<p>When drug molecules are passively absorbed through the cell membrane in the small intestine, the first key step is partitioning of the drug into the membrane. Partition data can therefore be used to predict drug absorption. The partitioning of a solute can be analyzed by drug partition chromatography on immobilized model membranes, where the chromatographic retention of the solute reflects the partitioning. The aims of this thesis were to develop the model membranes used in drug partition chromatography and to study the effects of different membrane components and membrane structures on drug partitioning, in order to characterize drug–membrane interactions.</p><p>Electrostatic effects were observed on the partitioning of charged drugs into liposomes containing charged detergent, lipid or phospholipid; bilayer disks; proteoliposomes and porcine intestinal brush border membrane vesicles (BBMVs), and on the retention of an oligonucleotide on positive liposomes. Biological membranes are naturally charged, which will affect drug partitioning in the human body.</p><p>Proteoliposomes containing transmembrane proteins and cholesterol, BBMVs and bilayer disks were used as novel model membranes in drug partition chromatography. Partition data obtained on proteoliposomes and BBMVs demonstrated how cholesterol and transmembrane proteins interact with drug molecules. Such interactions will occur between drugs and natural cell membranes. In the use of immobilized BBMVs for drug partition chromatography, yet unsolved problems with the stability of the membrane were encountered. A comparison of partition data obtained on bilayer disks with data on multi- and unilamellar liposomes indicated that the structure of the membrane affect the partitioning. The most accurate partition values might be obtained on bilayer disks.</p><p>Drug partition data obtained on immobilized model membranes include both hydrophobic and electrostatic interactions. Such partition data should preferably be used when deriving algorithms or computer programs for prediction of drug absorption.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:uu-5752 |
| Date | January 2005 |
| Creators | Engvall, Caroline |
| Publisher | Uppsala University, Department of Biochemistry, Uppsala : Institutionen för naturvetenskaplig biokemi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Doctoral thesis, comprehensive summary, text |
| Relation | Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, 1651-6214 ; 40 |
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