The problem of false positives and hits with unfavourable properties obtained in high-throughput screening can be limited by good preparation of compound libraries. Chemical libraries can consist of up to a few million compounds that have the desired properties for further testing. Each compound can be characterized by properties such as chemical structure, purity, quantity and physicochemical properties of the compound. Our library, which contains 887 compounds, was prepared using virtual filtering in KNIME software from the chemicals on our faculty.
The master's thesis aims to develop and optimize high-throughput methods for determining the solubility and partition coefficient that could be applied to our prepared chemical library. The microplate absorbance measurement method and the HPLC method were used to determine the solubility. We determined kinetic and thermodynamic solubility on microplates and then validated the thermodynamic method using the HPLC method on a reversed-phase C18 column. We used the isocratic HPLC method to determine the partition coefficient. We tested three different columns, different mobile phases and organic modifier proportions.
Furthermore, these methods were used to determine the solubility and partition coefficient of 219 model compounds from the chemical library, which was prepared with selected filters in the KNIME software. The method of measuring thermodynamic solubility was developed but unfortunately it did not give good results, as these are poorly reproducible and had a poor correlation with the results of HPLC methods. The method for determining the partition coefficient was not suitable for use on such scale. The Master’s thesis outcomes represent starting points for further development and optimization of the logP HPLC method.
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