Kaufmann, Desirée (2019)
Virtual insights on G protein inhibition and ion channel block – a computer-based study.
Technische Universität Darmstadt
Ph.D. Thesis, Primary publication
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Item Type: | Ph.D. Thesis | ||||
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Type of entry: | Primary publication | ||||
Title: | Virtual insights on G protein inhibition and ion channel block – a computer-based study | ||||
Language: | English | ||||
Referees: | Tietze, Dr. Daniel ; Buntkowsky, Prof. Dr. Gerd ; Hausch, Prof. Dr. Felix ; Fessner, Prof. Dr. Wolf-Dieter | ||||
Date: | 2019 | ||||
Place of Publication: | Darmstadt | ||||
Date of oral examination: | 1 July 2019 | ||||
Abstract: | The present work focuses on understanding the mechanisms of action of two pharmaceutically relevant inhibitor protein systems: the cyclic depsipeptides YM-254890 (YM) and FR900359 (FR) and their target protein, the alpha- (α) subunit of a heterotrimeric G protein as well as conotoxins, venoms obtainable from marine cone snails, which can act as blockers of voltage-gated ion channels. Understanding the mechanism of how drugs or drug candidates are affecting their molecular target is of vital importance in order to develop a promising drug candidate into a valuable medicine. Nowadays, such understanding is mainly gained from computational studies, better known as molecular modelling approaches, which are an essential part of every drug development campaign. Using the example of said two distinct protein ligand systems, respectively consisting of a target protein and an appropriate binding molecule, we aimed at elucidating the intrinsic subtype specificity determinants inherent in interacting biological systems by employing up-to-date computational techniques. Our explorations resulted in the successful generation of reliable data sets that are in accordance with to date published literature from laboratory experiments and might even be able to lay the foundation of learning or training data sets required for further computer-based investigations on similar systems. |
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URN: | urn:nbn:de:tuda-tuprints-91579 | ||||
Classification DDC: | 000 Generalities, computers, information > 004 Computer science 500 Science and mathematics > 500 Science 500 Science and mathematics > 540 Chemistry |
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Divisions: | 07 Department of Chemistry > Eduard Zintl-Institut > Physical Chemistry | ||||
Date Deposited: | 12 Nov 2019 12:59 | ||||
Last Modified: | 09 Jul 2020 02:47 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/9157 | ||||
PPN: | 455718083 | ||||
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