Use of surface charges from DFT calculations to predict intestinal absorption

Area of Science:

• Computational chemistry
• Pharmacokinetics
• Drug discovery

Background:

• Predicting drug absorption is crucial for pharmaceutical development.
• Existing models often lack accuracy for neutral molecules.
• Understanding molecular properties influencing absorption is key.

Purpose of the Study:

• To develop a predictive model for percent intestinal absorption (%Abs) of neutral molecules.
• To utilize surface charges calculated via density functional theory (DFT) for absorption prediction.
• To aid drug design by visualizing molecular contributions to absorption.

Main Methods:

• Developed a model correlating molecular surface charges (decomposed into sigma moments) with partition coefficients.
• Calculated surface charges using density functional theory (DFT).
• Trained and validated the model using a dataset of 241 drugs.

Main Results:

• Achieved a Root Mean Square Deviation (RMSD) of 13%.
• Model demonstrated high accuracy on both training (38 compounds) and high-quality test sets (107 drugs).
• Generated property maps highlighting atoms that affect intestinal absorption.

Conclusions:

• The DFT-based surface charge model accurately predicts intestinal absorption (%Abs) for neutral molecules.
• The model serves as a valuable tool for drug design and optimization.
• Property maps offer insights into molecular interactions with the epithelial membrane.