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In silico Interaktionsanalysen von 17β-Estradiol-Targetstrukturen

Micro-pollutants such as 17β-estradiol (E2) have been detected in different water resources and their negative effects on the environment and organisms have been demonstrated. It is essential to confirm the presence of micro-pollutants in different environments by biosensors and to remove these compounds. In this thesis, E2-binding target structures were used to investigate the underlying binding properties. E2-binding protein, DNA-, and PNA-aptamere (peptide nucleic acid) structures were used as targets to determine physicochemical interactions. The protein dataset consist of 35 publicly accessible three-dimensional structures of E2-protein complexes, from which six representative binding sites could be selected. There is no three-dimensional structure information for an E2-specific DNA aptamer, thus it was modeled using a coarse-grained modeling method. Using sequence information additional DNA aptamers were modeled. The E2 ligand was positioned close to the potential binding area of the aptamer structures, the underlying complexes were investigated by a molecular dynamics simulation, and the interactions were examined by an interaction profiler tool for each time step. A PNA generator was developed that can convert DNA and RNA in silico to more robust, but chemically equivalent PNA. This generator was used to transform the E2-specific DNA aptamer into PNA for binding studies with E2. All formed complexes were investigated with respect to the following non-covalent interaction types: hydrogen bonds, water-mediated hydrogen bonds, π-stacking, and hydrophobic interactions. Ten functional groups could be derived which formed the conserved interactions to E2. The study contributes to the understanding of the behavior of ligands that bind through different target structures in an aqueous solution and to the identification of binding specific interaction partners. The results of this thesis can be used to design novel synthetic receptor and filter systems.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:33620
Date18 April 2019
CreatorsEisold, Alexander
ContributorsMazik, Monika, Labudde, Dirk, Technische Universität Bergakademie Freiberg
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageGerman
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/acceptedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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