Groß, Christine (2019)
In Silico Studies on Proteins for Synthetic Biology.
Technische Universität Darmstadt
Ph.D. Thesis, Primary publication
|
Text
2019-01-14_Dissertation_Christine_Gross.pdf Copyright Information: CC BY-NC-ND 4.0 International - Creative Commons, Attribution NonCommercial, NoDerivs. Download (13MB) | Preview |
Item Type: | Ph.D. Thesis | ||||
---|---|---|---|---|---|
Type of entry: | Primary publication | ||||
Title: | In Silico Studies on Proteins for Synthetic Biology | ||||
Language: | English | ||||
Referees: | Hamacher, Prof. Dr. Kay ; Thiel, Prof. Dr. Gerhard | ||||
Date: | 2019 | ||||
Place of Publication: | Darmstadt | ||||
Date of oral examination: | 13 December 2018 | ||||
Abstract: | Synthetic biology develops artificial biomolecules or biological systems with novel functionalities for diverse applications in research, medicine or industry. This thesis focuses on in silico studies of three proteins that are promising candidates for enzymatic plastic waste treatment and highly sensitive biosensors, respectively. The first candidate is the enzyme Fusarium solani Cutinase (Longhi and Cambillau 1999), which is able to degrade synthetic polymers, like PET. It allows for the development of an environmental friendly and sustainable solution for plastic waste treatment on an industrial scale. As the wildype enzyme loses its activity during the process of PET degradation, a rational design approach was followed, to improve the activity of this enzyme for PET as substrate. Via MD simulations and linear response theory (LRT) (Ikeguchi et al. 2005) based on coarse-grained elastic network models, the reason for the loss of activity could be identified. Based on the knownledge gained, mutants with improved activity for PET were proposed. In the context of this study, an extension for the LRT method similar to that of a previous study (Knorr 2015) was developed. The second protein system, the hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channel (Santoro and Tibbs 1999), regulates the flux of ions across biological membranes by changes in the membrane voltage and binding of the ligand cAMP. Hence, it is an ideal model for studying the interplay of different domains during the gating process. Together with plenty of other ion channels, it can also serve as building blocks for the assembly of different domains to design synthetic ion channels with novel functionalities. To understand the complex mechanism of HCN gating, the extension of the LRT method was adjusted to work for a tetramer and was used to determine the conformational changes that occur upon binding of the ligand cAMP. In this context, movements in the transmembrane domains that are involved in the gating process were discovered for the first time. They provide important information on the complex gating mechanism and enable a directed planning of further experimental and theoretical investigations. Small viral pore forming proteins also enable the flux of ions across biological membranes and therefore can be seen as viral companions of ion channels. The third protein is such a pore forming protein from HIV and simian relatives SIV, called Vpu (Cohen et al. 1988). As this small protein is less complex than ion channels but also exhibits ion channel function, it is another candidate to serve as building block for the design of artificial ion channels. To consider the Vpu protein as possible building block, the formation of an ion conducting pore has to be a reliable property. In this thesis, the evolutionary conservation of ion channel formation was proved by computing the Shannon entropy (Strait and Dewey 1996) for involved residues based on a multiple sequence alignment. Although the study could not clarify the role of the ion channel function for virus release or replication, the detected evolutionary conservation serves as proof for the functional significance. Hence, this protein reliably forms an ion conducting pore and can be further considered as possible building block for the assembly of synthetic ion channels. |
||||
Alternative Abstract: |
|
||||
URN: | urn:nbn:de:tuda-tuprints-83488 | ||||
Classification DDC: | 500 Science and mathematics > 500 Science 500 Science and mathematics > 570 Life sciences, biology |
||||
Divisions: | 10 Department of Biology > Computational Biology and Simulation | ||||
Date Deposited: | 29 Jan 2019 09:28 | ||||
Last Modified: | 09 Jul 2020 02:28 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/8348 | ||||
PPN: | 44162815X | ||||
Export: |
View Item |