method for precisely measuring drug mobility in the presence of GCA.
• To explore the relationship between pharmaceutical compound structure and their interaction with GCA.
• To build predictive models for drug-GCA interactions using computational descriptors.

Main Methods:

• Capillary electrophoresis (CE) was employed to determine drug mobility in buffer and GCA solutions.
• Two-dimensional (2D) descriptors (using SELMA software) and three-dimensional (3D) quantum mechanical descriptors were utilized.
• Multivariate analysis, specifically Partial Least Squares (PLS), was applied to correlate structural descriptors with experimental CE-interaction data.

Main Results:

• The CE method demonstrated high precision in determining drug mobility.
• Predictive models achieved 85% accuracy when all data was used for training.
• Using separate training and test sets, 2D and 3D models predicted interactions with 78% and 82% accuracy, respectively.
• Hydrophobic properties positively correlated with drug-GCA interaction, while polar properties showed a negative correlation.

Conclusions:

• CE coupled with multivariate analysis provides a robust platform for studying drug-GCA interactions.
• Structural features, particularly hydrophobicity and polarity, significantly influence drug binding to GCA.
• The developed models can predict drug-GCA interactions, aiding in early-stage drug design and pharmacokinetic profiling.