Bauer, Daniel (2021)
Computational Study of Voltage-gated Sodium/Potassium channels.
Technische Universität Darmstadt
doi: 10.26083/tuprints-00018611
Ph.D. Thesis, Primary publication, Publisher's Version
|
Text
DB_computational_study_of_hcn_channels.pdf Copyright Information: CC BY-SA 4.0 International - Creative Commons, Attribution ShareAlike. Download (31MB) | Preview |
Item Type: | Ph.D. Thesis | ||||
---|---|---|---|---|---|
Type of entry: | Primary publication | ||||
Title: | Computational Study of Voltage-gated Sodium/Potassium channels | ||||
Language: | English | ||||
Referees: | Hamacher, Prof. Dr. Kay ; Thiel, Prof. Dr. Gerhard | ||||
Date: | 2021 | ||||
Place of Publication: | Darmstadt | ||||
Collation: | 108 Seiten | ||||
Date of oral examination: | 3 December 2021 | ||||
DOI: | 10.26083/tuprints-00018611 | ||||
Abstract: | Ion channels play a fundamental role in all biological entities ranging from small viruses up to complex animals. They are responsible for a vast number of different processes including virus uptake, regulation of the cells ionic balance, proliferation and cell signaling. Potassium channels are selective ion channels that primarily conduct potassium ions. Most channels of this subfamily are not permanently open, but their conductance can be regulated. This allows them to open or close in response to a broad range of environmental conditions. In humans, hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are crucial for various biological processes of the neuronal and cardiovascular system. In the heart, they are responsible for the pacemaker current, which drives the action potential in cardiac pacemaker cells. In the brain, HCN channels contribute to various regulatory functions in neurons and are involved in processes such as the sleep-wake cycle, learning, and brain development. Accordingly, malfunctioning of HCN channels is linked to severe diseases such as arrhythmia and epilepsy. For the present work, molecular dynamics (MD) simulations were used to study several aspects of HCN channels. In the first part, comparative MD simulations were carried out to investigate how the substitution of amino acids at key positions of the HCN1 gene alters the channels structure and dynamics. In combination with experimental data, this information can provide insight into fundamental principles of channel functioning and assist in the understanding and treatment of HCN-mediated diseases. Therefore, several de novo mutations with clinical relevance were investigated. Similar mutational studies were also used to elucidate the role of the conserved HCN domain which is unique for HCN channels. It could be shown that mutation of a single amino acid can disrupt the mechanical connection between domains of the channel and thereby alter gating characteristics. The second part of this work focused on ion conductance. HCN channels discriminate only moderately between potassium and sodium and show a relatively low conductance. Using MD simulations with an applied electric field, it was possible to obtain insights into a unique mechanism that underlies ion conduction in HCN channels: the presented HCN-specific soft knock-on mechanism is an alternation between two distinct states with either two or one ion bound to the selectivity filter (SF) and separated by a single water molecule. Within this model, a theory is presented on how the low selectivity in HCN channels is a result of potassium and sodium binding to the same binding sites within the SF, but with different affinity. Finally, free energy calculations show that the experimentally determined low conductance of HCN channels is a result of high energy barriers within the SF which are not compatible with diffusion-limited conductance. |
||||
Alternative Abstract: |
|
||||
Status: | Publisher's Version | ||||
URN: | urn:nbn:de:tuda-tuprints-186114 | ||||
Classification DDC: | 500 Science and mathematics > 500 Science 500 Science and mathematics > 570 Life sciences, biology 600 Technology, medicine, applied sciences > 610 Medicine and health |
||||
Divisions: | 10 Department of Biology > Computational Biology and Simulation | ||||
Date Deposited: | 10 Dec 2021 12:06 | ||||
Last Modified: | 10 Dec 2021 12:06 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/18611 | ||||
PPN: | 489278841 | ||||
Export: |
View Item |