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Models and Methods to Evaluate Transport of Drug Delivery Systems Across Cellular Barriers
Published on: October 17, 2013
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Interaction of Camptothecin with Model Cellular Membranes
Phu K Tang1,2, Kaushik Chakraborty1, William Hu3
1Department of Chemistry, College of Staten Island, City University of New York, 2800 Victory Boulevard, 6S-238, Staten Island, New York 10314, United States.
Journal of Chemical Theory and Computation
|March 4, 2020
Summary
Predicting anticancer drug partitioning in membranes is crucial. This study reveals how drug aggregation and interactions with lipid membranes influence drug distribution, impacting pharmaceutical development.
Area of Science:
- Computational Chemistry
- Biophysics
- Pharmacology
Background:
- Accurate prediction of drug partitioning in model membranes is vital for pharmaceutical research and development.
- Understanding drug-membrane interactions is key to designing effective drug delivery systems and predicting drug efficacy.
Purpose of the Study:
- To calculate the potential of mean force for camptothecin (CPT) across various model membrane interfaces using advanced sampling methods.
- To investigate the enthalpic and entropic contributions to CPT's partitioning behavior.
- To explore the impact of drug aggregation and drug-drug interactions on membrane partitioning.
Main Methods:
- Utilized the adaptive biasing force (ABF) methodology for calculating the potential of mean force.
- Simulated CPT across octanol bilayer, octanol/water, and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)/water interfaces.
- Performed long-time microsecond simulations to observe drug aggregation effects at high concentrations.
Main Results:
- Found an inverse relationship between CPT's rotational entropy and its hydrogen bond formation probability with POPC membranes.
- Observed that strong drug-drug aromatic interactions at high concentrations lead to drug stacking.
- Demonstrated that drug stacking facilitates penetration just beneath the POPC head groups, altering spatial orientation.
Conclusions:
- Drug aggregation significantly influences partitioning behavior and membrane interactions.
- Inhomogeneous membrane models must incorporate the effects of drug aggregation for accurate predictions.
- These findings provide insights into the complex dynamics of hydrophobic drug partitioning and membrane penetration.
