Study on the interactions of sulfonylurea antidiabetic drugs with normal and glycated human serum albumin by capillary electrophoresis-frontal analysisis
| Title in English | Study on the interactions of sulfonylurea antidiabetic drugs with normal and glycated human serum albumin by capillary electrophoresis-frontal analysis |
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| Authors | |
| Year of publication | 2016 |
| Type | Article in Periodical |
| Magazine / Source | JOURNAL OF SEPARATION SCIENCE |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1002/jssc.201600713 |
| Field | Biochemistry |
| Keywords | Binding constant; Capillary electrophoresis-frontal analysis; Glycated human serum albumin; Human serum albumin; Sulfonylureas antidiabetics; |
| Description | Diabetes is one of the most widespread diseases characterised by a deficiency in the production of insulin, or its ineffectiveness. As a result, the increased concentrations of glucose in the blood lead not only to damage to many of the body's systems but also causes the non-enzymatic glycation of plasma proteins affecting their drug binding. Since the binding ability influences its pharmacokinetics and pharmacodynamics, this is a very important issue in the development of new drugs and personalised medicine. In this study, capillary electrophoresis-frontal analysis was used to evaluate the affinities between human serum albumin or its glycated form and the first generation of sulfonylurea antidiabetics, since their inadequate concentration may induce hypoglycaemia or on the contrary hyperglycaemia. The binding constants decrease in the sequence acetohexamide > tolbutamide > chlorpropamide > carbutamide both for normal and glycated human serum albumins, with glycated giving lower values. These results provide a more quantitative picture of how these drugs bind with normal and modified human serum albumin and indicate capillary electrophoresis frontal analysis to be another tool for examining the changes arising from modifications of albumin, or any other protein, with all its benefits like short analysis time, small sample requirement and automation. |
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