Drug Distribution. Part 1. Models to Predict Membrane Partitioning
1Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 N Broad Street, Philadelphia, Pennsylvania, 19140, USA.
Pharmaceutical Research
|December 17, 2016
Summary
Two new models predict drug partitioning into cell membranes, crucial for understanding drug distribution and half-life. These models show drug orientation and physicochemical properties are key to accurate partitioning predictions.
Area of Science:
- Pharmacokinetics and Drug Metabolism
- Computational Chemistry
- Membrane Biophysics
Background:
- Tissue partitioning significantly influences drug distribution and elimination half-life.
- Drug distribution is governed by a combination of protein binding and lipid partitioning.
Purpose of the Study:
- To develop and validate structure-based models for predicting drug partitioning into microsomal membranes.
- To assess the role of drug orientation and physicochemical properties in membrane partitioning.
Main Methods:
- Developed an orientation-based model using a membrane template and free energy functions to predict drug conformations and orientations.
- Created a descriptor-based model considering neutral and ionized species for predicting membrane partitioning.
- Validated models using experimental data for multiple drug compounds.
Main Results:
- The orientation-based model accurately predicted membrane positions for nine compounds and partitioning for 67 drugs (average fold-error 2.4).
- The descriptor-based model predicted membrane partitioning for 92 drugs with an average fold-error of 2.0.
- Both models demonstrated the importance of drug orientation and physicochemical properties.
Conclusions:
- Drug orientation is a critical factor in membrane partitioning.
- Physicochemical properties can effectively predict drug membrane partitioning.
- These models offer valuable tools for drug discovery and development by aiding in the prediction of pharmacokinetic properties.
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