Homology modeling of mammalian sodium channels and their verification
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Abstract (EN)
Cell membranes consist of two layers of lipid molecules and are impermeable to ions. Ion transportation across the membrane comes true by means of integral proteins such as ion channels. Voltage gated sodium (NaV) channels are essential elements in ion channels family that responsible for the rapid upstroke of the action potential. Disruption of any ion channels leads to hereditary epilepsy, migraine, periodic paralysis, cardiac arrhythmia and chronic pain syndromes. The crystal structures of bacterial NaV channels that have been determined recently, have made way for studies of mammalian NaV channels through homology modeling. The process of predicting an unknown crystal structure using a known crystal structure is called homology modeling. The crystal structures of nine isoforms of sodium channels (Nav1.1- Nav1.9) found in the mammals are unknown. For this reason, crystal structures are obtained by using homology modeling based on known structures for modeling the systems found in mammals. However, homology modeling becomes difficult because of differences between mammalian and bacterial NaV channels. A crystal structure recently obtained from american cockroach shows a high similarity of 90% in the region where ion permeability occurs in mammals (S5-S6 Region). So our model is based on this crystal structure called NavPaS (PDB ID: 5X0M). Although the crystal structures of the channels found in mammals are not known, experimental results are available for some toxins that selectively bind to these channels. The validation of the models we have developed is based on the knowledge of toxin binding by molecular dynamic simulations and the comparison of these data with the experimental results. The developed models play a key role in understanding the mechanisms of ion permeability and toxin binding in mammals.
Author
Ali Osman Acar
Institution
How to Cite
Ali Osman Acar (Master Thesis). Homology modeling of mammalian sodium channels and their verification, 2017, TOBB Economics and Technology University.
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